Traditional Sliding Mode Control Research Articles

Speed Regulation and Optimization of Sensorless System of Permanent Magnet Synchronous Motor

Aiming at the problems of speed overshoot, slow convergence and poor anti-interference in the control of permanent-magnet synchronous motors (PMSMs) without a position sensor, a pulse vibration high-frequency signal injection method for a permanent-magnet synchronous motor with an improved sliding mode control was designed. Firstly, the improved approach rate function is combined with the improved non-singular fast terminal sliding mode surface to design the non-singular fast terminal sliding mode controller (NFTSMC), which is used in the speed loop to improve the speed convergence ability and reduce its overshoot. Secondly, in order to eliminate the influence of the band-pass filter on the system bandwidth in the traditional high-frequency injection method, a pulse vibration high-frequency signal injection method that injects high-frequency voltage signals and synchronous current signals into the d^ axis of the estimated two-phase rotation coordinate system d^q^ and the αβ axis of the two-phase stationary coordinate system αβ was designed to estimate the motor position and speed to achieve sensorless control. Finally, the above control strategy was compared with the speed loop PI and the traditional sliding mode controller (SMC) of the speed loop, respectively. The simulation and experimental results show that whether it is a no-load variable speed or fixed speed loading, the above control strategy can effectively reduce the speed overshoot, accelerate the speed convergence and improve the load capacity of the system.

Design of ABS fuzzy sliding mode control system based on pavement recognition

A fuzzy sliding mode variable structure control method based on road surface recognition was proposed to solve the problem that the Anti-lock Braking System (ABS) effect of current ABS algorithm was not ideal on complex road surface. In the road recognition module, real-time estimation of five typical road surfaces using fuzzy logic control. Dynamic calculation of optimal slip ratio for different road surfaces based on identified road conditions. Design of ABS sliding mode variable structure controller with optimal slip ratio and actual slip ratio as input. Aiming at the chattering problem of sliding mode control, a fuzzy controller is designed to reduce chattering. An 8-DOF dynamic simulation model of a four-wheel hub motor is established. The effectiveness of the controller is verified by braking simulation experiments on medium and low adhesion road. By comparing the simulation test with the traditional sliding mode controller under the condition of high adhesion road, the suppression effect of the system chattering is verified, and its excellent control performance is proved.

Speed Synchronization Control of Dual-SRM Drive With ISMC-Based Cross-Coupling Control Strategy

To improve the speed synchronization performance of dual switched reluctance motor (SRM) drive with traditional sliding mode control (TSMC), the improved sliding mode control (ISMC) based cross-coupling control strategy is proposed. Firstly, the overall control structure of the dual-SRM drive is represented. Secondly, the state variable is introduced to reduce the torque fluctuation and adjustment time of the dynamic process of each SRM drive in the system based on the traditional sliding surface and sliding mode reaching law. The adaptive law is introduced into the sliding mode controller to avoid the load torque observation. Thirdly, the ISMC-based cross-coupling control method for the speed synchronization of the dual-SRM drive is designed. The novel sliding surface is proposed considering the speed synchronization deviation. The novel sliding mode reaching law is represented by introducing the state variables. Then the ISMC-based cross-coupling control method is realized for speed synchronization. The stability is proved by Lyapunov function. Simulations and experiments are implemented to verify the effectiveness of the proposed method.

Fixed-time disturbance observer based robust tracking control of wheeled mobile robot with multiple disturbances

In this article, the problem of robust tracking control for wheeled mobile robot (WMR) with skidding, slipping, and parameter uncertainties is addressed. Through designing double sliding mode variables, a fixed time disturbance observer is developed to estimate the multiple disturbances within a fixed time, and the convergence time is regardless of the initial estimation error of the system. Based on the fixed-time disturbance observer (FTDOB) and the novel power reaching law sliding mode technique, a robust tracking controller is synthesized. The proposed control method eliminates the chattering problem existing in the traditional sliding mode control, and can guarantee the high-precision tracking control performance even in the presence of skidding, slipping and parameter uncertainties. The closed-loop system stability analysis is verified by the Lyapunov stability theory. Meanwhile, simulation comparative results are carried out to illustrate the effectiveness of the proposed control method.

Research on high water-based digital valve with dual-spool and control strategy

The straightness control of the working face is the key technology to realize intelligent production of coal mines. However, the discontinuity of on–off hydraulic components of the existing underground working face cannot meet the needs of intelligent straightness control. A new type of dual-spool high water-based digital valve with a motor ball screw as the driving element is proposed as a solution to this problem. In this paper, the force of the valve is firstly analyzed, and it is found that the force of the movement of the valve core can be equivalent to the disturbance of the motor. The control of the valve core is essentially displacement control. In addition, a mathematical model of the valve is established, and sliding mode control with a high-gain observer is proposed to overcome time-varying characteristics of the load. Theoretical analysis indicates that the proposed controller ensures asymptotic stability with existing uncertain disturbances. Moreover, a system based on MATLAB/Simulink simulation model is developed to further verify the performance of the proposed algorithm. Compared with traditional sliding mode control and proportional integral derivative, the proposed algorithm can still improve the tracking accuracy and robustness along with 0.05 mm error under strong time-varying interference. The valve reaches the required flow in around 0.2 s, which is sufficient for the majority of work surface application situations. The research proposes a novel design concept and control approach for straightening coal mine scraper conveyors.

An improved global fast terminal high-order sliding mode control strategy based on novel reaching law for improving PMLSM dynamic performance

Due to its better power density and efficiency, permanent magnet linear synchronous motor (PMLSM) is ideal for generating electricity with wave power device (WPD). Nevertheless, when the PMLSM for the WPD control system is impacted by changes in motor characteristics and interference from the outside environment, it typically is unable to deliver high-quality dynamic performance on schedule. Although sliding mode control (SMC) has been introduced to improve the robustness of the system greatly in recent decades, traditional methods still have problems such as slow dynamic response, poor anti-disturbance performance, large chattering amplitude, and phase delay. To solve the above defects in SMC, an improved global fast terminal high-order SMC strategy based on novel reaching law for improving PMLSM dynamic performance is proposed in this paper, as well as the sliding mode surface and control law of the speed controller is designed based on this control strategy. The proposed strategy would not only shorten the dynamic response time but also weaken the chattering magnitude in the sliding mode stage, improving the dynamic performance of both speed and current. The simulation results demonstrate that in comparison to the traditional PI and SMC control methods, the improved strategy proposed in this paper can further enhance the control performance of the linear motor, demonstrating the method’s enormous potential in the double closed-loop vector control system of PMLSM for WPD.

An extended state observer-based sliding mode control method for hydraulic servo system of marine stabilized platforms

The marine stabilized platform is a critical apparatus to ensure the stability of offshore equipment and operations with respect to the inertial coordinate system. However, the hydraulic actuating system of the platform is challenging to control due to the severe offshore environment and hydraulic parameter perturbations. Therefore, to improve the stability and anti-disturbance performance of the hydraulic actuators on the marine stabilized platform, an extended state observer-based sliding mode control (ESO-SMC) method is proposed in the paper. We first analyze the kinematic model of the platform and the dynamic model of the hydraulic servo system. Then, ESO-SMC is designed, and its stability is verified. The novel Marine Predator Algorithm (MPA) is used to optimize the parameters in ESO-SMC design. Simulation is performed in MATLAB/Simulink using an engineering ship model and a stabilized platform model on the ship. Compared with the traditional Sliding Mode Control (SMC), Velocity Feedforward PID (VFPID), and PID methods, ESO-SMC performs best in resisting external wave load disturbances and flow gain parameter perturbations. In conclusion, ESO-SMC is a reliable control approach for enhancing the anti-interference performance of the hydraulic servo system on marine stabilized platforms in the simulation.

Research on Amphibious Multi-Rotor UAV Out-of-Water Control Based on ADRC

This paper presents a study on controlling the out-of-water motion of amphibious multi-rotor UAVs using a cascade control method based on the Active Disturbance Rejection Control (ADRC) algorithm. The aim is to overcome the challenges of time-varying model parameters and complex external disturbances. The research involves developing an underwater dynamic model and analyzing hydrodynamic forces to calculate theoretical inertial hydrodynamic forces and simulate viscous hydrodynamic forces. This establishes the relationship between viscous hydrodynamic forces and exit velocity. A complete air dynamic model is then established, selecting model parameters based on the center of mass position of the amphibious vehicle to enable switching from water to air. To address control algorithm instability caused by changes in model parameters, position and attitude controllers are built using the ADRC algorithm. The control effects are compared with traditional PID and sliding mode controllers (SMC) to verify the effectiveness and superiority of the proposed cascade ADRC control strategy. Experimental results show that our controller has stronger anti-interference than traditional PID and SMC controllers and can overcome control instability caused by changes in model parameters. Our research highlights the importance of using ADRC-based controllers for amphibious multi-rotor UAVs to achieve robust and stable control.

Production Change Optimization Model of Nonlinear Supply Chain System under Emergencies

Aiming at the problem that the upstream manufacturer cannot accurately formulate the production plan after the link of the nonlinear supply chain system changes under emergencies, an optimization model of production change in a nonlinear supply chain system under emergencies is designed. Firstly, based on the structural characteristics of the supply chain system and the logical relationship between production, sales, and storage parameters, a three-level single-chain nonlinear supply chain dynamic system model containing producers, sellers, and retailers was established based on the introduction of nonlinear parameters. Secondly, the radial basis function (RBF) neural network and improved fast variable power convergence law were introduced to improve the traditional sliding mode control, and the improved adaptive sliding mode control is proposed so that it can have a good control effect on the unknown nonlinear supply chain system. Finally, based on the numerical assumptions, the constructed optimization model was parameterized and simulated for comparison experiments. The simulation results show that the optimized model can reduce the adjustment time by 37.50% and inventory fluctuation by 42.97%, respectively, compared with the traditional sliding mode control, while helping the supply chain system to return the smooth operation after the change within 5 days.

Path tracking of unmanned agricultural tractors based on a novel adaptive second-order sliding mode control

Unmanned tractors are widely adopted in agricultural operations as autonomous driving technology progresses. The current path tracking control methods are limited by the unstructured farmland, the accuracy and anti-interference ability needed to be improved. This paper presents a novel adaptive second-order sliding mode (ASOSM) control method to tackle the aforementioned problems in practical implementation. First, we introduce a preview lateral offset model based on the preview kinematic and tractor dynamic model, which helps solve the under-actuated problem in path tracking. Then, the ASOSM controller is designed using the revamped adding a power integrator (API) and adaptive mechanism, which ensures that the sliding variable is converged to zero within the finite time. Meanwhile, the chattering problem in traditional sliding mode control is relieved. Finally, a high-fidelity and full-car model is established under Simulink/Carsim environment, and comparative simulations conrm the superiority of the designed control method.

Experimental Design of Fast Terminal Sliding Mode Control for Valve Regulation under Water Load Uncertainty for Precision Irrigation

The application of control systems in precision irrigation is critical to ensure the accurate distribution of water in crops under various uncertainties. Shifts in the loading of the water supply on the control valve can be a significant uncertainty. Changes in weather and the uncertainty of the water level in the reservoir are also challenging issues. Sliding Mode Control (SMC) is a robust control technique that is simple to apply to deal with uncertainty, while Fast Terminal Sliding Mode Control (FTSMC) has the benefit of the rapid convergence. The DC electric motor, which is a common component of electric control valves, can be employed in designing control techniques for precision irrigation applications. This study aims to design a proposed experimental-based method, namely FTSMC for valve regulation under water load uncertainty for precision irrigation application. Modification of the signum function should be used to eliminate the chattering effect in real experiments.The results of experiments showed that the proposed method was superior to the conventional Proportional Integral Derivative (PID) and traditional SMC techniques in terms of overshoot, convergence rate and error. Because of those reasons, the FTSMC approach should be implemented on control valves against load uncertainty in precision irrigation applications.

Research On Adaptive Sliding Mode Control of PMSM Based On Novel Reaching Law

Based on the jitter and slow convergence speed caused by the conventional approach law SMC, a new exponential approach rate is proposed to optimize dynamic characteristics of the PMSM control system. The approach law is based on the conventional exponential adience law, and the variable of state the system are added. It can ceaseless adapt to the changes of the controlled system, ensure the high tracking function of the system and reduce the jitter caused by the control input. Meanwhile, based on the new exponential approach law, an self-adaption SMC is designed to estimate the uncertain parameters of the control process, and the stability of the make better approach law and control algorithm is analyzed by the function. Finally, The designed controller is compared with traditional sliding mode control and PI control through simulation experiments. The results show that the new exponential approach law can effectively suppress chattering and improve the dynamic characteristics of the system.

Adaptive sliding mode based fault tolerant control of wheeled mobile robots

ABSTRACT In this paper, we propose an adaptive sliding mode-based fault tolerant control for mobile robots. While a mobile robot is tracking a given trajectory, several fault cases may occur, such as sensor model and controller faults, changes in the dynamic equation due to robot body shape or weight changes, and loss of actuator effectiveness. Disturbance signals are caused by the actuator faults and, for various reasons, can be considered the primary issue for the robots. In real-time applications, the Sliding Mode Controller (SMC) is insufficient if the robot parameters are unknown, the robot model is non-linear, and the overall system is subject to disturbances. An adaptive law is used to support the SMC to maintain the sliding surface and solve the problems of unknown system parameters, actuator faults, and disturbances. Besides SMC, the kinematic controller is also used, and its gain values are optimized using a neural network and a kinematic controller. The stability of the overall system is proven by using the Lyapunov theory. Besides actuator faults, the system is disturbed by defining a disturbance signal, which is added to the control signals. To show the effectiveness of the proposed controller, it is compared with traditional SMC and PID.

Fractional Order Sliding Mode Controller Based on Supervised Machine Learning Techniques for Speed Control of PMSM

Tracking the speed and current in permanent magnet synchronous motors (PMSMs) for industrial applications is challenging due to various external and internal disturbances such as parameter variations, unmodelled dynamics, and external load disturbances. Inaccurate tracking of speed and current results in severe system deterioration and overheating. Therefore, the design of the controller for a PMSM is essential to ensure the system can operate efficiently under conditions of parametric uncertainties and significant variations. The present work proposes a PMSM speed controller using machine learning (ML) techniques for quick response and insensitivity to parameter changes and disturbances. The proposed ML controller is designed by learning fractional-order sliding mode control (FOSMC) controller behavior. The primary purpose of using ML in FOSMC is to avoid the self-tuning of the parameters and ensure the speed reaches the reference value in finite time with faster convergence and better tracking precision. Furthermore, the ML model does not require the mathematical model of the speed controller. In this work, several ML models are empirically evaluated on their estimation accuracy for speed tracking, namely ordinary least squares, passive-aggressive regression, random forest, and support vector machine. Finally, the proposed controller is implemented on a real-time hardware-in-the-loop (HIL) simulation platform from PLECS Inc. Comparative simulation and experimental results are presented and discussed. It is shown from the comparative study that the proposed FOSMC based on ML outperformed the traditional sliding mode control (SMC), which is more commonly used in industry in terms of tracking speed and accuracy.

Vibration suppression using a mechatronic PDD-ISD-combined vehicle suspension system

In this paper, the performance of a novel power-driven-damper (PDD) and inerter-spring-damper (ISD) combined suspension system for a quarter-car model is investigated to address the vibration suppression problem at both low and high frequencies for vehicles. Using a structure-based approach, we propose and optimize eight different passive mechanical networks and compare the vibration suppression abilities of four candidates across a wide frequency spectrum. The impact of changes in the inertance and the deputy spring stiffness is also analyzed. To accurately track the vertical dynamics of the optimal PDD-ISD suspension and account for the limited control force, a fractional-order derivative sliding mode controller (FD-SMC) is designed. The performance of FD-SMC is compared against that of the traditional sliding mode controller (TSMC) under a compound road, and the results show that, FD-SMC exhibits a superior vibration suppression and control efficiency.

Robust relative orbit synchronization for spacecraft cluster: A distributed learning sliding mode control approach

This paper investigates the issue of robust relative orbit synchronization control for spacecraft cluster subjects to space perturbation. First, the relative orbit dynamics of the leader-follower spacecraft cluster is established. Combined with P-type learning algorithm and sliding mode control (SMC) strategy, a novel distributed learning SMC (LSMC) strategy with the consensus algorithm is explored such that all the follower spacecrafts converge to the target relative position and their velocities tend to the leader spacecraft. The distributed P-type learning algorithm is used to update and compensate space perturbation for all the follower spacecrafts. The proposed LSMC approach has the potential to achieve higher control accuracy than the traditional SMC one while it has the lower computation burden than the distributed adaptive SMC one. The stability analysis of the proposed distributed LSMC strategy is provided in detail. Finally, a numerical example is simulated to illustrate the effectiveness and superiority of the proposed distributed LSMC-based relative orbit synchronization control for spacecraft cluster.

Double power sliding mode control of permanent magnet synchronous motor based on high-order sliding mode method

In view of the shortcomings of traditional sliding mode control of permanent magnet synchronous motor (PMSM), such as slow convergence, serious speed overshoot and outstanding chattering, an improved dual power approach law is proposed. Combined with the equivalent control, a high-order sliding mode rotor is designed by using the second-order nonsingular terminal sliding surface, which greatly improves the dynamic and static performance of the motor and effectively suppresses chattering. The simulation results show that the convergence speed of the improved dual-power reaching law is faster and the anti-disturbance ability of the system is significantly improved.

Robust sliding mode controller for frequency regulation in a microgrid

The distribution of power at minimum frequency deviation is a primary objective in an isolated microgrid due to variation in inertia and uncertainties in distributed generations. Thus, in this study, a centralized robust sliding mode controller is proposed to achieve minimum frequency deviation with optimal power distribution among distributed generations in an isolated microgrid. The microgrid model is developed for small signal analysis purpose using the electric vehicle charging model dynamics, the wind energy model dynamics and the run-of-river hydro model dynamics. The proposed controller parameters are optimized using linear matrix inequality (LMI), and its asymptotic convergence law is verified via Lyapunov’s stability theorem. The effective reduction in frequency deviations, time characteristics and chattering in control signals is achieved using the proposed controller. Furthermore, robustness nature of the proposed controller conforms against random plant outage sequence, random load and wind uncertainty. In addition, the performance of proposed controller is compared with existing state proportional–integral–derivative (PID) controller and traditional sliding mode control (SMC) even in presence of random plant outage sequence, load and wind speed uncertainties. The proposed controller is capable of regulating power share scenario intelligently according to load disturbance, plant uncertainties and also reducing time characteristics, oscillations and chattering phenomena in control effort within a short duration. As a result, the responses of proposed controller are compared with existing controllers in terms of improved closed-loop dynamics and its effectiveness. The performance of the proposed controller is demonstrated using MATLAB© simulations platform.

Design of single neuron super-twisting sliding mode controller for permanent magnet synchronous servo motor

Aiming at the control system of permanent magnet synchronous servo motor which is easily affected by external disturbance and parameter uncertainty, a single neuron sliding mode combining single neuron adaptive algorithm and super-twisting sliding mode (STSM) control is proposed. The STSM control is used to overcome the chattering problem in the traditional sliding mode control, and the proportional control and the STSM control are combined to enhance the robustness of the control system. In order to improve the dynamic performance of the system and enhance the anti-disturbance ability of the system, the single neuron adaptive control adopted can adjust the relevant parameters of the designed sliding mode controller online. The simulation and experimental results show that the designed improved sliding mode controller can effectively suppress the chattering of the control system, realize the fast following and no overshoot of the control system, and enhance the robustness of the system.

Adaptive Neural Network Extended State Observer-Based Finite-Time Convergent Sliding Mode Control for a Quad Tiltrotor UAV

The internal and external disturbance of the quad tiltrotor UAV stem from its rotor tilting motion and wind disturbance, which affect the control stability of the quad tiltrotor UAV in full flight. This paper proposes a control law design method based on the Adaptive Neural Network Extended State Observer-based Finite-Time Convergent Sliding Mode Control (ANNESO-FTCSMC). The adaptive neural network obtains the unknown total disturbance term that needs to be compensated in the finite-time convergent sliding mode control. An extended state observer is used to estimate the state variables of the controlled plant. The stability of the ANNESO-FTCSMC controller is proved with the Lyapunov stability theory. The unknown total disturbance as the expanded state variable of the state observer has the advantage of high adaptability, and the ANNESO-FTCSMC has a strong ability to compensate for the internal and external disturbances of the system. Compared with traditional sliding mode control, ANNESO-FTCSMC does not contain switching terms, so ANNESO-FTCSMC is chattering-free and converges faster. Based on this method, the flight control system of the quad tiltrotor UAV is designed and verified by hardware-in-loop simulation. The hardware-in-loop simulation results of attitude control in different flight modes and trajectory tracking control in full flight show that the ANNESO-FTCSMC controller is suitable for the flight control of quad tiltrotor UAV. Compared with the PID controller and ADRC controller, ANNESO-FTCSMC controller has more stable flight state of quad tiltrotor UAV under different flight modes and the same total disturbance. The transition process of ANNESO-FTCSMC controller from helicopter mode to airplane mode is also smoother and will not have large fluctuations. Therefore, ANNESO-FTCSMC controller has strong anti-disturbance and robustness.