Permanent magnet synchronous motor (PMSM) will demonstrate chaotic phenomena when its parameters fall into a certain area. The performance of PMSM will degrade because of chaos. Therefore, chaos should be suppressed or eliminated. According to the features of this practical plant, the drawbacks of existing control methods are analyzed, and the nonlinear feedback control method is suggested to control the chaos in PMSM. The nonlinear feedback principle is developed using the direct axis and the quadrature axis stator voltage as manipulated variables. The control target will become a unique asymptotically stable equilibrium under the nonlinear feedback principle, by this way, the controlled states can reach the target and the control objective can be implemented. This method can be physically realized using nonlinear state feedback. The control forces can be put into effect at any time. The target of the method may be any point in the strange attractor. The influence of the model error and the measurement noise upon the control performance is studied via simulations. Simulation results show the effectiveness of this method under the presence of the model error and the measurement noise

The modern world fully relies on wireless communication. Because of intrinsic physical constraints of the wireless physical media (multipath, damping, and filtering), signals carrying information are strongly modified, preventing information from being transmitted with a high bit rate. We show that, though a chaotic signal is strongly modified by the wireless physical media, its Lyapunov exponents remain unaltered, suggesting that the information transmitted is not modified by the channel. For some particular chaotic signals, we have indeed proved that the dynamic description of both the transmitted and the received signals is identical and shown that the capacity of the chaos-based wireless channel is unaffected by the multipath propagation of the physical media. These physical properties of chaotic signals warrant an effective chaos-based wireless communication system.

A novel robust control scheme employing three first-order auto-disturbance rejection controllers (ADRCs) is presented for the speed control of induction motor drives. Compared with the existing high-order ADRC-based speed control structures, the proposed method does not need to estimate the rotor flux. As a result, the implementation of the proposed scheme on a digital signal processor (DSP) is easier, and the runtime of the proposed ADRC control algorithm is shorter. The simulation results show that the proposed control scheme can cope with the internal disturbance and external disturbance, such as the motor's parameter variations, the load disturbances, etc. A TMS320F2812 DSP-based prototype using the proposed control scheme was developed. The comparative experimental results show that the robustness of the proposed ADRC system is obviously better than the conventional proportional-integral system when various disturbances occur, and the scheme is feasible and effective.

In this paper, a fractional order model of pneumatic servo system is introduced by replacing the integer order dynamic equation with the corresponding fractional order one. Then, a Fractional order Proportional-Integer-Differential (FPID) controller is optimized for the servo system using an online multi-variable multi-objective genetic algorithm (MMGA). The proposed MMGA searches in five-dimensional parameter space based on Pareto rank to balance multi-objectives. In order to provide a basis for comparison, the parameters of a Integer order Proportional-Integer-Differential (IPID) controller are also optimized using the same method. The performance indices defined for comparison are the steady state tracking accuracy and the control energy consumption. Additionally, seven other methods from the literature are compared. The experimental results obtained show that the optimized FPID controller results in a better performance than the optimized IPID controller and the other existing approaches.

The work is supported in part by NSFC (Grant no. 61172070), IRT of Shaanxi Province (2013KCT-04), EPSRC (Grant no.Ep/1032606/1).Peer reviewedPostprin