Adaptive flow controller for use with a flow control system

• US 5,768,121 A
• Filed: 05/24/1995
• Issued: 06/16/1998
• Est. Priority Date: 05/24/1995
• Status: Expired due to Term

• Current Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Original Assignee: Johnson Service Company
• Inventors: Federspiel, Clifford C.
• Primary Examiner(s): Elmore, Reba I.
• Assistant Examiner(s): BROWN, THOMAS
• Application Number:
  US08/448,681
• Time in Patent Office: 1,119 Days
• Field of Search: 236/46 R, 236/49.3, 236/49.5, 236/91 C, 165/16, 73/3, 454/61, 454/370, 454/49, 364/177, 364/148-152, 364/153, 364/157, 364/160-166, 364/176
• US Class Current: 700/28
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/74 for controlling air flow rate or air velocity
• CPC Class Codes: G05B 13/024 in which a parameter or coefficient is automatically adjusted to optimise the performance
• CPC Class Codes: G05D 7/0635 by action on throttling means G05D7/0688, G05D7/0694 take precedence

Abstract

The present invention relates to an adaptive airflow control system for positioning damper systems or controlling air units utilized in an environment control system. The system is based on a conservative, fixed-gain, proportional-only feedback design to guarantee stable operation given the nonlinear behavior of flow through a valve or damper. A time-dependent deadzone of nonlinearity is used to reject measurement noise. Such a system allows a person to adjust the performance of the system by selecting a parameter that affects the tradeoff between tracking capability and noise rejection.

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 unit, the flow sensor generating a flow signal representative of an amount of the air flow provided to the environment;

a memory; and

a processor coupled to the memory and the 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 setpoint error signal and a deadzone of nonlinearity in order to reject noise, said setpoint error signal being the difference between the flow setpoint signal and the flow signal, wherein the processor calculates the deadzone of nonlinearity in accordance with a variance and standard deviation of the flow signal.

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

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 actuator 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 actuator output signal in accordance with cyclical operation of the software-based control algorithm, and wherein the deadzone of nonlinearity is stored in the memory and recalculated each cycle of operation of the control algorithm.

6. The controller of claim 5 wherein the deadzone of nonlinearity is adaptively calculated.

7. The controller of claim 6 wherein the deadzone of nonlinearity is adaptively related to the variance.

8. A controller for use in an environment control system including an air duct including damper operatively associated with actuator, the actuator positioning the damper so that the damper provides a rate of air flow to an environment in response to an actuator control signal, the actuator being operatively coupled to the controller, the controller comprising;

a sensor means for generating an actual flow signal representative of the rate of the air flow provided across the damper;

a memory means for storing information; and

a processor means coupled to the memory means and the sensor means, the processor means for cyclically receiving the actual flow signal from the sensor means and for cyclically generating the actuator control signal in response to the actual flow signal, wherein the actuator control signal is related to a desired rate for the rate of the air flow provided across the damper, the processor means calculating the actuator control signal is accordance with a setpoint error signal and a deadzone of nonlinearity in order to reject noise, said setpoint error signal being the difference between the flow setpoint signal and the flow signal, wherein the deadzone of nonlinearity is calculated in accordance with a variance and standard deviation of the actual flow signal.

9. The controller of claim 8 wherein the setpoint error signal is related to a difference between a flow setpoint signal generated in a previous cycle of operation of the processing means and the actual flow signal received in a current cycle of operation of the processing means.

10. The controller of claim 8 wherein the memory means stores a software-based control algorithm and the processor means generates the actuator output signal in accordance with the software-based control algorithm.

11. The controller of claim 9 wherein the memory means stores a software-based control algorithm and the processor cyclically generates the flow setpoint signal in accordance with cyclical operation of the software-based control algorithm, and wherein the previous cycle is from a most recent previous cycle of operation of the control algorithm.

12. The controller of claim 8 wherein the memory means includes a software-based control algorithm and the processor means cyclically generates the flow setpoint signal in accordance with cyclical operation of the software-based control algorithm, and wherein the deadzone of nonlinearity is stored in the memory means and recalculated each cycle of operation of the control algorithm.

13. The controller of claim 12 wherein the deadzone of nonlinearity is related to a previous deadzone of nonlinearity calculated in a previous cycle.

14. The controller of claim 13 wherein the deadzone of nonlinearity is adaptively related to the variance.

15. 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 a controller output signal from the controller, the flow sensor being exposed to the flow provided by the unit, the flow sensor generating the actual flow signal representative of the amount of flow provided, a method of controlling the amount of the flow provided by the unit comprising steps of:

receiving the actual flow signal from the flow sensor;

determining a setpoint error signal based on the difference between a flow setpoint signal and the actual flow signal;

calculating a deadzone of nonlinearity in accordance with a variance and standard deviation of the 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.

16. The controller of claim 15 wherein the step of determining a setpoint error signal includes determining the setpoint error signal based on a difference between a previous flow setpoint signal and the actual flow signal.

17. The controller of claim 15 wherein the memory includes a software-based control algorithm and the processor generates the actuator output signal in accordance with the software-based control algorithm.

18. The controller of claim 16 wherein the memory includes a software-based control algorithm and the processor cyclically generates the actuator 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.

19. The controller of claim 15 wherein the deadzone of nonlinearity is adaptively calculated, whereby the deadzone of nonlinearity is related to previous values of the deadzone of nonlinearity.

20. The controller of claim 16 wherein the deadzone of nonlinearity is adaptively related to the variance.

determining a setpoint error signal based on the difference between a flow setpoint signal and the actual flow signal;

calculating a deadzone of nonlinearity in accordance with a variance and standard deviation of the 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.