Abstract

This article presents a continuous control-set model-predictive control (CCS-MPC) for speed regulation of a series dc motor powered by a dc-dc converter (buck or boost converter). The proposed control considers the nonlinear structure of the converter-motor system and formulates an optimal control problem that guarantees a unique and global optimum solution in each time step. Furthermore, closed-loop stability is ensured using the discrete-time Lyapunov theory and the Karush-Kuhn-Tucker conditions. A disturbance observer is used to estimate the load torque, enabling precise control and mitigating variations and uncertainties in the parameters. Experimental results in both buck and boost setups demonstrate that the proposed approach achieves faster dynamics, shorter settling times, and more reliable speed regulation compared with traditional methods, for both regulating and tracking speed.