Ali Hajary, Reza Kianinezhad, Seyed Ghodratolah Seyfossadat, Alireza Saffarian, Seyed Seidolah Mortazavi,
Volume 11, Issue 1 (Journal of Control, V.11, N.1 Spring 2017)
Abstract
Control methods for multi-phase machine drives under open-phase fault condition are commonly designed to achieve minimum torque ripple. These methods are usually based on machine fault model. Therefore, it is highly model dependant. In this article, a new robust control method for six-phase induction motors (SPIM) under open-phase fault condition is proposed. Design of ADRC is independent of the controlled system model and machine parameters. This method has been proposed for the first time for multi-phase machines in the post-fault situation. There is no need to change control structure for post-fault operation and machine control in faulty condition is carried out without need to fault detection. Performace of ADRC in healthy and faulty situations are compared with PI and resonant (dual PI) controllers. Simulation results on a six-phase induction motor are presented for verification of the proposed control scheme. It can be seen the six-phase induction motor drive shows better performance when it works with ADRC in both healthy and faulty operation modes.
Nematollah Ghahremani, Reza Mortazavi, Ali Ahmad Barati,
Volume 15, Issue 4 (Journal of Control, V.15, N.4 Winter 2022)
Abstract
In this paper, first, using a test set on a turbocharged diesel engine in the engine test room, a nonlinear model is obtained and it is linearized around several operation points. Then, for the linear models, a linear quadratic integral Gaussian controller (LQIG) with variable parameters as function of engine speed is designed and simulated. In the proposed method, by controlling the wastegate, the boost produced by the turbocharger can be controlled at all engine speeds (especially the lower and middle speeds) with high performance response, thereby improving the output power and engine torque in all speeds. The closed loop control system is simulated and evaluated in the presence of noise and model uncertainty. The simulation results show the better performance and higher robustness in comparison with PID and LQR controllers.
