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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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