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Universal process control using artificial neural networks

  • US 5,159,660 A
  • Filed: 10/11/1990
  • Issued: 10/27/1992
  • Est. Priority Date: 08/09/1990
  • Status: Expired due to Term
First Claim
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1. A control system for controlling an open-loop stable process, said process having a process output represented by a process output signal, and being responsive to a control signal for changing said process output as a function of said control signal, said system comprising:

  • a) setpoint selection means for generating a setpoint signal representative of a desired value of said process output;

    b) comparator means connected to said setpoint selection means and said process output for comparing said process output signal to said setpoint signal and for deriving from said comparison an error signal representative of the difference between said process output signal and said setpoint signal;

    c) sampling means connected to said comparator means for producing time-spaced samples of said error signal at selected time intervals; and

    d) control means connected to said sampling means and said process, said control means being responsive to said error signal samples for generating said control signal,e) said control means being an artificial neural network, said network including a plurality of layers of neurons connected so as to interact with each other in accordance with variable weights, a first of said layers having a plurality of neuron inputs, and another of said layers having a network output; and

    f) said sampling means being so connected to said network as to simultaneously apply to individual ones of said neuron input signals representative of individual ones of said time-spaced error signal samples, and also to simultaneously vary individual ones of said weights as a function of individual ones of said time-spaced error signal samples.

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