Stochastic Regulation of Nonlinear Multivariable Dynamic Systems.

摘要

Estimation and control algorithms were developed and evaluated for closed-loop regulation of noise-corrupted nonlinear multivariable dynamic systems. The stochastic regulation design procedures involve (1) deterministic multivariable feedback control design at a steady-state operating condition using linear quadratic regulator theory, (2) stochastic estimator design as defined in this study, and (3) closed-loop regulation based on feedback of estimated system state and selected output variables through the deterministic control logic. Four state estimation algorithms were defined: (1) digital smoothing of noisy measurements, (2) digital smoothing plus sensor compensation, (3) Kalman estimation logic using assumed linear plant and sensor dynamics, and (4) Kalman estimation with model-mismatch compensation logic which accommodates uncertainties associated with characterization of nonlinear plant dynamics by an assumed linear model. The developed methodology was evaluated by application to a nonlinear dynamic simulation of the F100/F401 turbofan engine at the military power operating condition.