Adaptive Gain Tuning Rule for Nonlinear Sliding-mode Speed Control of Encoderless Three-phase Permanent Magnet Assisted Synchronous Motor

In this paper, an adaptive gain tuning rule is designed for the nonlinear sliding mode speed control(NSMSC) in order to enhance the dynamic performance and the robustness of the permanent magnet assisted synchronous reluctance motor(PMa-Syn RM) with considering the parameter uncertainties. A nonlinear sliding surface whose parameters are altering with time is designed at first. The proposed NSMSC can minimize the settling time without any overshoot via utilizing a low damping ratio at starting along with a high damping ratio as the output approaches the target set-point. In addition, it eliminates the problem of the singularity with the upper bound of an uncertain term that is hard to be measured practically as well as ensures a rapid convergence in finite time, through employing a simple adaptation law. Moreover, for enhancing the system efficiency throughout the constant torque region, the control system utilizes the maximum torque per ampere technique. The nonlinear sliding surface stability is assured via employing Lyapunov stability theory. Furthermore, a simple sliding mode estimator is employed for estimating the system uncertainties. The stability analysis and the experimental results indicate the effectiveness along with feasibility of the proposed speed estimation and the NSMSC approach for a 1.1-k W PMa-Syn RM under different speed references, electrical and mechanical parameters disparities, and load disturbance conditions.

Noise level estimation method with application to EMD-based signal denoising

This paper proposes a new signal noise level estimation approach by local regions. The estimated noise variance is applied as the threshold for an improved empirical mode decomposition（EMD） based signal denoising method. The proposed estimation method can effectively extract the candidate regions for the noise level estimation by measuring the correlation coefficient between noisy signal and a Gaussian filtered signal. For the improved EMD based method, the situation of decomposed intrinsic mode function（IMFs） which contains noise and signal simultaneously are taken into account. Experimental results from two simulated signals and an X-ray pulsar signal demonstrate that the proposed method can achieve better performance than the conventional EMD and wavelet transform（WT） based denoising methods.

Sliding Mode Control with Perturbation Estimation and Hysteresis Compensator Based on Bouc-Wen Model in Tackling Fast-Varying Sinusoidal Position Control of a Piezoelectric Actuator

In this paper,a sliding mode control with perturbation estimation(SMCPE) coupled with an inverse hysteresis compensator is proposed for the motion tracking control of a microposition system with piezoelectric actuation.The inverse hysteresis compensator is employed to cancel the hysteresis nonlinearity,thus reducing the nonlinear system to a linear system with an inversion error.Then,a SMCPE controller is adopted to deal with all the unmodeled dynamics and disturbances,aiming at improving the dynamic performance and the robustness of system.An experiment of a piezoelectric actuator is presented to demonstrate the feasibility and effectiveness of the proposed control scheme.The result shows that for a fast-rate control input,the proposed method is capable of leading to a good performance of system behavior.