System Identification and Control of Automatic Car Pedal Pressing System

This paper mainly explores the system identification and control of an automatic car pedal pressing system. Specifically, the system identification was achieved using an artificial neural network, with the help of MATLAB’s System Identification Toolbox. The proportional-integral-derivative (PID) controller and fuzzy logic controller were designed, and normalized with membership functions. These functions were scaled with a gain as a scaling factor. The controller gains were tuned by a metaheuristic algorithm named particle swarm optimization (PSO). On this basis, the two controllers were compared with a number of performance indices, including integral squared error (ISE), integral absolute error (IAE), integral time absolute error (ITAE), and mean squared error (MSE). The car pedal pressing performance was measured at different speed levels for each controller.