Chaoxu Mu

On switching manifold design for terminal sliding mode control

Abstract In this paper, a general design scheme is proposed for finite-time switching mode manifolds and corresponding nonsingular controllers. The reduced system is obtained from terminal sliding mode control (TSMC) and its homogeneity is investigated, which also illustrates that TSMC is finite-time control by the homogeneous theory. Based on the homogeneity analysis, a design proposal is provided for general finite-time switching manifolds and corresponding controllers, which guarantee that all states of a controlled system are finite-time convergent to the origin. In simulations, three finite-time switching manifolds are presented and the corresponding controllers are validated to perform the finite-time control for the double integral system.

A Novel Multiplex Network-Based Sensor Information Fusion Model and Its Application to Industrial Multiphase Flow System

Increasingly advanced technology allows the monitoring of complex systems from a wide variety of perspectives. But the exploration of such systems from a multichannel sensor information viewpoint remains a complicated challenge of ongoing interest. In this paper, first, based on a well-designed double-layer distributed-sector conductance (DLDSC) sensor, systematic oil–water and gas–liquid two-phase flow experiments are carried out to capture abundant spatiotemporal flow information. Second, well flow parameter measurement performance of the DLDSC sensor is effectively validated from the perspective of normalized conductance. Third, a novel multiplex network-based model is presented to implement data mining and characterize the evolution of flow dynamics. The results demonstrate that the model is powerful for the exploration of the spatial flow behaviors from heterogeneity to randomness in the studied two-phase flows.

A continuous sliding mode controller for the PMSM speed regulation based on disturbance observer

This paper mainly studies the speed control for a permanent magnet synchronous motor system. The relationship between the reference quadrature axis current and the speed output is approximately considered as a second-order model. Based on this second-order model, a composite control strategy is adopted, where a continuous sliding mode controller is designed for the speed regulation without chattering and a disturbance observer is introduced as a compensator to resist disturbances and to reduce control gains. Simulation results have been presented to illustrate that the proposed method has good responses to reference speed signals with torque load disturbances.

Nonsingular terminal sliding mode control for speed regulation of permanent magnet synchronous motor with parameter uncertainties and torque change

This paper mainly studies the speed control for a permanent magnet synchronous motor (PMSM) system with parameters uncertainties and torque change. PMSM is a typical nonlinear multivariable coupled system, and is sensitive to the load disturbance and the changing of motor parameters. Hence, the drive performance of PMSM is deteriorated when faced with all kinds of disturbances. A new control algorithm based on nonsingular terminal sliding mode control (NTSMC) is designed to replace the traditional sliding mode control (SMC) in this paper, which can provide effective control for the speed regulation of PMSM servo system with parameter uncertainties and torque change. The high performance in simulation results are proposed to verify the effectiveness of this proposed method.

Adaptive sliding mode control for the speed regulation of PMSMs with load change

This paper mainly studies the speed control for a permanent magnet synchronous motor system. The relationship between the reference quadrature axis current and the speed output is approximately considered as a second-order model. Based on this second-order model, an adaptive sliding mode controller is designed for the speed regulation, which can provide effective control for load torque change and parameter uncertainty. Simulation results are presented to veryfy the proposed method.

Observer-Based Load Frequency Control for Island Microgrid with Photovoltaic Power

As renewable energy is widely integrated into the power system, the stochastic and intermittent power generation from renewable energy may cause system frequency deviating from the prescribed level, especially for a microgrid. In this paper, the load frequency control (LFC) of an island microgrid with photovoltaic (PV) power and electric vehicles (EVs) is investigated, where the EVs can be treated as distributed energy storages. Considering the disturbances from load change and PV power, an observer-based integral sliding mode (OISM) controller is designed to regulate the frequency back to the prescribed value, where the neural network observer is used to online estimate the PV power. Simulation studies on a benchmark microgrid system are presented to illustrate the effectiveness of OISM controller, and comparative results also demonstrate that the proposed method has a superior performance for stabilizing the frequency over the PID control.

Nonsingular terminal sliding mode control for the speed regulation of permanent magnet synchronous motor with parameter uncertainties

The drive performance of permanent magnet synchronous motor (PMSM) can be deteriorated due to various disturbances. In this paper, the problem of speed control for a PMSM system with parameter uncertainties is investigated. A new control algorithm based on nonsingular terminal sliding mode control (NTSMC) is proposed, where the controller is developed for speed regulation. Compared with conventional strategies, this new controller provides improved performance for speed regulation of PMSM when subject to parameter uncertainties, in that it achieves fast dynamic response and strong robustness. Simulation studies are conducted to verify the effectiveness of this proposed method.

Multivariate empirical mode decomposition and multiscale entropy analysis of EEG signals from SSVEP-based BCI system

The steady-state visual evoked potential (SSVEP)-based Brain-Computer Interface (BCI) has been employed in the brain-controlled wheelchair system for patients with severe dyskinesia disease. However, a long-time operation brings about users fatigue, leading to a decrease of performance of the BCI system in practical applications. The characterization of the fatigued mechanism and the improvement of the SSVEP classification accuracy remains a challenging problem of significant importance. In this letter, we first conduct SSVEP experiments to acquire the EEG signals during both normal and fatigued states. Then we develop a novel framework, which integrates the advantages of multivariate empirical mode decomposition (MEMD) and Support Vector Machine (SVM), for improving the SSVEP classification accuracy, especially during the fatigued state. The results suggest that the novel framework enables us to obtain a higher SSVEP classification accuracy compared with the method without MEMD. Furthermore, in order to reveal the fatigued behavior, we use the multivariate multiscale sample entropy (MMSE) to analyze the multi-channel EEG signals corresponding to normal and fatigued states. We interestingly find that the MMSE values in the fatigued state are lower than that in the normal state, which reflects the increase of regularity in SSVEP signals during the fatigued state. That is, a greater synchronization of neural assemblies is required to realize cognitive impairment when fatigue happens. The knowledge for the understanding of the brain fatigued behavior underlying SSVEP-based BCI experiments is gained by our analysis.

Robust Sliding Mode Speed Control with Adaptive Torque Observer for High Performance PMSM

In order to optimize the speed-control performance of the permanent-magnet synchronous motor (PMSM) system with different disturbances and uncertainties, a nonlinear speed-control algorithm for the PMSM servo systems using sliding-mode control (SMC) and load torque compensation techniques is developed in this paper. A SMC strategy is designed based on field oriented control (FOC) theory, which is adopted in the speed loop of PMSM system. Meanwhile, considering the SMC need providing large gain to restrain disturbances resulting in large chattering, an adaptive extended sliding mode torque observer (ESMO) is proposed to estimate and compensate load torque. Through torque estimation for feed-forward compensation, one new composite SMC algorithm has been proposed to take a smaller value of switching gain without large chattering. The control scheme is verified by comprehensive simulation and experimental results.

New two-axis model based field oriented control strategy for single-sided linear induction motors

Due to the particular structure of single-sided linear induction motors (SLIMs), e.g. cut-open magnetic circuit, difference between primary and secondary width, they suffer heavily from longitudinal end-effect and transversal edge-effect. Consequently the secondary flux linkage, secondary resistance and thrust are deteriorated, which would increase the copper loss, thrust ripple, and decrease the efficiency and dynamic response. In this paper, first, a new two-axis model of SLIM that comprehensively considers longitudinal end-effect and transversal edge-effect, is proposed. Second, an improved field oriented control (FOC) strategy for SLIM based on the new model is presented, by which the secondary flux linkage, secondary resistance and thrust can be observed precisely. Third, a compensation method for excitation is implemented to balance the influence of the longitudinal end-effect. Simulations demonstrate the proposed strategy has effective improvements in thrust ripple and dynamic response.