Comparison of PSO and SQP Methods for Energy Optimization of a Backstepping-Controlled Differential Mobile Robot

This work focuses on improving the energy efficiency of a backstepping-controlled differential mobile robot (WDMR). The controller is designed to track a reference trajectory accurately and efficiently. The control parameters are determined using two different methods: particle swarm optimization (PSO) and sequential quadratic programming (SQP). We compared these two methods on the basis of precision and energy optimization criteria. Through this comparison, we were able to identify an optimal solution by combining the results of both methods. The trajectory tracking achieved satisfies the precision criteria and energy efficiency requirements of the mobile robot.