ADAPTIVE FLOW CONTROLLER FOR USE WITH A FLOW CONTROL SYSTEM AND METHOD

Abstract

An adaptive airflow control system can be used to position damper systems or controlling air units utilized in an environment control system. The environment can include a controller. The controller includes a circuit configured to provide a control signal in response to a sensed flow signal. The control signal is related to a desired rate of flow provided across a component. The circuit is configured to provide the control signal in accordance with a system gain factor calculated using a pressure factor which represents a pressure drop across the component associated with a unit of the environment control system.

Description

NOTICE

A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by any one of the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever.

FIELD OF THE INVENTION

The present application is related to an airflow control apparatus or an environmental control system. More particularly, the present application is related to an adaptive control system for positioning damper systems or controlling air units utilized in an environment control system. U.S. Pat. Nos. 5,768,121 and 5,875,109. Discloses flow control systems and are incorporated herein by reference in their entireties.

Environment control networks, facility management systems, and damper systems are employed in office buildings, manufacturing facilities, and appliances for controlling the internal environment of the facility. For example, in a heating, ventilating, and air conditioning (HVAC) system, controlled air units (e.g., variable air volume (VAV) boxes, unitary devices (UNT) or damper systems) are located throughout the facility and provide environmentally controlled air to the internal environment of the facility. The controlled air is provided at a particular temperature or humidity so that a comfortable internal environment is established. The air flow rate of the controlled air is preferably measured in cubic feet per minute (CFM).

The VAV boxes are coupled to an air source which supplies the controlled air to the VAV box via duct work VAV boxes and unitary devices provide the controlled air through a damper. The damper regulates the amount of the controlled air provided to the internal environment. The damper is coupled to an actuator which preferably positions the damper so that appropriate air flow (in CFM) is provided to the internal environment.

A controller is generally associated with at least one actuator and damper. The controller receives information related to the air flow and temperature in the internal environment and appropriately positions the actuator so that the appropriate air flow is provided to the internal environment. The controller may include sophisticated feedback mechanisms such as proportional (P), proportional integral (PI) or proportional integral derivative (PID) control algorithms. Sophisticated feedback mechanisms allow the actuator to be positioned more precisely.

The controller generally includes a flow control system for positioning the actuator so that the damper provides a desired amount of air flow. The flow control system can measure the actual air flow across the damper and adjusts the position of the actuator until the desired amount of air flow is provided by the controlled air unit. In such systems, the performance of the flow control system (e.g., the accuracy or precision of the position of the system damper) is critical to reliability, energy efficiency, and overall performance of the HVAC system and controlled air unit. Poor flow control often leads to degraded temperature control performance, decreased efficiency for the controlled air unit, and premature mechanical failures for the actuator and damper system associated with the unit.

Flow controllers or flow control systems in HVAC systems can be prone to slow response and poor disturbance rejection due to the inherent non-linear behavior and measurement noise associated with controlled air units such as VAV boxes. The measurement of actual air flow can be strongly affected by turbulence. Additionally, friction, hysteresis, and non-linear relationships between the flow rate and damper position complicate the control of damper systems.

SUMMARY OF THE INVENTION

Some embodiments relate to an environment control system including an air unit for providing air flow to an environment. The air unit is operatively associated with a controller which controls an amount of the air flow in accordance with a flow setpoint signal from the controller. The controller includes a flow sensor exposed to the air flow provided by the air unit. The flow sensor generates a flow signal representative of the amount of the air flow provided to the environment. The controller also includes a memory, and a processor coupled to the memory and the flow sensor. The processor is configured to cyclically receive the flow signal and generates a controller output signal in response to the flow signal and the flow setpoint signal. The controller output signal is provided to the air unit to cause the air unit to provide the amount of the air flow represented by the flow setpoint signal. The processor calculates the controller output signal in accordance with a system gain factor calculated using a pressure factor which represents a pressure drop across a component associated with the air unit.

In some embodiments, a setpoint error signal is related to a difference between a previous flow setpoint signal and the flow signal is determined. In some embodiments, the memory includes a software-based control algorithm, and the processor generates the flow setpoint signal in accordance with the software-based control algorithm. In some embodiments, the memory includes a software-based control algorithm, and the processor cyclically generates the controller output signal in accordance with cyclical operation of the software-based control algorithm. The previous flow setpoint signal is from a most recent previous cycle of operation of the control algorithm. In some embodiments, the memory includes a software-based control algorithm and the processor cyclically generates the controller output signal in accordance with cyclical operation of the software-based control algorithm, and the system gain factor is a maximum system gain. In some embodiments, the system gain factor is calculated according to an equation as follows: 5SQR (Pvalve) f_rated/T where Pvalve is the pressure drop across the component, f_rated is a flow rate at a nominal static pressure, and T denotes a stroke time of an actuator associated with the component. In some embodiments, pressure drop across the component is calculated using an equation as follows: Pvalve=ρQ²e^(a+bθ)/(2A_θ²), where Pvalve is the pressure drop across the component, Q is a flow value, θ is a damper position associated with the component, A_θ is an area of an opening at the damper position, and a and b are constants.

Some embodiments relate to a controller for use in an environment control system. The controller includes a circuit configured to provide a control signal in response to a sensed flow signal. The control signal is related to a desired rate of flow provided across a component. The circuit is configured to provide the control signal in accordance with a system gain factor calculated using a pressure factor which represents a pressure drop across the component associated with a unit of the environment control system.

In some embodiments, the control signal is provided in response to a setpoint error signal which is related to a difference between a flow setpoint signal generated in a previous cycle of operation and the sensed flow signal received in a current cycle of operation. In some embodiments, the circuit provides the control signal in accordance with a software-based control algorithm. In some embodiments, the circuit is configured to provide the control signal in accordance with cyclical operation of a software-based control algorithm. In some embodiments, the circuit is configured to provide the control signal in accordance with cyclical operation of a software-based control algorithm, and the system gain factor is a maximum system gain. In some embodiments, the circuit is configured to provide the control signal in accordance with the system gain factor calculated according to an equation as follows: 5 SQR(Pvalve) f_rated/T where Pvalve is the pressure drop across the component, f_rated is a flow rate at a nominal static pressure, and T denotes a stroke time of an actuator associated with the component. In some embodiments, the pressure drop across the component is calculated using an equation as follows: Pvalve=ρQ²e^(a+bθ)/(2A_θ²), where Pvalve is the pressure drop across the component, Q is a flow value, θ is a damper position associated with the component, A_θ is an area of an opening at the damper position, and a and b are constants. In some embodiments, the pressure drop across the component is sensed using a pressure sensor. In some embodiments, the term valve can refer to pneumatic or fluid control valve. In some embodiments, a valve can be an air unit including a damper. The damper can be moved by an actuator in some embodiments.

Some embodiments relate to a control system including a unit for providing a flow of a fluid, a controller for providing a controller output signal, and a flow sensor for providing an actual flow signal. The controller includes a memory and a processor. The unit is operatively associated with the controller and controls an amount of the flow in accordance with the controller output signal from the controller. The flow sensor is exposed to the flow provided by the unit and provides a flow signal representative of the amount of the flow provided. In some embodiments, a method of controlling the amount of the flow provided by the unit includes steps of: receiving the flow signal from the flow sensor, and providing a control signal in response to the flow signal. The control signal is related to a desired rate of flow provided across a component. The control signal is provided in accordance with a system gain factor calculated using a pressure factor which represents a pressure drop across the component associated with the unit.

In some embodiments, the control signal is provided by determining a setpoint error signal based on a difference between the control signal and the flow signal. In some embodiments, the control signal is provided in accordance with cyclical operation of a software-based control algorithm, and wherein the system gain factor is a maximum system gain. In some embodiments, wherein the control signal is provided in accordance with the system gain factor calculated according to an equation as follows: 5SQR(Pvalve) f_rated/T where Pvalve is the pressure drop across the component, f_rated is a flow rate at a nominal static pressure, and T denotes a stroke time of an actuator associated with the component. In some embodiments, the pressure drop across the component is calculated using an equation as follows: Pvalve=ρQ²e^(a+bθ)/(2A_θ²), where Pvalve is the pressure drop across the component, Q is a flow value, θ is a damper position associated with the component, A_θ is an area of an opening at the damper position, and a and b are constants. In some embodiments, the method further includes measuring the pressure drop using a sensor.

Some embodiments relate to an environment control system which includes an air unit which provides air flow to an environment. The air unit is operatively associated with a controller and controls an amount of the air flow in accordance with a flow setpoint signal. The controller includes a flow sensor, a memory and a processor. The flow sensor is exposed to the air flow provided by the unit and generates a flow signal representative of an amount of the airflow provided to the environment. The processor is coupled to the memory and the sensor and configured to cyclically receive the flow signal and generate a controller output signal in response to the flow signal and the flow setpoint signal. The controller output is provided to the air unit to move the damper to a position corresponding to the flow setpoint signal. The processor calculates the controller output signal in accordance with a setpoint error signal and a deadzone of nonlinearity. The deadzone of nonlinearity is calculated in accordance with a variance of the flow signal.

Some embodiments also relate to a controller for use in an environment control system which includes an air duct including a damper which is operatively associated with an actuator. The actuator positions the damper so that the damper provides a rate of air flow to an environment in response to an actuator control signal. The actuator control signal represents the air flow rate and is operatively coupled to the controller. The controller includes a sensor means, a memory means and a processor means. The sensor means generates an actual flow signal. The memory means stores information. The processor means is coupled to the memory means and the sensor means, and cyclically receives the actual flow signal from the sensor means and cyclically generates the actuator control signal in response to the actual flow signal. The actuator is related to a desired rate for the rate of the air flow provided across the damper. The processor means calculates the actuator control signal in accordance with a setpoint error signal and a deadzone of non-linearity. The deadzone of nonlinearity is calculated in accordance with a variance of the actual flow signal.

Some embodiments also relate to a control system which includes a unit such as a damper or valve for providing flow, a controller for providing a controller output signal, and a flow sensor for providing an actual flow signal. The unit is operatively associated with a controller and controls an amount of the flow in accordance with the controller output signal. The flow sensor is exposed to the flow provided by the unit and generates the actual flow signal representative of the amount of air flow. A method of controlling the amount of the flow provided by the unit comprises the steps of receiving the actual flow signal from the flow sensor, determining a setpoint error signal based on a flow setpoint signal and the actual flow signal, calculating a deadzone of nonlinearity in accordance with a variance of the actual flow signal, applying the deadzone of nonlinearity to the setpoint error signal to develop the controller output signal, and providing the controller output signal to the unit.

Certain aspects of some embodiments adaptively provide a time-dependent deadzone of nonlinearity to reject measurement noise. The user can adjust the performance of the system by selecting a parameter which affects the tradeoff between tracking capability and noise rejection. The deadzone of nonlinearity operates to dampen small adjustments to the actuator control signal thereby reducing the actuator duty cycle.

The flow controller of some embodiments advantageously requires few computations and does not require tuning. In another aspect of the invention, the flow controller is coupled to a memory which receives the deadzone of nonlinearity and recalculates the deadzone of nonlinearity data after each cycle. The flow controller is implemented in a software program.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will hereafter be described with reference to the accompanying drawings wherein like numerals denote like elements, and:

FIG. 1 is a simplified schematic block diagram of an environment control system in accordance with some embodiments;

FIG. 2 is a more detailed schematic block diagram of a controller and a VAV box for use in the environment control system illustrated in FIG. 1 in accordance with some embodiments;

FIG. 3 is a more detailed schematic block diagram of the controller illustrated in FIG. 2 in accordance with some embodiments;

FIG. 4 is a block diagram illustrating the software-based control algorithm for the controller shown in FIG. 3 in accordance with some embodiments;

FIG. 5 is a diagram illustrating the calculation of the pulse width signal based on the pulse width modulation function for the controller shown in FIG. 3 in accordance with some embodiments;

FIG. 6 is a diagram illustrating the calculation of the controller error signal based on the setpoint error signal and the deadzone of nonlinearity for the controller shown in FIG. 3 in accordance with some embodiments;

FIGS. 7A-B show pseudo code in accordance with some embodiments; and

FIG. 8 is a graph showing flow control for the controller illustrated in FIG. 2 in accordance with some embodiments.

DETAILED DESCRIPTION

In some embodiments, a flow control system and method can provide suitable control at low flows. In some embodiments, the systems and methods are less susceptible to performance issues associated with proportional control with variable dead zone (PVDC) algorithms at low flows. In some embodiments, the systems and methods reduce steady state error at low flows (e.g., less than 200 cfm for 800 cubic feet per minute (cfm) for a variable air volume (vav) box) is to less than 10%. In some embodiments, the systems and methods use an adaptive gain to reduce the steady state error to less than 5%.

In some embodiments, the systems and methods have advantages over PVDC algorithms that have a fixed proportional gain for flow control. The proportional gain for such algorithms is generally inversely proportional to the maximum flow of the valve (flow when valve is completely open) for stable control and assumes the valve pressure to be 3 times the design pressure (DesP)=1 in. water column (wc). Thus, the maximum flow is assumed to be sqrt(3)*DesQ, where DesQ is the design flow i.e flow when pressure=DesP and valve is completely open. In some embodiments, the flow control is configured to use an adaptive proportional gain which changes as the static pressure across the valve changes. Instead of blindly using a factor of 3, the flow controller is configured to use the pressure across the valve in steady state to estimate the maximum flow and accordingly update the proportional gain.

In some embodiments, the pressure across the valve can be measured in a variety of ways: 1. By using a pressure sensor which would measure the pressure drop across a valve; 2. By using the flow and damper position to estimate the pressure drop across a valve (e.g., component associated with an air unit). The damper and flow position measurement can be related to area of the opening and flow. In some embodiments, Pvalve=ρQ2e(a+bθ)/(2Aθ²) where Pvalve is pressure across the valve (e.g., component associated with an air unit), Q is flow, θ is the damper position, A_θ is the area of the opening at damper position θ (e.g., the open cross sectional area when the damper is 0 percent open), and a and b are constants. In some embodiments, the flow controller is configured to reduce the proportional gain when steady state error is greater than 10% and increase the gain when the actuator is hunting. In some embodiments, adaptive proportional gain of a PVDC is provided outside of the deadband.

Referring to FIG. 1, a controller may be utilized in an environment control network or system 10. Although a flow controller is described below for use in an HVAC environment, the controller may be utilized in any fluid flow application in some embodiments. For example, the flow controller of may be used in liquid supply systems such as those used in petroleum or chemical processing industries or other flow applications such as those in food preparation, material treatment plants or any industry utilizing controlled flow of material.

Environment control system 10 including a work station 12, a station 14, a station 16, a controller 20, a controller 24, and a controller or module 30. Controllers 20, 24 and module 30 are coupled with station 14 via a communication bus 32. Work station 12, station 14 and station 16 are coupled together via a communication bus 18. Station 16 is also coupled to a communication bus 17. Communication bus 17 may be coupled to additional sections or additional controllers, as well as other components utilized in environment control system 10.

Environment control system 10 is a facilities management system such as the Metasys™ system as manufactured by Johnson Controls, Inc. (JCI) for use with VAV boxes 38 and 40 or a building management system (BMS) in some embodiments. Alternatively, system 10 can be a unitary system having roof-top units, cooling units, or other damper or valve systems. Stations 14 and 16 are stations manufactured by JCI, and controllers 20 and 24 are VAV controllers manufactured by JCI or other controllers known in the art in some embodiments. Controller or module 30 is an air handler control unit (AHU) such as units manufactured by JCI for monitoring and effecting the operation of an air handler (not shown) which provides forced air or air flow for system 10. Controllers 20 and 24 can be any type of computing device for determining control signals for units that provide a flow of fluid (e.g., air).

Communication buses 17 and 32 are N2 buses preferably comprised of a twisted pair of conductors, and communication bus 18 is a LAN (N1) bus for high level communications. Bus 18 is a high speed bus (e.g., an ARCNET™, ethernet protocol, or other protocol). Work station 12 and stations 14 and 16 include ethernet or ARCNET communication hardware. Buses 17 and 32 utilize RS485 protocol. Controllers 20 and 24, module 30, and stations 14 and 16 include RS485 communication hardware. Preferably, controllers 20 and 24, stations 14 and 16 and work station 12 include communication software for transmitting and receiving data and messages on buses 17, 18 and 32.

Controller 20 is operatively associated with a controlled air unit such as VAV box 38, and controller 24 is operatively associated with a controlled air unit such as VAV box 40 in some embodiments. Controller 20 communicates with work station 12 via communication bus 32 through station 14 and communication bus 18. In some embodiments, station 14 multiplexes data over communication bus 32 to communication bus 18. Station 14 operates to receive data on communication bus 32 provide data to communication bus 18, receive data on communication bus 18, and provide data to communication bus 32. Station 14 is capable of other functions useful in environment control system 10 in some embodiments. Work station 12 is a computer, a portable computer, or other computing device which is coupled to communication bus 18. Bus 18 can be part of a wireless network and is not necessarily a physical communication link in some embodiments. Work station 12 can be any remote or local computing device.

The following is a more detailed description of controller 20 and VAV box 38 with reference to FIG. 2 according to in some embodiments. Controller 20 is a direct digital control (DDC) which includes a communication port 34 coupled with communication bus 32 (FIG. 1) in some embodiments. Controller 20 includes an air flow input 56, a temperature input 54 and an actuator output 74 in some embodiments. VAV box 38 may also advantageously include heating or cooling units for treating an air flow 64. Inputs 54 and 56 are y analog inputs received by an A/D converter (not shown) in controller 20 in some embodiments. Controller 20 includes circuitry and software for conditioning and interpreting the signals on inputs 54 and 56 in some embodiments.

VAV control box 38 includes a damper 68, an air flow sensor 52 and an actuator 72 in some embodiments. Actuator 72 positions damper 68 and is an electric motor based actuator. Many controllers use synchronous AC motors with dual winding as actuator 72. In some embodiments, actuator 72 and controller 20 may be pneumatic device, valve, component associated with an air unit, or any other type of device for controlling and positioning damper 68. Actuator 72 is an EDA-2040™ motor manufactured by JCI having a full stroke time (T_stroke) of 1. 2, or 5.5 minutes for a 90° stroke in some embodiments. Although details associated with VAV box 38 is described, controller 20 can be configured for various types of equipment including different types of HVAC equipment.

The position of damper 68 controls the amount of air flow 64 provided to environment 66. Environment 66 can be a room, hallway, residence, building, or portion thereof or other internal environment. Air flow sensor 52 provides an air flow parameter across conductor 58 to air flow input 56. The airflow parameter represents the amount of air flow 64 provided through damper 68 to an environment 66.

Controller 20 provides an actuator output signal to actuator 72 from actuator output 74 via a conductor 76. Controller 20 receives a temperature signal from a temperature sensor 50 across a conductor 60 at temperature input 54. Temperature sensor 50 is generally a resistive sensor located in environment 66.

In some embodiments, air flow sensor 52 is a differential pressure (ΔP) sensor which provides a ΔP factor related to airflow (volume/unit time, hereinafter CFM airflow). CFM airflow may be calculated by the following equation:

$\begin{array}{cc}\mathrm{CMF}\mathrm{Air}\mathrm{Flow}=4005\left(\sqrt{\frac{\Delta P}{K}}\right)\times \mathrm{Box}\mathrm{Area}\mathrm{OR}\mathrm{CMF}\mathrm{Air}\mathrm{Flow}=\mathrm{SQR}\left(\frac{2}{\mathrm{airdensity}}\right)\left(\sqrt{\frac{\Delta P}{K}}\right)\times \mathrm{Box}\mathrm{Area}& \left(1\right)\end{array}$

• • where: ΔP is the differential pressure from air flow sensor 52;
  • Box Area is the inlet supply cross-section area in square feet; and
  • K is a CFM multiplier representing the pickup gain of the air flow.

The value K and value of box area are stored in a memory (not shown) in controller 20 when controller 20 is initialized or coupled with VAV box 38. The value of box area is generally in the range of 0.08 to 3.142 feet squared, and the value of K is generally between 0.58 and 13.08. The value of box area and K may be advantageously communicated from controller 20 to work station 12 so that service people do not have to otherwise obtain these values from paper data sheets and files. Air flow sensor 52 is preferably a diaphragm-based pressure sensor. Air flow sensor 52 can be any device for sensing or determining air flow. In some embodiments, a pressure sensor 53 is provided to provide an indication of pressure across a component such as a valve (e.g., damper 68). The pressure value from optional sensor 53 can be used to determine maximum system gain as explained below in some embodiments.

With reference to FIGS. 1 and 2, the operation of environment control system 10 is described as follows. Controllers 20 and 24 are configured to appropriately position actuator 72 in accordance with a cyclically executed control algorithm, In accordance with the algorithm, controller 20 receives the air flow signal at input 56, the temperature signal at input 54, and other data (if any) from bus 32 at port 34 every cycle, preferably every 1.5 seconds or, alternatively, 1.0 seconds, depending on the controller algorithm. Controller 20 provides the actuator output signal at the actuator output 74 every cycle to accurately position damper 68 so that environment 66 is appropriately controlled (heated, cooled, or otherwise conditioned). Thus, controller 20 cyclically responds to the air flow signal and the temperature signal and cyclically provides the actuator output signal to appropriately control internal environment 66.

The actuator output signals are pulse width signals which cause actuator 72 to move forward, backward, or stay in the same position, and controller 20 internally keeps track of the position of actuator 72 as it is moved in some embodiments. Alternatively, actuator 72 may provide feedback indicative of its position, or the actuator signal may indicate the particular position to which actuator 72 should be moved.

FIG. 3 is a more detailed block diagram of controller 20 in accordance with an exemplary aspect of some embodiments. Controller 20 includes a processor 100 coupled with actuator output 74, temperature input 54, air flow input 56, and communication port 34. Processor 100 is a processor with a communication port 34 is coupled with a twisted pair of conductors comprising communication bus 32 (FIG. 1).

Controller 20 also includes a memory 102. Memory 102 may be any storage device including but not limited to a disc drive (hard or floppy), a RAM, EPROM, EEPROM, flash memory, static RAM, or any other device for storing information. Memory 102 includes RAM and an EEPROM for storing air flow control algorithm data in some embodiments. Memory 102 is coupled to the processor via an internal bus 106.

In operation, processor 100 cyclically samples signals at temperature input 54, actuator output 74, and air flow input 56 and performs mathematical operations on these signals. The mathematical operations generate parameter values representative of the signals at inputs 54 and 56 and output 74. Processor 100 can also sample signals form pressure sensor 53.

With reference to FIG. 4, the operation of system 10 in a dynamic environment 137 is represented in a flow control diagram. Controller 20 is programmed to operate as a flow controller circuit 125 which generates an actuator output signal u(t) to position damper 68 (FIG. 2). Circuit 125 includes an anti-aliasing filter 128, a sampler 130, a controller error circuit 132, a controller output circuit 134 and a timer 136.

Air flow sensor 52 (FIG. 2) generates a continuous time measurement signal z(t). A flow signal f(t) is representative of the amount of air flow to environment 137, and is typically corrupted by noise which is represented by n(t). The combination of the measurement noise signal n(t) and the flow signal f(t) is represented by the continuous time measurement signal z(t) provided by sensor 52.

An analog low-pass anti-aliasing filter 128 receives and filters the continuous time measurement signal z(t) so noise at frequencies higher than the Nyquist frequency of sampler 130 is rejected. Sampler 130 receives the filtered continuous time measurement signal z(t) and provides the filtered signal z(t) to controller error circuit 132 as a discrete air flow signal z(k) which represents the measured air flow signal from flow sensor 52 at the kth instant in time. Controller error circuit 132 receives the discrete air flow signal z(k) from sampler 130 and computes a controller error signal e_c(k) based on a previously-stored flow setpoint signal f_sp(k), the discrete air flow signal z(k) and a deadzone of linearity.

Controller output circuit 134 receives the controller error signal e_c(k) from controller error circuit 132 and computes a pulse signal τ_d(k) to timer 136 based on a desired pulse width τ(k), a minimum pulse width τ(k) a maximum pulse width τ_min, a maximum pulse width τ_max a decay rate ζ, a system gain g_max and the controller error signal e_c(k). The pulse width signal τ(k) represents the change in position of actuator 72 should be positioned, Timer 136 receives the pulse width signal τ(k) and issues the actuator output signal u(t) to actuator 72 (FIG. 2). Actuator 72 receives the actuator output signal u(t) from actuator output 74 via conductor 76 and adjusts the position of damper 68 so that environment 66 is appropriately controlled.

The operation of flow controller circuit 125 is discussed in more detail as follows. Sampler 130 converts the continuous time measurement signal z(t) to a discrete air flow signal z(k).

Controller error circuit 132 receives the discrete air flow signal z(k) and computes the controller error signal e_c(k). Controller error circuit 132 includes a deadzone circuit 138, a controller error signal circuit 142, and a summer 144. Summer 144 calculates a setpoint tracking error signal e_sp(k) based on the difference between the discrete air flow signal z(k) and the flow setpoint signal f_sp(k). The flow setpoint signal f_sp(k) is related to the position to which actuator 72 should have been moved (the desired air flow rate) in the previous cycle and may be user input or calculated by the controller algorithm or other hardware or software components in system 10. The flow setpoint signal f_sp(k) is calculated in response to temperature, air flow or other system parameters. More specifically, the setpoint tracking error signal e_sp(k) is calculated as follows:

$\begin{array}{cc}{e}_{sp}\left(k\right)=f_{sp}\left(k\right)-z\left(k\right)& \left(2\right)\end{array}$

Deadzone circuit 138 also receives the discrete air flow signal z(k) and computes the deadzone of nonlinearity.

The deadzone of nonlinearity is dependent on the amount, variance and standard deviation of noise in the discrete air flow signal z(k). It is adaptively calculated and adaptively related to the setpoint tracking error signal e_sp(k) insofar memory 102 stores the deadzone of nonlinearity which was calculated in the previous cycle of flow controller circuit 125. The deadzone of nonlinearity depends on the chosen system feedback gain g_max and the chosen decay rate ζ for circuit 134.

Controller error signal circuit 142 receives the setpoint tracking error signal e_sp(k) from summer 144, the deadzone of nonlinearity from deadzone circuit 138, and calculates the controller error signal e_c(k) by applying the deadzone of nonlinearity to the setpoint tracking error signal e_sp(k) to reject measurement noise. Therefore, the controller error signal e_c(k) is not necessarily the setpoint error. It is the value calculated by controller error signal circuit 142 after the setpoint tracking error signal e_sp(k) has been processed to eliminate noise. Thus, the user can adjust the performance of flow controller circuit 125 by selecting a parameter that affects the tradeoff between tracking capability and noise rejection.

Controller output circuit 134 receives the controller error signal e_c(k) from controller error signal circuit 142 and generates the new pulse width signal τ(k) representative of the desired air flow or desired position of actuator 72. Controller output circuit 134 includes a desired pulse width circuit 150 and a pulse width modulation logic circuit 152. Pulse width circuit 150 receives the controller error signal e_c(k) and initially calculates the desired pulse width τ_d(k) based on the following equation:

$\begin{array}{cc}{\tau }_d\left(k\right)=\frac{e_c\left(k\right)}{g_{\max }}& \left(3\right)\end{array}$

wherein g_max represents the maximum system gain. The discrete-time integrator is only stable if the system feedback gain is greater than zero and less than approximately two times the inverse of the gain of flow controller circuit 125. Therefore, a preferable stability range for Equation 5 is calculated as follows:

$\begin{array}{cc}0<K<\frac{2}{g_{\max }}& \left(4\right)\end{array}$

where K is the proportional gain of controller 20. In order to guarantee flow controller circuit 125 is stable under all operating conditions, the system feedback gain g_max used in Equation 6 is derived from the worst-case (maximum) gain of the time-varying integrator. Preferably, the following estimate of the worst-case system gain g_max is used in Equation 5:

$\begin{array}{cc}{g}_{\max }=5\sqrt{\mathrm{Pvalve}}\frac{f_{\mathrm{rated}}}{T}& \left(5\right)\end{array}$

The factor of 5 accounts for the effects of the position of actuator 72 and the pressure ratio on the gain. The term f_rated is the flow rate at a nominal static pressure (e.g., one inch of water) when damper 68 is completely open. The factor of Pvalve is the pressure drop across the valve (e.g., component associated with an air unit) in some embodiments. The term T denotes the stroke time of actuator 72. The factor of Pvalve can be measured (e.g. using sensor 53) or estimated in some embodiments. In some embodiments, a model is used to estimate pressure as a function of flow and damper position. The model can be defined by the following equation: Pvalve=f(flow,damperposition).

Estimations of the factor of Pvalve can be made using the below equation:

• • Pvalve=ρQ²e^(a+bθ)/(2A_θ²), where Pvalve is pressure across the valve (e.g., component associated with an air unit); Q is flow, θ is the damper position; A_θ is the area of the opening at damper position θ (e.g., the open cross sectional area when the damper is 0 percent open); and a and b are constants dependent upon size and material of valve and damper. Flow Q can be provided by sensor 52 in some embodiments.

The term gmax is generally within a range from 5.77 to 1371 CFM/sec in some embodiments. In comparison to a system that use a fixed coefficient of 5√3, the use of the coefficient including the term Pvalve makes the coefficient adaptive. In low flow situations if the damper is relatively open, the pressure drop across the valve or component associated with an air unit is not 3 times the rated pressure. With such a fixed coefficient, the proportional gain cannot be made more aggressive without making the system unstable.

Pulse width modulation circuit 134 receives the desired pulse width signal τ_d(k) and issues the pulse signal τ(k) to timer 136 based on the following relationship:

$\begin{array}{cc}\tau \left(k\right)=\left\{\begin{array}{cc}\mathrm{sign}\left({\tau }_d\left(k\right)\right){\tau }_{\max }\mathrm{when}& ❘{\tau }_d\left(k\right)❘>{\tau }_{\max }\\ {\tau }_d\left(k\right)\mathrm{when}& t_{\min }<❘{\tau }_d\left(k\right)❘>{\tau }_{\max }\\ {\tau }_{\min }\mathrm{when}& \left(1-\frac{ϛ}{2}{t}_{\min }\right)<❘{\tau }_d\left(k\right)❘\leqq {\tau }_{\min })\\ 0\mathrm{when}& ❘{\tau }_d\left(k\right)❘\leqq \left(1-\frac{ϛ}{2}\right){\tau }_{\min }\end{array}\right\}& \left(6\right)\end{array}$

where τ_min is the minimum pulse width τ_max is the maximum pulse width and ζ is the decay rate under worst case conditions.

Therefore, pulse width modulation circuit 134 provides timer 136 with the maximum pulse width τ_max when the controller error signal e_c(k) is large, the minimum pulse width τ_min when the controller error signal e_c(k) is small. 0 when the controller error signal e_c(k) is very small and the desired pulse width τ_d(k) when the desired pulse width, τ_d(k) is greater than the minimum pulse width τ_min and less than or equal to the maximum pulse width τ_max Referring to FIG. 5 and Equation 8, the pulse width signal τ(k) drives actuator 72 for the maximum amount of time when the controller error signal e_c(k) is very large as represented by a τ_max point 154. When the controller error signal e_c(k) is small (i.e. τ_min<|τ_d(k)|≤τ_max) actuator 72 is driven the desired amount of time (i.e. τ(k)=τ_d(k) as represented by the linear portion of the graph between τ_max point 154 and a τ_min point 156. Actuator 72 is driven for a minimum amount of time when the controller error signal e_c(k) is smaller as represented by τ_min point 156.

As previously described in conjunction with controller error circuit 132, a pulse-width modulated device with high-gain feedback, such as constant-rate actuator 72, is susceptible to measurement noise which results in an increase in the average duty cycle of actuator 72. Therefore, controller 20 has some ability to reject measurement noise in some embodiments.

During every cycle of operation of flow controller circuit 125, the deadzone of nonlinearity is applied to the setpoint tracking error signal e_sp(k) to reject measurement noise and results in the controller error signal e_c(k). The deadzone of nonlinearity depends on the magnitude of the measurement noise and the acceptable probability controller 20 will issue a pulse width switching signal u(t) that moves the flow signal f(t) away from the flow setpoint signal f_sp(k) when the flow signal f(t) is exactly equal to the flow setpoint signal f_sp(k). This probability is represented by p. The deadzone of nonlinearity also depends on the system feedback gain g_max and the decay rate ζ in Equations 5 and 8.

Referring to FIG. 6, the pulse signal τ(k) and the deadzone of nonlinearity have a direct effect on the setpoint tracking error signal e_sp(k). The minimum setpoint tracking error signal e_sp(k) causes a pulse to be issued by controller output circuit 134 and is dependent on the deadzone of nonlinearity the system gain g_max, and the decay rate ζ. Assuming the measurement noise is normally distributed and there is an acceptable value of p deadzone circuit 138 preferably calculates the deadzone of nonlinearity as follows:

$\begin{array}{cc}\Delta =\max \left[Z\frac{p}{2}\sqrt{R\left(k\right)}-e_1,0\right]& \left(9\right)\end{array}$ $\mathrm{wherein}:$ $\begin{array}{cc}{e}_1=g_{\max }{\tau }_{\min }\left(1+\frac{ϛ}{2}\right)& \left(10\right)\end{array}$

where Zp/2 is the upper P/2 percentage point of the standard normal distribution. R(k) is the variance of the measurement noise and e₁ is the minimum magnitude of the controller error such that a pulse is issued. The parameter p is preferably any number between 0 and 1 and can be specified by the user to achieve a tradeoff between setpoint tracking and duty cycle. For most applications involving cascaded flow and zone temperature control p is small (for example, preferably 0.01). However, there are some applications, such as zone balancing in which the user may make p large (e.g., 0.2-0.3) so that a rapid response with a minimal steady-state error is achieved.

Generally, the variance of the measurement noise changes with time so it is estimated as controller 20 operates. The following equation estimates the variance of the measurement noise:

$\begin{array}{cc}R\left(k\right)=\left(1-w\right)R\left(k-1\right)+w\frac{1}{6}\left(z\left(k-2\right)-2z\left(k1\right)+z\left(k\right)\right)2& \left(12\right)\end{array}$

wherein w represents the filter factor which is calculated as follows:

$\begin{array}{cc}w=\frac{t_s}{T}& \left(13\right)\end{array}$

Where T is the stroke time of actuator 72 and t_s is the sampling interval. Timer 136 receives the pulse signal τ(k) from pulse width modulation logic circuit 152 and issues the actuator output signal u(t) to actuator 72 from actuator output 74 via conductor 76 which adjusts the position of damper 68 so that environment 66 is appropriately controlled. A pulse width switching signal of 1, 0 or −1 represents positive movement, no movement or negative movement, respectively, of actuator 72, and is issued by timer 136 during each cycle of operation of flow controller circuit 125. As illustrated in FIG. 4. this cyclical operation of the software-based control algorithm used in flow controller circuit 125 then begins again by air flow sensor 52 generating the continuous time measurement signal z(t) based on the flow signal f(t) and the measurement noise signal n(t).

In some embodiments, controller 20 is configured by controller executed software. Exemplary controller executed software is provided in FIGS. 7A-B and configures controller 20 for the operations discussed with reference to FIGS. 4-7. The software of FIGS. 7A-7B can be modified to use the adaptive gain discussed above. The software shows basic data collection operations and signal calculations for controller 20. Alternatively, a hardware control circuit, or other software may be utilized to calculate the deadzone of nonlinearity, the flow setpoint signal f_sp(k) and the actuator output signal u(t) for actuator 72 and controller 20.

With reference to FIG. 8, performance of controller 20 is shown. A line 800 represents flow and a line 802 represents flow set point across an X-axis 810 representing time in second and a Y-axis 812 representing flow in cfm. Line 800 represents flow for a controller using a PVDC algorithm with adaptive gain (e.g., inversely proportional to the maximum flow of the valve or component associated with an air unit (flow when valve is completely open) for stable control). The design flow is 800 cfm and the design pressure is 1 inch wc. The close correspondence between line 802 and line 800 shows the accuracy of the PVDC algorithm using adaptive gain.

It is understood, that while the detailed drawings and specific examples given describe some embodiments, they are for the purpose of illustration only. The invention is not limited to the precise details and conditions disclosed. For example, although a particular application is discussed, other applications may utilize the flow controller of some embodiments. Also, although particular facility management systems and components are suggested the system may be configured for various other HVAC systems. The system may easily be configured to utilize metric units. Also, single lines in the various Figures may represent multiple conductors. Various changes may be made to the details disclosed without departing from the spirit of the invention which is defined by the following claims.

Claims

1. In an environment control system including an air unit for providing air flow to an environment, the air unit being operatively associated with a controller and controlling an amount of the air flow in accordance with a flow setpoint signal from the controller, the controller comprising: a flow sensor exposed to the air flow provided by the air unit, the flow sensor generating a flow signal representative of the amount of the air flow provided to the environment;a memory; anda processor coupled to the memory and the flow sensor, the processor configured to cyclically receive the flow signal and generate a controller output signal in response to the flow signal and the flow setpoint signal, the controller output signal being provided to the air unit to cause the air unit to provide the amount of the air flow represented by the flow setpoint signal, the processor calculating the controller output signal in accordance with a system gain factor calculated using a pressure factor, the pressure factor representing a pressure drop across a component associated with the air unit.

2. The controller of claim 1, wherein a setpoint error signal is related to a difference between a previous flow setpoint signal and the flow signal is determined.

3. The controller of claim 1, wherein the memory includes a software-based control algorithm and the processor generates the flow setpoint signal in accordance with the software-based control algorithm.

4. The controller of claim 2, wherein the memory includes a software-based control algorithm and the processor cyclically generates the controller output signal in accordance with cyclical operation of the software-based control algorithm, and wherein the previous flow setpoint signal is from a most recent previous cycle of operation of the control algorithm.

5. The controller of claim 1, wherein the memory includes a software-based control algorithm and the processor cyclically generates the controller output signal in accordance with cyclical operation of the software-based control algorithm, and wherein the system gain factor is a maximum system gain.

6. The controller of claim 5, wherein the system gain factor is calculated according to an equation as follows:

7. The controller of claim 6, wherein the pressure drop across the component is calculated using an equation as follows: Pvalve=ρQ2e(a+bθ)/(2Aθ2), where Pvalve is the pressure drop across the component, Q is a flow value, θ is a damper position associated with the component, Aθ is an area of an opening at the damper position, and a and b are constants.

8. A controller for use in an environment control system, the controller comprising: a circuit configured to provide a control signal in response to a flow value, wherein the control signal is related to a desired rate of flow provided across a component, the circuit configured to provide the control signal in accordance with a system gain factor calculated using a pressure factor, the pressure factor representing a pressure drop across the component associated with a unit of the environment control system.

9. The controller of claim 8, wherein the control signal is provided in response to a setpoint error signal is related to a difference between a flow setpoint signal generated in a previous cycle of operation and the sensed flow signal received in a current cycle of operation.

10. The controller of claim 8, wherein the circuit provides the control signal in accordance with a software-based control algorithm.

11. The controller of claim 9, wherein the circuit is configured to provide the control signal in accordance with cyclical operation of a software-based control algorithm.

12. The controller of claim 8, wherein the circuit is configured to provide the control signal in accordance with cyclical operation of a software-based control algorithm, and wherein the system gain factor is a maximum system gain.

13. The controller of claim 8, wherein the circuit is configured to provide the control signal in accordance with the system gain factor calculated according to an equation as follows:

14. The controller of claim 13, wherein the pressure drop across the component is calculated using an equation as follows: Pvalve=ρQ2e(a+bθ)/(2Aθ2), where Pvalve is the pressure drop across the component, Q is a flow value, θ is a damper position associated with the component, Aθ is an area of an opening at the damper position, and a and b are constants.

15. The controller of claim 13, wherein the pressure drop across the component is is sensed using a pressure sensor.

16. In a control system including a unit for providing a flow of a fluid, a controller for providing a controller output signal, and a flow sensor for providing an actual flow signal, said controller including a memory and a processor, the unit being operatively associated with the controller and controlling an amount of the flow in accordance with the controller output signal from the controller, the flow sensor being exposed to the flow provided by the unit, the flow sensor providing a flow signal representative of the amount of the flow provided, a method of controlling the amount of the flow provided by the unit comprising steps of: receiving the flow value;provide a control signal in response to the flow signal, wherein the control signal is related to a desired rate of flow provided across a component, the control signal is provided in accordance with a system gain factor calculated using a pressure factor, the pressure factor representing a pressure drop across the component associated with the unit.

17. The controller of claim 16, wherein the control signal is provided in accordance with cyclical operation of a software-based control algorithm, and wherein the system gain factor is a maximum system gain.

18. The controller of claim 17, wherein the control signal is provided in accordance with the system gain factor calculated according to an equation as follows:

19. The controller of claim 18, wherein the pressure drop across the component is calculated using a model defined by Pvalve=f(flow, damper position).

20. The controller of claim 18, further comprising measuring the pressure drop using a sensor.