Sliding Mode Variable Structure Control Research Articles

Advanced Control Scheme Optimization for Stand-Alone Photovoltaic Water Pumping Systems

This study introduces a novel method for controlling an autonomous photovoltaic pumping system by integrating a Maximum Power Point Tracking (MPPT) control scheme with variable structure Sliding Mode Control (SMC) alongside Perturb and Observe (P&O) algorithms. The stability of the proposed SMC method is rigorously analyzed using Lyapunov’s theory. Through simulation-based comparisons, the efficacy of the SMC controller is demonstrated against traditional P&O methods. Additionally, the SMC-based system is experimentally implemented in real time using dSPACE DSP1104, showcasing its robustness in the presence of internal and external disturbances. Robustness tests reveal that the SMC controller effectively tracks Maximum Power Points (MMPs) despite significant variations in load and solar irradiation, maintaining optimal performance even under challenging conditions. The results indicate that the SMC system can achieve up to a 70% increase in water flow rates compared with systems without MPPT controllers. Furthermore, SMC demonstrated high sensitivity to sudden changes in environmental conditions, ensuring efficient power extraction from the photovoltaic panels. This study highlights the advantages of integrating SMC into Photovoltaic Water Pumping Systems (PV-WPSs), providing enhanced control capabilities and optimizing system performance. The findings contribute to the development of sustainable water supply solutions, particularly in remote areas with limited access to the electrical grid.

Research on Voltage Prediction Using LSTM Neural Networks and Dynamic Voltage Restorers Based on Novel Sliding Mode Variable Structure Control

To address the issue of uncertainty in the occurrence time of voltage sags in power grids, which affects power quality, a voltage state prediction method based on LSTM neural networks is proposed for predicting voltage states. For the problem of quickly and accurately compensating for voltage sags, a DVR system based on a new approach law of sliding mode variable structure control is proposed, which significantly reduces chattering, improves response speed, and enhances the robustness of the system. The stability of the system is proven based on Lyapunov stability theory. Simulation experiments are conducted to analyze the voltage state prediction effect based on the LSTM neural network and the compensation effect of the novel reaching law of sliding mode variable structure control under different levels of voltage sag, validating the effectiveness and correctness of the proposed solution.

Observer-based decoupling control of air flow and pressure in fuel cell systems

This paper investigates the control of the air supply system for marine proton exchange membrane fuel cells. A mathematical model of the air supply system is established, and a sliding mode diagonal decoupling controller based on a state observer is proposed. The control effectiveness is validated through experiments and simulations. A decoupling control strategy for the air supply system of marine fuel cells is presented. First, the load input current of the fuel cell system is selected according to the load characteristics of the target vessel, ensuring that the load current meets the power level of the fuel cell system model. Second, the impact of the cathode pressure on the fuel cell system is analyzed. An observer-based measurement method is proposed to address the measurement issue of cathode pressure. On this basis, a decoupling control strategy combining a diagonal decoupling matrix and sliding mode variable structure control theory is proposed. Finally, the effectiveness of the decoupling controller is validated through Matlab/Simulink. The results show the proposed decoupling controller exhibits superior performance to existing controllers with environmental disturbances, continuous time-varying loads, and step loads. The maximum relative error is 2.95%, the average relative error is 0.022%, and the longest adjustment time is 0.5 s. These results indicate that the control performance of the proposed decoupling controller is superior to that of diagonal PI controllers and sliding mode controllers, thereby validating the superiority of the sliding mode decoupling controller. This article provides a useful method for the development and application of control technology for the air supply system of marine fuel cells.

Research on dynamic modeling and control strategy of four anti-swing cable system for ship-mounted cranes

Ship-mounted cranes are becoming increasingly essential to modern ocean shipping. However, due to the continuous influence of waves, currents, and winds, achieving accurate and fast lifting is difficult because of the large payload swing during the lifting operation. Therefore, this study proposes a Four Anti-swing Cable System (FASCS) for ship-mounted cranes. Firstly, a dynamic model of the FASCS was established by using Robotics and Newton method, and a tension control method (TCM) is designed to reduce the swing angle of the payload. Concurrently, a sliding mode variable structure controller with improved reaching law (SMVSC-IRL) is designed to control the cooperative movement of the anti-swing cables and prevent the occurrence of snap. The dynamic characteristic analysis by MATLAB/Simulink shows that the swing angle suppression effect reaches 89.3% on average, and the projected area of the payload trajectory was reduced by 60%, which can significantly improve the efficiency of ship-mounted cranes lifting operations. In addition, the length and speed of cables in errors can approach 0 within 7 s, and the strong robustness of the designed SMVSC to control the cooperative motion of the anti-swing cables is proved. The results of this study contribute to the in-depth optimization and engineering verification of the FASCS for ship-mounted cranes.

Joint buffetings suppression and trajectory tracking by fuzzy-based super-twist sliding mode control: Application to a fast parallel robot for PnP operations

This paper deals with the suppression of robotic joint buffetings for enhanced precision of trajectory tracking by means of fuzzy-based super-twist sliding mode control, which is illustrated with a fast pick-and-place parallel robot for material handling. Prior to control design, the joint motions and torques are measure to identify the dynamic parameters of the robot with recursive least square method, which is experimentally validated for the further model-based control design. In order to suppress the joint buffetings and to improve the tracking accuracy, the control law by integrating fuzzy algorithm and second-order sliding mode control is designed, where the control performance is evaluated by observing the joint dynamics, compared to the classical computed torque control and fuzzy sliding mode variable structure control. The experimental results and comparative study show the effectiveness of the developed control scheme, regarding the joint buffetings suppression and trajectory tracking precision. The main contribution lies in the integrated fuzzy algorithm and second-order sliding mode control for the model-based control design, with acceptable computational cost and trajectory tracking accuracy, from the perspective of actual engineering application.

Sliding-Mode Control of Linear Induction Motor Based on Exponential Reaching Law

As a strongly coupled, multivariable, high-order nonlinear, time-varying complex system, a linear induction motor is susceptible to outside disturbances and mismatched parameters. Because of its straightforward control mechanism and fixed PI value, the traditional PI regulator is frequently utilized in linear induction motor speed control systems. However, because of these limitations, it frequently falls short of meeting the high-performance control needs of the motor in complex operating conditions. In order to solve the contradiction between the sliding-mode motion reaching time and vibration, the sliding-mode variable structure control is applied to the linear induction motor speed control system in this paper. The sliding-mode controller is designed using the exponential reaching law method, and the designed system is analyzed through simulation. The findings demonstrate how the controller enhances the system’s robustness and disturbance resistance by bringing about the advantages of rapidity, stability, no overshooting, and a strong resistance to load disturbance.

An Improved Predictive Controller for PMSM based on Dual-Channel Feedback

Abstract High-performance and high-power-density DC servo drives of permanent magnet synchronous motors (PMSM) are applied to the military, especially in airborne optoelectronic pods, light mines, and launch turntables in the aerospace field. The above application scenarios require the volume of drivers to be smaller and have large power outputs. In the field of pods and light mines, high bandwidth and good tracking performance are required, especially in terms of steady-state accuracy. Since light mines are used for target tracking scanning, the errors at the end of the optical rotating mechanism are amplified tens or even hundreds of times after transmission through the line of sight to the target end. Therefore, the requirements for steady-state accuracy are extremely high. In this article, a predictive control method is proposed, using a sliding mode variable structure controller to make up for the error arising from system parameter changes in predictive control. Finally, a dual-channel rotary transformer feedback position coarse-fine combination algorithm method is studied to reduce the angular measurement error and further improve steady-state accuracy.

Integrated dynamics and control of space multi-joint robotic arm

This paper presents research on the integrated dynamics and control methods of a multi-joint robotic arm system installed on a spatial inertial platform. An integrated recursive dynamic model of the posture of the multi-joint robotic arm is established by using the method of dual quaternions. This model can succinctly describe the position and attitude relationships among the joints of the robotic arm. Based on this model, a sliding mode variable structure controller is designed, which can achieve convergence of position and attitude errors even in the presence of external disturbances. The designed controller is validated through simulations, the results of which demonstrate satisfactory control performance, offering reference value for practical engineering applications.

Active and passive heave compensation system based on feedback linearization sliding mode variable structure control

This study presents a novel electric-hydraulic servo system with an active–passive lift compensation feature designed for a lifting crane used in offshore operations. Additionally, the study explores the control methodology of this system. Firstly, the principle of the combined active–passive lift-compensated system is explained, and the mathematical model of the response is established. To eliminate the strong nonlinearities inherent and mismatched term, the method of exact input-state linearization is employed. For observing the uncertain disturbance terms in the model, a new type of expanded state sliding mode observer(ESSMO) is designed. Subsequently, a control strategy of sliding mode with variable structure is designed using the method of hyperbolic convergence law. The stability of the controller is proved based on Lyapunov’s stability theorem. Finally, the control method is simulated and analyzed under different working conditions and compared with traditional PID control and sliding mode control strategies directly designed by the nonlinear model. The simulation results demonstrate that the feedback linearized hyperbolic convergence law sliding mode control strategy not only reduces dependence on exact parameters of the original system but also exhibits strong robustness and suppression of model nonlinearities and parameter uncertainty.

The Adaptive Bilateral Control of Underwater Manipulator Teleoperation System with Uncertain Parameters and External Disturbance

A novel self-adaptive bilateral control strategy is introduced to manage uncertainties inherent in the teleoperation of an underwater manipulator system effectively. In response to uncertainties stemming from both the mathematical model and external disturbances, our approach offers innovative solutions. Firstly, to address uncertainties in the master model parameters, we propose a reference adaptive impedance control based on a nominal model. This control strategy dynamically adjusts the reference position of the desired model, leveraging adaptive control laws to compensate for model uncertainties. Additionally, to tackle uncertainties specific to the slave manipulator, we employ adaptive compensation using radial basis function (RBF) networks. Our unique combination of sliding mode variable structure controllers and robust adaptive controllers aims to mitigate approximation errors, ensuring precise tracking of the master manipulator’s position by the slave manipulator. By employing Lyapunov function analysis, we demonstrate the system’s superior tracking performance and global stability, with assured asymptotic convergence for force–position tracking. Through comprehensive experimentation, our results showcase the exceptional force–position tracking capabilities of the overall control system, even under challenging conditions of model uncertainties and external disturbances. Moreover, our system exhibits remarkable stability, reliability, and robustness, underscoring the effectiveness of our proposed adaptive control approach.

Improved Sliding Mode Variable Structure Control of Robot Manipulators with Flexible Joints based on Singular Perturbation

This paper discusses the kinematics analysis method of six link mechanism based on virtual prototype technology and Adams. Firstly, the kinematics mathematical model of the six-bar linkage is deduced. Then, based on the design and development process of virtual prototype technology, the virtual prototype model of the six-bar press is established in ADAMS software. Finally, the kinematics simulation analysis is carried out for the model. The proposed method provides a reference for the parametric and optimal design analysis of the multi bar linkage of the mechanical press.

Sliding‐mode variational structure study of Cuk converter based on target holographic feedback

SummaryWith the rapid advancement of new energy sources, distributed power supplies have gained widespread adoption in DC microgrid systems. The stability of the DC‐DC converter, serving as the central component for energy transfer between the distributed power supply and the DC bus, holds significant importance in ensuring the overall system performance. Due to the intricate nature of real‐world operating conditions, the DC bus voltage is frequently subject to uncertainties such as fluctuations in distributed power supplies and random variations in loads. As a consequence, the reliability of DC‐DC converters faces escalating demands, making it challenging for conventional linear controllers to ensure consistent operation of DC‐DC converters across a broad range. This study focuses on addressing this issue by investigating the Cuk converter, which serves as a representative example of a single‐input multiple‐output system. The operating characteristics and control challenges of the Cuk converter are analyzed, and a nonlinear control strategy based on target holographic feedback is proposed to enhance the system's stability. Considering the non‐minimum phase characteristics of the Cuk converter and its inability to be linearized through exact feedback, a sliding mode variable structure control approach is introduced, utilizing target holographic feedback. Through simulation and experimental analysis, the effectiveness of the model and the theoretical analysis are validated.

Sliding mode variable structure control of RP manipulator based on computational torque

Study the control problem of a coupled robotic arm with moving and rotating joints, a PID control method based on calculated torque is proposed. Considering that the robot model is difficult to obtain accurately, only its estimation model can be obtained. The output feedback signal is used to define the sliding mode surface function with error signal. Sliding mode variable structure controller(SMVSC) is designed based on the computational torque control method. Taking the mathematical model of RP robot as an example, Experimental calculations have found that the control accuracy can be guaranteed, but there is a significant chattering situation. In engineering practice, it is necessary to process the symbol function.

Agile Attitude Maneuver Control of Micro-Satellites for Multi-Target Observation Based on Piecewise Power Reaching Law and Variable-Structure Sliding Mode Control

This paper addresses the issue of agile attitude maneuver control for low-Earth-orbit satellites during short arc segments for multi-target observations. Specifically, a configuration design for Control Moment Gyroscopes (CMGs) and a hybrid control law are provided. The control law is adept at avoiding singularities and escaping singular planes. Subsequently, an optimal time-based attitude maneuver path-planning method is presented, rooted in the relationship between Euler angles/axis and quaternions. Furthermore, a novel satellite attitude maneuver controller is developed based on a piecewise power-reaching law for variable structure sliding mode control. The paper theoretically demonstrates that the proposed piecewise power reaching law possesses two favorable properties regarding convergence time. On the other hand, the designed reaching law maintains continuity at all stages, theoretically eliminating buffeting. The simulation results demonstrate that the proposed controller achieves an Euler angle control precision of ±0.03° and angular velocity accuracy of ±0.15°/s, fulfilling the demands of multi-objective observational tasks. Compared to conventional power reaching law controllers, the convergence time is reduced by 3 s, and Euler angle accuracy is improved by 70%. This underscores the effectiveness of the proposed algorithm.

Application of sliding mode variable structure control algorithm in PMSM vector control system in complex environment.

In order to meet the increasing demand of high-performance control in industrial production, a new sliding mode variable structure control algorithm, Asymptotic Sliding Mode Control (ASMC), is designed in this study to solve the serious chattering problem of sliding mode control. Firstly, a traditional sliding mode exponential approximation law control model and a state space and control function are constructed based on sliding mode control. Secondly, by eliminating the jitter factor, ASMC algorithm is combined with sliding mode control to achieve precise control of permanent magnet synchronous motor (PMSM) and improve its performance. The experimental results indicated that in the simulation experiment, the research system tended to stabilize within 0.2-0.3 seconds, and the system chattering was significantly suppressed. And its output was smoother, the jitter amplitude was significantly reduced by 1/3, and the output torque was more stable. In addition, when the parameter H0 changed to 2H0, the overall speed curve did not change much, with only a slight overshoot. The overshoot was only 2.8%, and the change amplitude was maintained at around 25r/min, indicating that the research system had strong self stability performance. In actual experiments, the current command oscillation of the research system was significantly reduced. The local graph showed that the output fluctuation amplitude of the asymptotic approach law actual control was significantly smaller under no-load disturbance. When the H0 changed towards 2H0, the actual adjustment time was about 0.1 seconds, which was consistent with the simulation experiment. Therefore, the contribution of the research is that the ASMC algorithm can suppress the chattering problem of the system and improve the approaching speed, thus improving the speed regulation quality of the system. This new algorithm has great theoretical and practical significance for improving the performance of PMSM, and is practical in the actual vector control system of PMSM.

Path Planning and Tracking Control of Tracked Agricultural Machinery Based on Improved A* and Fuzzy Control

In order to improve the efficiency of agricultural machinery operations and reduce production costs, this article proposes a path planning algorithm based on the improved A* algorithm (IA*) and a tracking controller based on fuzzy sliding mode variable structure control (F-SMC) to meet the operation requirements of tracked agricultural machinery. Firstly, we introduce a heuristic function with variable weights, a penalty, and a fifth-order Bezier curve to make the generated path smoother. On this basis, the ant colony algorithm is introduced to further optimize the obtained path. Subsequently, based on fuzzy control theory and sliding mode variable structure control theory, we established a kinematic model for tracked agricultural machinery as the control object, designed a fuzzy sliding mode approaching law, and preprocessed it to reduce the time required for sliding mode control to reach the chosen stage. The simulation experiment of path planning shows that compared with A*, the average reduction rate of the path length for IA* is 5.51%, and the average reduction rate of the number of turning points is 39.01%. The path tracking simulation experiment shows that when the driving speed is set to 0.2 m/s, the adjustment time of the F-SMC controller is reduced by 0.99 s and 1.42 s compared to the FUZZY controller and PID controller, respectively. The variance analysis of the adjustment angle shows that the minimum variance of the F-SMC controller is 0.086, and the error converges to 0, proving that the vehicle trajectory is smoother and ultimately achieves path tracking. The field test results indicate that the path generated by the IA* algorithm can be tracked by the F-SMC controller in the actual environment. Compared to the A* algorithm and FUZZY controller, the path tracking time reduction rate of IA* and F-SMC is 29.34%, and the fuel consumption rate is reduced by 2.75%. This study is aimed at providing a feasible approach for improving the efficiency of tracked agricultural machinery operations, reducing emissions and operating costs.

Research on Optimal Fast Terminal Sliding Mode Control of Horizontal Vibration of High-speed Elevator Car System

An optimal fast terminal sliding mode control strategy is proposed to suppress effectively the horizontal vibration of the high-speed elevator car system is caused by uncertainties such as rail unevenness, elevator load variation, and component friction and wear. Firstly, considering the elevator's composition structure and vibration characteristics, a 4-degree-of-freedom car system horizontal vibration active control model with a symmetric distribution of the control center is established. Secondly, considering the nonlinear factors of the rolling guide shoe and the external excitation, an optimal fast terminal sliding mode controller (PFTSMC) based on the sliding mode variable structure control is designed to eliminate the horizontal vibration of the car, define the nonsingular terminal sliding mode surface, and introduce the fast terminal convergence law based on the fast terminal attractor to ensure the accessibility of the sliding mode motion and reduce the jitter vibration. In addition, optimization of controller parameters using random weight particle swarm algorithm (RNW-PSO) to improve the controller's vibration suppression performance and robustness. Finally, the proposed controller can achieve more than 51.2% attenuation of horizontal vibration acceleration and displacement, showing that PFTSMC can effectively reduce the horizontal vibration of high-speed elevator car systems and improve ride comfort.

Depth control of an unmanned underwater vehicle based on robust inversion and sliding mode variable structure control

This paper addresses the depth control problem of an underactuated Unmanned Underwater Vehicle (UUV) subject to model uncertainties and ocean current interference. A robust inversion sliding mode variable structure control method is proposed. First, a vertical-plane UUV depth control model is established. Then, the inversion control method is combined with the sliding mode variable structure control method to devise an inversion sliding mode control algorithm. In order to further improve the control system’s robustness against external environmental interference, a robust control methodology is introduced for the design of the depth controller. Simulation results demonstrate that the designed controller effectively addresses the issues of model uncertainties and ocean current interference, thereby enhancing the UUV’s depth control accuracy.

Sensorless HSPMSM Control of an Improved SMC and EKF Based on Immune PSO

Here, for controlling a high-speed flywheel permanent magnet synchronous motor (HSPMSM), a position sensorless control method for estimation of motor rotor position and speed is proposed to address the problems faced by mechanical position sensors of high cost, large size, and poor interference immunity. The extended Kalman filter (EKF) has difficulty obtaining the optimal covariance matrix when performing state estimation. Therefore, the particle swarm algorithm (PSO) with an immune mechanism is used to optimize the covariance matrix of the EKF. However, the EKF algorithm makes the system less robust due to its delay effect. Based on the traditional sliding mode control rate, the exponential convergence law is improved, and the continuous function sat(s) is used instead of the symbolic function sgn(s). This improves the convergence law and proves the asymptotic stability of the designed sliding mode variable structure controller based on Lyapunov’s stability theorem. Then, the novel control law is applied to the sliding mode surface (SMS). An ordinary sliding mode controller (OSMC) using a linear sliding mode controller (LSMC), a global sliding mode controller (GSMC) using a global sliding mode surface (GSMS), and an integral sliding mode controller (ISMC) using an integral sliding mode surface (ISMS) are designed for improving control. Joint simulation in MATLAB and Simulink verifies that the optimized EKF based on the immune PSO can improve precision and accuracy for controlling the electronic rotor position and speed. Comparing the new sliding mode controller with a traditional PI controller reveals that the proposed system has stronger resistance to load disturbance and better robustness.

Research on improved sliding mode control of permanent magnet synchronous motor with disturbance compensation

In order to address the shortcomings of traditional sliding mode variable structure control in permanent magnet synchronous motor vector control, such as the state quantity’s inability to converge to 0 in limited time, too large chattering, too large load disturbance, poor dynamic performance, a non-singular fast terminal sliding mode control algorithm in speed loop is proposed. At the same time, a new approach rate is designed by comparing the advantages and disadvantages of different approach rates, which can restrain the natural chattering of sliding mode and improve the approach rate. On this basis, in order to increase response time, lessen chattering, and enhance the observer’s capacity for adaptation, a load torque observer is constructed, load disturbance is added to the speed loop as feedforward compensation, and a new approach rate is added to the observer. The simulation results manifest that the design successfully tracks load torque, enhances the system’s dynamic performance, and lessens the impact of sliding mode chattering.