Evolutionary Computing Control Strategy of Nonholonomic Robots with Ordinary Differential Equation Kinematics Model

• DOI: 10.3390/electronics14030601
• Publication Date: 2025-02-03T17:18:56Z
• Authors: Jiangtao Wu; Hong Cheng; Kefei Tian; Peinan Li
• Keywords: Nonholonomic system; Kinematics equations; Bernoulli differential equation

This paper introduces an Evolutionary Computing Control Strategy (ECCS) for the motion control of nonholonomic robots, and integrates ordinary differential equation (ODE)-based kinematics model with a nonlinear predictive (NMPC) strategy particle-based evolutionary computing (PEC) algorithm. The ECCS addresses key challenges traditional NMPC controllers, such as their tendency to fall into local optima when solving optimization problems, by leveraging global capabilities computation. Experiment results on MATLAB Simulink platform demonstrate that proposed significantly improves accuracy reduces errors compared linearized MPC (LMPC) strategies. Specifically, maximum error 90.6% 94.5%, mean square 67.8% 92.6%, root 43.5% 70.3% in velocity steering angle control, respectively. Furthermore, experiments are separately implemented CarSim physical environment verify availability ECCS. These validate effectiveness embedding ODE framework robust efficient robots.