Linear model predictive control of input-output linearized processes with constraints

摘要

An input-output linearization streategy for nonlinear processes with input and/or output constraints is proposed. The nonlinear control system is comprised of: (i) an input-output linearizing controller that compenstates for process nonlinearities; (ii) a constraint mapping procedure that transforms the original constraints into constraints on the feedback linearized system; and (iii) a linear model predictive controller that regulates the resulting constrained linear system, The appraoch combines the computational simplicity of input-output linearization and the constaint handling capability of model predictive control. Simulation results for a continuous stirred tank ractor demonstrate the superior performance of the proposed strategy as compared to conventional model predictive control techniques.