Improved control strategy for PMSM based on fuzzy sliding mode control and sliding-mode observer

Aimed at the problems of large torque ripple,obvious chattering and poor estimation accuracy of back-EMFs in traditional permanent magnet synchronous motor(PMSM)control system with sliding mode observer(SMO),an improved control strategy for PMSM based on a fuzzy sliding mode control(FSMC)and a two-stage filter sliding mode observer(TFSMO)is proposed.Firstly,a novel reaching law(NRL)used in the speed loop based on hyperbolic sine function is studied,and fuzzy control ideal is shown to achieve the self-turning of the parameter for the reaching law,thus a fuzzy integral sliding mode controller based on the novel reaching law is designed in speed loop.Then the suppression effect upon chattering caused by the novel reaching law is analyzed strictly by discrete equation.Secondly,in order to restrain the high frequency components and measurement noise in back-EMFs,a two-stage filter structure based on a variable cut-off frequency low-pass filter(VCF-LPF)and a modified back-EMF observer(MBO)is conceived,and the rotor position is compensated reasonably.As a result,a TFSMO is designed.The stability of the proposed control strategy is proved by Lyapunov Criterion.The simulation and experiment results show that,compared with traditional SMO,the controller suggested above can obtain very nice system respond when the motor starts and is subjected to external disturbances,and effectively improve the problems about torque ripple,chattering and the estimation accuracy of back-EMF.

Bioinspired backstepping sliding mode control and adaptive sliding innovation filter of quadrotor unmanned aerial vehicles

Quadrotor unmanned aerial vehicles have become the most commonly used flying robots with wide applications in recent years.This paper presents a bioinspired control strategy by integrating the backstepping sliding mode control technique and a bioinspired neural dynamics model.The effects of both disturbances and system and measurement noises on the quadrotor unmanned aerial vehicle control performance have been addressed in this paper.The proposed control strategy is robust against disturbances with guaranteed stability proven by the Lyapunov stability theory.In addition,the proposed control strategy is capable of providing smooth control inputs under noises.Considering the modeling uncertainties,the adaptive sliding innovation filter is integrated with the proposed control to provide accurate state estimates to improve tracking effectiveness.Finally,the simulation results demonstrate that the proposed control strategy provides satisfactory tracking performance for a quadrotor unmanned vehicle operating under disturbances and noises.

Pressure-tracking control of a novel electro-hydraulic braking system considering friction compensation

This work presents an integrated pressure-tracking controller for a novel electro-hydraulic brake(EHB) system considering friction and hydraulic disturbances. To this end, a mathematical model of an EHB system, consisting of actuator and hydraulic sub-systems, is derived for describing the fundamental dynamics of the system and designing the controller. Due to sensor inaccuracy and measurement noise, a Kalman filter is constructed to estimate push rod stroke for generating desired master cylinder pressure. To improve pressure-tracking accuracy, a linear friction model is generated by linearizing the nonlinear Tustin friction model, and the unmodeled friction disturbances are assumed unknown but bounded. A sliding mode controller is designed for compensating friction disturbances, and the stability of the controller is investigated using the Lyapunov method. The performance of the proposed integrated controller is evaluated with a hardware-in-the-loop(HIL) test platform equipped with the EHB prototype. The test results demonstrate that the EHB system with the proposed integrated controller not only achieves good pressure-tracking performance, but also maintains robustness to friction disturbances.

Nonlinear Longitudinal Attitude Control of an Unmanned Seaplane with Wave Filtering

A new longitudinal attitude control system design for an unmanned seaplane in the severe sea states is presented in this paper. We develop a nonlinear passive observer, which is used to achieve wave filtering and state estimation. Moreover, the observer can be extended to achieve adaptive wave filtering in varying sea states. Using the estimated low-frequency states, a backstepping sliding mode controller is designed to keep the longitudinal attitude of the unmanned seaplane stable. The stability of the total closed loop system is analyzed by using Lyapunov theory. Simulations are performed in different wave conditions, including Seastate 3 and Seastate 5. The simulations results show that the proposed longitudinal attitude controller can improve the anti-waves capability effectively. Moreover, adaptive wave filter has a significant advantage over a filter with fixed model parameters in varying sea states.

Fingerprint Core Location Algorithm Based on Sliding Window

In order to improve the efficiency of the fingerprint core location algorithm, a fingerprint core location method using sliding window on the basis of core location algorithm with the complex filter was proposed. The local region of the fingerprint image was extracted by a fixed-size window sliding in the region of the fingerprint image, and the selected local region by window as the calculation object is used to detect the core. The experiment results show that the method cannot only effectively detect fingerprint core, but also improve the efficiency of the detection algorithm comparing with the global fingerprint core location detection algorithm.

Novel distributed passive vehicle tracking technology using phase sensitive optical time domain reflectometer

A novel distributed passive vehicle tracking technology is proposed and demonstrated. This technology is based on a phase-sensitive optical time domain reflectometer（Φ-OTDR） that can sense and locate vibrations. Two algorithms, dynamic frequency-space image and 2D digital sliding filtering, are proposed to distinguish a car＇s moving signals from severe environmental noises and disturbances. This technology is proved effective by field experiments for tracking a single car and multiple cars. This work provides a new distributed passive way for real-time vehicle tracking and this technology will be extremely important for traffic controlling and public safety in modern society.