US 5,822,740 AGranted

Adaptive fuzzy controller that modifies membership functions

AssigneeHoneywell Inc.

InventorsChristine M. Haissig, Michael A. Woessner, Dimitris K. Pirovolou

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Abstract

A direct adaptive fuzzy controller having an adaptation mechanism that modifies the locations of output membership functions to improve performance of the fuzzy controller. The controller has a fuzzy rule base that has a different or unique output membership function for each fuzzy rule. The adaptation mechanism modifies the location of the output membership functions in response to the performance of the controller system, to continuously improve its performance. The controller is a feedback mechanism that functions not only using measured outputs of the process controlled, but has feedforward compensation that causes the controller to anticipate feedback due to measured disturbances or other parameters of the process. The adaptive fuzzy controller can be used for various processes, including combi-boiler domestic hot water temperature control, automobile cruise control, a residential thermostat, duct air temperature or static pressure control for the air handling unit in a heating ventilation and air conditioning system, and furnace temperature control for curing parts.

Claims18

Dependent claims

A adaptive fuzzy controller for controlling a process, comprising:

an input processing unit;
an adaptive fuzzy control logic unit connected to said input processing unit;
an output processing unit connected to said adaptive fuzzy control logic unit;
a sensor proximate to the process and connected to said input processing unit;
and
an actuator, for controlling the process, connected to said output processing unit;
and
wherein:
said adaptive fuzzy control logic unit comprises:
an adaptation mechanism connected to said input processing unit;
and
a fuzzy control logic unit connected to said adaptive mechanism and to said input and output processing units;
said sensor provides a process parameter measurement to said input processing unit;
said input processing unit has an input for a process parameter setpoint;
said adaptation mechanism:
computes an error measure between the process parameter measurement and the process parameter set point;
determines whether the absolute value of the error measure is less than an adaptation threshold;
does nothing further if the absolute value of the error measure is less than the adaptation threshold;
obtains degrees of use of fuzzy rules and current locations of output rule membership functions from said fuzzy control logic unit;
calculates new locations of the output rule membership functions;
and
sends the new locations to said fuzzy control logic unit;
said fuzzy control logic unit comprises:
a fuzzifier connected to said output processing means;
a fuzzy inference engine connected to said fuzzifier and to said adaptation mechanism;
a defuzzifier connected to said inference engine and to said output processing unit;
a collection of input membership functions unit connected to said fuzzifier;
a collection of output membership functions unit connected to said adaptation mechanism and said defuzzifier;
and
a fuzzy rule base connected to said fuzzy inference engine, said collection of input membership functions unit and said collection of output membership functions unit;
said sensor provides an environment disturbance parameter measurement to said input processing unit;
said input processing unit has an input for receiving parameters for configuring and adjusting the adaptation fuzzy controller;
the process is hot water temperature control of a boiler;
said sensor comprises:
a temperature sensor;
and
a flow rate sensor;
the process parameter measurement is hot water temperature;
the environment disturbance parameter measurement is hot water flow rate;
and
said actuator is an actuator of a gas valve which controls a flow of gas to a combustion process of the boiler, for heating hot water.

38 more elements

An adaptive fuzzy logic controller for controlling a process parameter, having an adaptive fuzzy control logic which comprises:

an adaptation mechanism for:
computing an error measure;
determining whether the absolute value of the error measure is greater than or equal to an adaptation threshold value;
obtaining degrees of membership of fuzzy rules and current locations of output membership functions of the fuzzy rules, and calculating new locations of the output membership functions of the fuzzy rules, only if the absolute value of the error measure is greater than or equal to the adaptation threshold value;
and
a fuzzy control logic unit comprising:
a fuzzifier for receiving and transforming the process parameter measurement and the process parameter setpoint into a process parameter measurement signal coded with a first set of shapes and locations of input membership functions and a process parameter setpoint signal coded with a second set of shapes and locations of input membership functions;
a collection of input membership functions for providing said fuzzifier with sets of shapes and locations of input membership functions;
a collection of output membership functions, for providing current locations of output membership functions to said adaptation mechanism and for receiving new locations of the output membership functions;
a fuzzy rule base for receiving sets of shapes and locations of input membership functions from said collection of input membership functions, receiving sets of shapes and locations of output membership functions from said collection of output membership functions, and mapping a combination of input membership functions to each output membership function;
a fuzzy inference engine for receiving the process parameter measurement signal coded with a first set of shapes and locations of input membership functions and the process parameter setpoint signal coded with a second set of shapes and locations of input membership functions, receiving a mapping of a combination of input membership functions to each output membership function, indicating the degree to which each fuzzy rule is used, and providing the degrees of membership of the fuzzy rules to said adaptation mechanism;
and
a defuzzifier for receiving sets of shapes and locations of output membership functions from said collection of output membership functions, receiving degrees of membership of the fuzzy rules, and providing command information signals for controlling the process.

10 more elements

An adaptive fuzzy logic controller comprising:

input processing means, having a plurality of inputs for receiving disturbance, setpoint, process parameter, and other parameter signals, and having at least one output, for transforming normalizing, scaling, filtering, integrating, taking derivatives, and/or analog-to-digital converting the signals into an output as specified by an application for controlling at least one process parameter;
an adaptive fuzzy control logic means, having at least one input connected to the at least one output of said input processing means, and having at least one output, wherein said adaptive fuzzy control logic means comprises:
an adaptation mechanism having a first plurality of inputs for receiving the output of said input processing means, a second plurality of inputs indicating degrees of membership of fuzzy control logic rules in that for each time the adaptive fuzzy logic controller cycles, the degree of membership being the extent that each rule was used and indicating a relationship between the inputs and the outputs of the fuzzy control logic means, a third plurality of inputs indicating current locations of output member functions, and a plurality of outputs indicating new locations of output membership functions;
and
a fuzzy control logic having a first plurality of inputs for receiving the output of said input processing means, a second plurality of inputs connected to the plurality of outputs from said adaptation mechanism, a first plurality of outputs connected to the second plurality of inputs of said adaptation mechanism, a second plurality of outputs connected to the third plurality of inputs of said adaptation mechanism, and a third plurality of outputs indicating raw control command information;
wherein said fuzzy control logic comprises:
a fuzzifier having a first plurality of inputs for receiving the output of said input processing means, and a second plurality of inputs indicating shapes and locations and a set of outputs providing a fuzzified output of said input processing means, indicating shapes and locations of the input membership functions, wherein the fuzzified output is taking measured values of the output and transforming them in view of the input membership functions for the outputs;
a collection of input membership functions having a plurality of outputs connected to the second plurality of inputs of said fuzzifier;
a fuzzy rule base having a plurality of outputs for indicating and mapping a combination of input membership functions to each output membership function;
a fuzzy inference engine having a plurality of inputs connected to the plurality of outputs of said fuzzifier, having a second plurality of inputs connected to the plurality of outputs of said fuzzy rule base, and having a plurality of outputs, for indicating the degree to which each fuzzy rule is used;
a collection of output membership functions having a first plurality of outputs indicating the shape and locations of the output membership functions, a second plurality of outputs indicating the current locations of the output membership functions, and a plurality of inputs indicating the new locations of the output membership functions;
and
a defuzzifier having first and second pluralities of inputs connected to the outputs of said fuzzy inference engine and of said collection of output membership functions, having a plurality of outputs indicating raw command information signals;
output processing means, having a plurality of inputs connected to the plurality of outputs of said defuzzifier, and a plurality of outputs indicating raw control command information, signals for transforming, normalizing, scaling, filtering, integrating, taking derivatives, and/or digital-to-analog converting raw command information signals into actuating signals;
and
a process having a first plurality of inputs connected to the plurality of outputs of output processing means, a second plurality of inputs receiving measured disturbances of the process, and a plurality of outputs indicating at least one property of a parameter or parameters being controlled.

13 more elements

An adaptive fuzzy logic controller for controlling a process parameter of a process, comprising:

an input processing unit;
an adaptive fuzzy control logic, connected to said input processing unit, comprising:
an adaptation mechanism for:
computing an error measure;
determining whether the absolute value of the error measure is greater than or equal to an adaptation threshold value;
and
obtaining degrees of membership of fuzzy rules and current locations of output membership functions of the fuzzy rules, and calculating new locations of the output membership functions of the fuzzy rules, only if the absolute value of the error measure is greater than or equal to the adaptation threshold value;
and
a fuzzy control logic unit comprising:
a fuzzifier for receiving and transforming a process parameter measurement and a process parameter setpoint into a process parameter measurement signal coded with a first set of shapes and locations of input membership functions and a process parameter setpoint signal coded with a second set of shapes and locations of input membership functions;
a collection of input membership functions for providing said fuzzifier with sets of shapes and locations of input membership functions;
a collection of output membership functions, for providing current locations of output membership functions to said adaptation mechanism and for receiving new locations of the output membership functions;
a fuzzy rule base for receiving sets of shapes and locations of input membership functions from said collection of input membership functions, receiving sets of shapes and locations of output membership functions from said collection of output membership functions, and mapping a combination of input membership functions to each output membership function;
a fuzzy inference engine for receiving the process parameter measurement signal coded with a first set of shapes and locations of input membership functions and the process parameter setpoint signal coded with a second set of shapes and locations of input membership functions, receiving a mapping of a combination of input membership functions to each output membership function, indicating the degree to which each fuzzy rule is used, and providing the degrees of membership of the fuzzy rules to said adaptation mechanism;
and
a defuzzifier for receiving sets of shapes and locations of output membership functions from said collection of output membership functions, receiving degrees of membership of the fuzzy rules, and providing command information signals for controlling the process;
and
an output processing unit connected to said adaptive fuzzy control unit.

15 more elements

Dependencies are inferred from the claim text.