Smart Anti-Pinch Window Simulation Using H-/H∞ Criterion and MOPSO

Automobile power windows are mechanisms that can be opened and shut with the press of a button. Although these windows can comfort the effort of occupancy to move the window, failure to recognize the person's body part at the right time will result in damage and in some cases, loss of that part. An anti-pinch mechanism is an excellent choice to solve this problem, which detects the obstacle in the glass path immediately and moves it down. In this paper, an optimal solution is presented for fault detection of the anti-pinch window system. The anti-pinch makes it possible to detect an obstacle and prevent damages through sampling parameters such as current consumption, the speed and the position of DC motors. In this research, a speed-based method is used to detect the obstacles. In order to secure the anti-pinch window, an optimal algorithm based on a fault detection observer is suggested. In the residual design, the proposed fault detection algorithm uses the DC motor angular velocity rate. Robustness against disturbances and sensitivity to the faults are considered as an optimization problem based on Multi-Objective Particle Swarm Optimization algorithm. Finally, an optimal filter for solving the fault problem is designed using the method. The results show that the simulated anti-pinch window is pretty sensitive to the fault, in the sense that it can detect the obstacle in 50 ms after the fault occurrence.