Synthesis and validation of finite time servo control with PSO identification for automotive electronic throttle

摘要

In order to enhance the rapidity and accuracy of throttle opening trajectory tracking for vehicle electronic throttle control (ETC) systems, a finite time servo control strategy is investigated by incorporating the particle swarm optimization (PSO) identification technique with the finite time stability theory. The PSO technique is adopted to identify the uncertain physical parameters of a real vehicle ETC system. In the PSO-based identification algorithm, the integrated square error between the actual and model throttle opening angles is regarded as the fitness function, and the mutation operation is added to prevent the particles from falling into local optimum. The designed servo controller is comprised of a feed-forward controller for trajectory tracking accuracy, a nonlinearity compensator for friction and return spring, and a feedback controller for finite time stability by utilizing additional power integrator and backstepping technique. The effectiveness of the proposed control strategy is verified by both the comparison results with the existing strategy in MATLAB/Simulink environment and the experiment results carried out on the electronic throttle hardware-in-loop test platform in several actual operating cases.