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By optimizing the predicted performance over a receding horizon, modelpredictive control (MPC) provides the ability to enforce state and controlconstraints. The present paper considers an extension of MPC for nonlinearsystems that can be written in pseudo-linear form with state- andcontrol-dependent coefficients. The main innovation is to apply quadraticprogramming iteratively over the horizon, where the predicted state trajectoryis updated based on the updated control sequence. Output-feedback control isfacilitated by using the block-observable canonical form for linear,time-varying dynamics. This control technique is illustrated on variousnumerical examples, including the Kapitza pendulum with slider-crank actuation,the nonholonomic integrator, the electromagnetically controlled oscillator, andthe triple integrator with control-magnitude saturation.

Output-Feedback Nonlinear Model Predictive Control with Iterative State- and Control-Dependent Coefficients