In this dissertation, optimal switching in switched systems using adaptive dynamic programming (ADP) is presented. Two applications in power electronics, namely single-phase inverter control and permanent magnet synchronous motor (PMSM) control are studied using ADP. In both applications, the objective of the control problem is to design an optimal switching controller, which is also relatively robust to parameter uncertainties and disturbances in the system. An inverter is used to convert the direct current (DC) voltage to an alternating current (AC) voltage. The control scheme of the single-phase inverter uses a single function approximator, called critic, to evaluate the optimal cost and determine the optimal switching. After offline training of the critic, which is a function of system states and elapsed time, the resulting optimal weights are used in online control, to get a smooth output AC voltage in a feedback form. Simulations show the desirable performance of this controller with linear and nonlinear load and its relative robustness to parameter uncertainty and disturbances. Furthermore, the proposed controller is upgraded so that the inverter is suitable for single-phase variable frequency drives. Finally, as one of the few studies in the field of adaptive dynamic programming (ADP), the proposed controllers are implemented on a physical prototype to show the performance in practice. The torque control of PMSMs has become an interesting topic recently. A new approach based on ADP is proposed to control the torque, and consequently the speed of a PMSM when an unknown load torque is applied on it. The proposed controller achieves a fast transient response, low ripples and small steady-state error. The control algorithm uses two neural networks, called critic and actor. The former is utilized to evaluate the cost and the latter is used to generate control signals. The training is done once offline and the calculated optimal weights of actor network are used in online control to achieve fast and accurate torque control of PMSMs. This algorithm is compared with field-oriented control (FOC) and direct torque control based on space vector modulation (DTC-SVM). Simulations and experimental results show that the proposed algorithm provides desirable results under both accurate and uncertain modeled dynamics.

Degree Date

Spring 5-16-2020

Document Type


Degree Name



Mechanical Engineering


Ali Heydari

Subject Area

Mechanical Engineering



Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License