Constrained nonlinear model-based predictive control using ARX-plus Volterra models

In this paper a nonlinear adaptive constrained model predictive control scheme based on models identified from input-output data is proposed. We consider single input-single output (SISO) nonlinear systems described by ARX-plus Volterra models. The proposed control action is obtained by solving a fourth order nonlinear programming problem online subject to linear constraints on the input signal. The adaptive nonlinear control strategy is obtained by augmenting the non-adaptive controller with an indirect parameter estimation scheme which accounts for unknown and/or slowly time-varying parameters. Simulation case study is used to demonstrate the practical utility of the proposed control scheme and to evaluate its performance.