Predictive control method and apparatus
First Claim
1. A predictive control method for controlling a physical object, the physical object being responsive to a manipulated variable signal Un and producing a controlled variable signal Xn, comprising the steps of:
- (1) preparing a multi-layered neural network as an identification model for said physical object;
(2) receiving, at said multi-layered neural network, said controlled variable signal Xn and said manipulated variable signal Un, at a sampling time, and predicting a predicted value Zn+1 for said controlled variable signal Xn using said multi-layered neural network;
(3) computing an error signal Δ
Xn+1 between said predicted value Zn+1 and a desired value dn+1 for said controlled variable signal Xn ;
(4) receiving said error signal Δ
Xn+1 at said multi-layered neural network, finding a correction amount Δ
Un for said manipulated variable signal Un using back propagation within said multi-layered neural network, and correcting said manipulated variable signal Un according to said correction amount Δ
Un;
and(5) transmitting said corrected manipulated variable signal to said physical object and controlling said physical object according to said corrected manipulated variable signal.
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Abstract
This invention relates to a predictive control method and apparatus for controlling a nonlinearly controlled object, such as a manipulator. The method and apparatus can control an object having unknown dynamic characteristics and can compensate for disturbances. A multi-layered neural network is provided as an identification model for the object to the controlled. A controlled variable signal received from the object and a manipulated variable signal for controlling the object are fed into the neural network to predict a future value of the controlled variable signal using forward calculation. The predicted future value is compared with a desired control variable value to produce an error value. The error value is input to the neural network to compute a correction value for the manipulated variable signal using back-propagation. The correction value is used to modify the manipulated variable signal value to thereby control the object.
27 Citations
14 Claims
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1. A predictive control method for controlling a physical object, the physical object being responsive to a manipulated variable signal Un and producing a controlled variable signal Xn, comprising the steps of:
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(1) preparing a multi-layered neural network as an identification model for said physical object; (2) receiving, at said multi-layered neural network, said controlled variable signal Xn and said manipulated variable signal Un, at a sampling time, and predicting a predicted value Zn+1 for said controlled variable signal Xn using said multi-layered neural network; (3) computing an error signal Δ
Xn+1 between said predicted value Zn+1 and a desired value dn+1 for said controlled variable signal Xn ;(4) receiving said error signal Δ
Xn+1 at said multi-layered neural network, finding a correction amount Δ
Un for said manipulated variable signal Un using back propagation within said multi-layered neural network, and correcting said manipulated variable signal Un according to said correction amount Δ
Un;
and(5) transmitting said corrected manipulated variable signal to said physical object and controlling said physical object according to said corrected manipulated variable signal. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A predictive control apparatus for controlling a physical object, the physical object being responsive to a manipulated variable signal Un and producing a controlled variable signal Xn, comprising:
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a multi-layered neural network used as an identification model for said physical object; first means for receiving said controlled variable signal Xn and said manipulated variable signal Un into said multi-layered neural network, at a sampling time, and for predicting a predicted value Zn+1 for said controlled variable signal Xn using said multi-layered neural network; means for computing an error signal Δ
Xn+1 between said predicted value Zn+1 and a desired value dn+1 for said controlled variable signal Xn ;second means for receiving said error signal Δ
Xn+1 into said multi-layered neural network, for finding a correction amount Δ
Un for said manipulated variable signal Un using back propagation within said multi-layered neural network, and for correcting said manipulated variable signal Un according to said correction amount Δ
Un ; andmeans for transmitting said corrected manipulated variable signal to said physical object and controlling said physical object in accordance with said corrected manipulated variable signal. - View Dependent Claims (8, 9, 10, 11, 12, 13, 14)
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Specification