Method and apparatus for controlling multivariable nonlinear processes
First Claim
1. A method for controlling a process having process inputs, process outputs comprising of at least one controlled variable, and an actuator affecting the process, the method comprising computing at least one manipulated variable for use by the actuator to affect the controlled variable in relation to a setpoint, the method comprising the steps of:
- a) obtaining a set of manipulated variables;
b) selecting a first manipulated variable from the set of manipulated variables that has not been previously selected;
c) computing a predicted controlled variable having an associated setpoint and corresponding to said first manipulated variable as a function of the process inputs and outputs, said predicted controlled variable representing the process output as advanced by an optimum prediction time, said optimum prediction time representing the effective response time of the controlled variable to the setpoint;
d) determining sensitivity from a change in value of the predicted controlled variable to a change in value of the corresponding first manipulated variable;
e) determining a difference between the predicted controlled variable and the associated setpoint;
f) incrementing the value of the first manipulated variable in relation to the sensitivity and the difference;
g) repeating steps b) through f) for each manipulated variable from the set of manipulated variables; and
h) repeating steps b) through g) until a predetermined condition is satisfied, said predetermined condition being the determination of the optimum prediction time wherein a minimal change in the manipulated variable is required to affect a change in the controlled variable that minimizes the difference between the controlled variable and the associated setpoint so that the difference is within a predetermined tolerance .
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Abstract
A method and apparatus for a robust process control system which utilizes a neural-network based multivariable inner-loop PD controller cascaded with decoupled outer-loop controllers with integral action, the combination providing a multivariable nonlinear PID and feedforward controller. The inner-loop PD controller employs a quasi-Newton iterative feedback loop structure whereby the manipulated variables are computed in an iterative fashion as a function of the difference between the inner loop setpoint and the predicted controlled variable as advanced by the optimum prediction time, in order to incorporate the downstream limiting effects on the non-limited control loops. The outer-loop controllers compensate for unmodeled process changes, unmeasured disturbances, and modeling errors by adjusting the inner-loop target values.
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Citations
31 Claims
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1. A method for controlling a process having process inputs, process outputs comprising of at least one controlled variable, and an actuator affecting the process, the method comprising computing at least one manipulated variable for use by the actuator to affect the controlled variable in relation to a setpoint, the method comprising the steps of:
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a) obtaining a set of manipulated variables; b) selecting a first manipulated variable from the set of manipulated variables that has not been previously selected; c) computing a predicted controlled variable having an associated setpoint and corresponding to said first manipulated variable as a function of the process inputs and outputs, said predicted controlled variable representing the process output as advanced by an optimum prediction time, said optimum prediction time representing the effective response time of the controlled variable to the setpoint; d) determining sensitivity from a change in value of the predicted controlled variable to a change in value of the corresponding first manipulated variable; e) determining a difference between the predicted controlled variable and the associated setpoint; f) incrementing the value of the first manipulated variable in relation to the sensitivity and the difference; g) repeating steps b) through f) for each manipulated variable from the set of manipulated variables; and h) repeating steps b) through g) until a predetermined condition is satisfied, said predetermined condition being the determination of the optimum prediction time wherein a minimal change in the manipulated variable is required to affect a change in the controlled variable that minimizes the difference between the controlled variable and the associated setpoint so that the difference is within a predetermined tolerance . - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A system for controlling a process, said process responsive to a set of manipulated variables for affecting the process as a function of a controlled variable in order to place the process at a desired setpoint, said system comprising:
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a) means for retrieving a set of current values of the manipulated variables; b) selector means for choosing a selected manipulated variable from the set of current values of the manipulated variables that has not been previously selected; c) a nonlinear function generator for generating a predicted controlled variable as advanced by an optimum prediction time, the optimum prediction time representing the effective response time of the controlled variable to the setpoint; d) a sensitivity processor for determining the sensitivity of a change in value of the predicted controlled variable to a change in the corresponding manipulated variable; e) a first computation means for determining the difference between the predicted controlled variable and the setpoint corresponding to the selected manipulated variable; f) a second computation means for recomputing the value of the selected manipulated variable as a function of said difference, said sensitivity, and said current value; g) a limiter for preventing the selected manipulated variable from exceeding its limits; and h) a processing element for operating said system for all values of the manipulated variable and for completing the operation of said system when a predetermined condition is satisfied. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31)
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Specification