Study On Chaos Control And Synchronization For Complex Motor Systems And Complex Motor Networks

As energy conversion devices, brushless DC motors (BLDCMs) and permanent magnet synchronous motors (PMSMs) have been widely used in industry for the past few years. At the same time, with the development of power electronic technique and control technique, motor networks are becoming an important form of modern industrial production automation. Some investigations have indicated that with certain system parameter values and operating conditions, the single motor and complex motor network exhibit unstable behavior, such as bifurcation or chaos, which threaten the secure and stable operation of motor drive system. To achieve the stable operation of industrial production, we study on the controlling and synchronization chaos in motor systems and motor network in this paper. The main research work of this dissertation has five parts as follows:First, basing on finite-time stability theory and Lyapunov stability theory, we constructed a nonlinear controller to control the undesirable chaos in BLDCM. Theoretical analysis and computer simulation results show the method is very effective.Second, the synchronization of PMSM chaotic system is investigated intensively. By using Lyapunov stability theory and sliding mode control method, we construct controller for synchronization of chaotic PMSM systems. Simulation results show the proposed control law is very effective and robust.Third, we investigate the chaos synchronization in star-coupled complex motor networks based on Lyapunov stability theory. By selecting the drive PMSM system and using coupling functions, we can realize the synchronization of star-coupled complex motor networks. Computer simulation results show the method is very effective.Fourth, we investigate the chaos control in complex motor network. Based on Lyapunov stability theory and pinning control method, we propose pinning controllers to achieve controlling chaos in complex motor network quickly. Finally, simulation results are given to verify the effectiveness and correctness of this technique.Fifth, using adaptive technique, the pinning controller with adaptive coupled strength and adaptive control gains is deduced. And then, the process of controlling chaos in complex motor network is simulated and analyzed. By selecting nodes randomly, we can achieve the control goal with smaller control energy and lower computational complexity.