Adaptive Speed Control for a DC Motor Using DC/DC Converters: An Inverse Optimal Control Approach

This paper proposes an adaptive speed control strategy for DC motors using a DC/DC converter (in buck and boost modes) based on the inverse optimal control (IOC) approach. Our proposal leverages the robust theoretical framework of IOC to derive a control law that ensures the stability and optimal performance of nonlinear dynamical systems through the Lyapunov theory. The control law is designed to minimize a specified cost function, implicitly supporting the optimality of the control strategy. An integral action is incorporated into the IOC approach to enhance performance, ensuring asymptotic stability without affecting convergence properties. The control strategy was implemented on buck and boost converter/DC motor systems. In addition, a disturbance observer technique was utilized for real-time load torque estimation, ensuring precise and efficient control to tackle the challenge posed by unknown and time-varying load torques. Simulations in PLECS and experimental results demonstrate the superiority of the proposed IOC approach compared to conventional cascaded PI control. Our approach reports significantly faster response times and reduced settling times in both buck and boost converter configurations, showcasing its potential for efficient and robust DC motor speed control applications.