Sliding Mode Control Technology Research Articles

Research on the control strategy of gravity energy storage system based on sliding mode control technology

Abstract As a newly proposed physical energy storage method, gravity energy storage (GES) is currently in its infancy at home and abroad, and the control technology of slope GES is not yet mature. This article focuses on the control strategy of the slope GES system, designs the machine/grid side control block diagrams with the sliding mode control technology, and compares the differences between sliding mode control and traditional PI control through simulation analysis. It is concluded that the sliding mode control strategy has a faster adjustment speed, smaller fluctuation range, and better overall control performance.

Voronoi-based adaptive area optimal coverage control for multiple manipulator systems with uncertain kinematics and dynamics

This paper studies an adaptive area optimal coverage control method for multi-manipulator systems under the presence of both uncertain kinematics and dynamics. Initially, an objective cost function associating the voronoi tessellation is utilized to transform the optimal coverage control into the tracking control problem. Consequently, an adaptive area optimal coverage control strategy is designed by using the adaptive dynamic and kinematic programming. In this control strategy, the sliding mode control technology for each robot manipulator system is created to pursue control optimality and prescribed coverage performance simultaneously. The adaptive control algorithm using the parameter linearization properties is further deployed to directly cope with the influence caused by the parameter uncertainties of manipulator dynamics and kinematics. Theoretical analysis is given to guarantee the stability and convergence of the proposed optimal area converge controller, subject to optimal cost. Illustrative example is provided to validate the performance of the proposed framework.

Sliding mode controller with neural network compensation for tank

The control effectiveness of the all-electric tank stabilizers directly affects the firing accuracy of the tank gun. In order to improve the firing accuracy of the moving tank, this paper proposes a sliding mode control (SMC) strategy using neural network feed-forward compensation for the tank bidirectional stabilizers. SMC technology can quickly and effectively deal with uncertainties, unmodeled terms, and external disturbances in complex tank systems. Neural networks possess the advantage of approximating arbitrary continuous functions in finite time, realizing the estimation of SMC control errors with feed-forward compensation. The Lyapunov stability analysis proves that the designed controller can achieve asymptotic stabilization in finite time. Finally, both co-simulation and physical experiments are conducted. The results show that the proposed control strategy possesses better tracking speed and tracking accuracy compared to the conventional controller and exhibits strong robustness.

Nonlinear Disturbance Observer-Based Fault-Tolerant Sliding-Mode Control for 2-D Plane Vehicular Platoon With UTVFD and ANAS.

This article investigates a nonlinear disturbance observer (NDO)-based fault-tolerant sliding-mode control (SMC) for 2-D plane vehicular platoon systems subjected to actuator faults with unknown time-varying fault direction (UTVFD), asymmetric nonlinear actuator saturation (ANAS), nonlinear unmodeled dynamics, and unknown external disturbance. The Nussbaum-type function approach is adopted to solve the problem of actuator faults with UTVFD. The designed NDO not only can estimate the lumped disturbance accurately but also can reduce the control peaking and chattering phenomena caused by the Nussbaum-type function. Then, an adaptive saturation compensator is designed to compensate for the influence of actuator saturation on the system. In addition, by combining SMC technology with the prescribed tracking performance (PTP) approach, a distributed fault-tolerant control scheme is developed to not only ensure collision avoidance and communication connectivity but also realize a variety of driving scenarios, such as multilane vehicle merging and vehicular platoon lane changing. Finally, simulation results are presented to show the proposed scheme's effectiveness and advantages.

Sliding-mode surface-based approximate optimal control for nonlinear multiplayer Stackelberg-Nash games via adaptive dynamic programming

This paper studies the sliding-mode surface (SMS)-based approximate optimal control issue for a class of nonlinear multiplayer Stackelberg-Nash games (MSNGs). First, considering different roles of the players in MSNGs, a hierarchical decision-making process is expressed as designing different cost functions for the leader and the followers. Therein, the leader makes its decision preferentially with consideration of all followers, while each follower responds optimally to leader’s strategy simultaneously via Nash games. Then, based on the sliding mode control technology, a novel robust control policy is proposed to solve the coupling Hamilton–Jacobi equations of nonlinear MSNGs. Subsequently, SMS-based critic network is utilized to approximate optimal control inputs for all players. Based on the Lyapunov stability theory, it is strictly proven that all signals of the closed-loop nonlinear systems are uniformly ultimately bounded. Finally, the effectiveness of the proposed method is demonstrated via a simulation example.

Continuous and Periodic Event-Triggered Sliding-Mode Control for Path Following of Underactuated Surface Vehicles.

This article develops continuous and periodic event-triggered sliding-mode control (SMC) algorithms for path following of underactuated surface vehicles (USVs). Based on the SMC technology, a continuous path-following control law is designed. The upper bounds of quasi-sliding modes for path following of USVs are established for the first time. Subsequently, both continuous and periodic event-triggered mechanisms are considered and added into the proposed continuous SMC scheme. It is demonstrated that with appropriate selecting of control parameters, the use of hyperbolic tangent functions does not affect the boundary layer of quasi-sliding mode caused by event-triggered mechanisms. The proposed continuous and periodic event-triggered SMC strategies can make the sliding variables reach the quasi-sliding modes and stay in there. Moreover, energy consumption can be reduced. Stability analysis shows that the USV can follow a reference path by using the designed method. The simulation results show the effectiveness of the proposed control methods.

Hierarchical Sliding-Mode Surface-Based Adaptive Critic Tracking Control for Nonlinear Multiplayer Zero-Sum Games via Generalized Fuzzy Hyperbolic Models

This paper investigates the hierarchical sliding-mode surface (HSMS)-based adaptive critic tracking control problem for nonlinear multiplayer zero-sum games (ZSGs). First, a generalized fuzzy hyperbolic models-based identifier is employed to approximate the unknown nonlinear functions. According to the derived data-driven model, a static control policy is proposed to transform the considered optimal tracking control problem into an optimal regulation control problem of an induced error system. Subsequently, based on sliding mode control technology and the concept of hierarchical design, a novel optimal feedback control policy is developed to regulate the tracking error by minimizing a performance index function related to the HSMS. The solution to the Hamilton-Jacobi-Isaacs equation of nonlinear multiplayer ZSGs is obtained via the HSMS-based critic neural network. Furthermore, the historical stored data is utilized to conquer the difficulty associated with the persistence of excitation conditions. Based on Lyapunov stability theory, it is strictly proven that the tracking error and the critic neural network weight are uniformly ultimately bounded. Finally, two examples are presented to demonstrate the effectiveness of the proposed control scheme.

Super-Twisting Sliding Mode Active Disturbance Rejection Control of Permanent Magnet Synchronous Motor Based on Vector Control

The vector control speed regulation system of the permanent magnet synchronous motor founded on traditional control has some weaknesses of poor rapidity and robustness, and it is hard to satisfy the current control requirements. A new control method combining active disturbance rejection control technology with improved super-twisting sliding mode control technology (STSM-ADRC) comes up. In active disturbance rejection control, the tracking differentiator is simplified; the extended state observer is designed to observe all internal and exterior disturbances of the system; the improved super-twisting sliding mode control law is going to take the place of the error feedback control law; and the simulation is carried out. Compared with the existing control algorithms, this new control method can overcome the influence of load disturbances and track the given speed effectively. And the responsiveness and robustness of the system are strengthened.

Nonsingular Fast Terminal Sliding Mode Neural Network Decentralized Control of a Quadrotor Unmanned Aerial Vehicle

A nonsingular terminal sliding mode decentralized controller that can ensure the tracking errors of the trajectories and attitude rapid convergence in finite time is proposed for an insufficient driven and strongly coupled nonlinear four-rotor unmanned aerial vehicle (UAV). The total lift of the UAV system is decomposed into three virtual drive separation forces corresponding to the three positions. The insufficient drive UAV system is transformed into a virtual full-drive model for research. The three position states and the three attitude states of UAV are placed correspondingly to the six subsystems by variable substitution. The model uncertainty and unknown disturbance term for each subsystem serves as total coupling terms among the subsystems. The upper bounds of the total coupling terms are considered as unknown ordinary higher order polynomials varying with the six states of the system under the action of time change. With the help of Cauchy inequality, the estimates of the upper bounds are obtained from the approximation performance of the RBF neural network. Finally, the decentralized controller is designed for each attitude subsystem and the virtual decentralized controller for each position subsystem. It is also mapped to the tracking total lift controller by using the virtual decentralized position controller. The controller design process uses the nonsingular terminal sliding mode control technology to ensure that the quadrotor attitude and position variables can quickly converge to the desired value in a short time. Simulation experiments verify that the proposed control method is effective and feasible.

A robust voltage control of dual active full bridge converter based on RBF neural network sliding mode control with reduced order modeling approach

This paper presents a control method of dual active full bridge (DAB) DC/DC converter based on neural network Sliding mode control under the reduced order modeling method, which is used to enhance the output voltage regulation and improve the system robustness. Sliding mode control (SMC) is famous for its robustness and improving the dynamic performance of nonlinear systems. However, it includes drawbacks such as complex modeling, chattering, and decreased tracking performance. Therefore, through the method of reduced order modeling, the Radial Basis Function neural network algorithm is selected to modify and design the traditional sliding mode variable structure controller, completing the design of neural network approximation terms and adaptive laws. The proposed reduced order modeling and RBF(Radial Basis Function Neural Network)-SMC scheme simplifies the dual active full bridge modeling process, completes the parameter approximation of the sliding mode controller, and eliminates the chattering problem. Firstly, through simulation and comparative analysis of commonly used modeling methods for dual active full bridge, a reduced order modeling method was adopted to simplify the design process. Then, by ingeniously designing the sliding mode surface and Radial Basis Function control law, and using neural network to modify the Sliding mode control technology, the chattering problem, load disturbance and voltage fluctuation influence of the sliding mode controller are improved. The stability of the control method is proved by Lyapunov stability theory. Finally, the proposed RBF-SMC method is compared with PI linear control and classical Sliding mode control methods through simulation and experiments to verify the effectiveness of the proposed control method.

Fuzzy approximation-based optimal consensus control for nonlinear multiagent systems via adaptive dynamic programming

This paper investigates the fuzzy approximation-based optimal consensus control problem for nonlinear multiagent systems with unknown perturbations. By constructing local error dynamics, the considered optimal consensus problem is reformulated as finding Nash-equilibrium solutions to zero-sum games. Then, by using sliding mode control technology and the concept of hierarchical design, a series of control signals are sequentially designed to regulate the consensus error and minimize the local value function. In addition, an identifier-critic architecture is developed by using generalized fuzzy hyperbolic models, where the identifier is employed to relax the requirement for complete system dynamics information, and the hierarchical sliding mode surface-based critic network is applied to approximate optimal control inputs. Finally, A simulation example is presented to illustrate the validity of the proposed approach.

Improved Torque Ripple of Switched Reluctance Motors using Sliding Mode Control for Electric Vehicles

This study describes the direct torque control-DTC approach, based on the Sliding Mode Control (SMC) technology with chattering reduction, for reducing the torque ripple of the Switched Reluctance Motor (SRM). The SRM torque control loop has been given the SMC treatment to account for the low-frequency fluctuations in the torque output. To maintain a consistent motor speed, the sliding mode controller modifies the value of the reference current. The findings demonstrate that the constant sliding mode controller is superior to PI controllers at lowering the motor's torque ripple, compensating for its nonlinear torque characteristics, and rendering the drive insensitive to parameter changes. MATLAB/SIMULINK simulation has been used to show how well this SMC performs. The performance of the proposed SMC method has been demonstrated by simulation in MATLAB/SIMULINK with a three-phase 8/6 pole, and a 2kW SRM.

Networked synchronization transmission of laser pattern signal based on integral augmented sliding mode control

We propose a new integral augmented sliding mode control technology to realize the networked synchronization transmission of laser pattern signal. In the technical scheme, the chattering phenomenon is suppressed by designing the sliding mode surface with integral augmented. And there are no restrictions on the technical parameters of the controlled network, such as the network topology, the node dynamics, the number of nodes, and so on. Therefore, the technology has good universality and practicability.

Frequency Regulation of Power Systems With a Wind Farm by Sliding-Mode-Based Design

Load frequency regulation is an essential auxiliary service used in dealing with the challenge of frequency stability in power systems that utilize an increasing proportion of wind power. We investigate a load frequency control method for multiarea interconnected power systems integrated with wind farms, aimed to eliminate the frequency deviation in each area and the tie-line power deviation between different areas. The method explores the derivative and integral terminal sliding mode control technology to solve the problem of load frequency regulation. Such technology employs the concept of relative degrees. However, the subsystems of wind-integrated interconnected power systems have different relative degrees, complicating the control design. This study develops the derivative and integral terminal sliding-mode-based controllers for these subsystems, realizing the load frequency regulation. Meanwhile, closed-loop stability is guaranteed with the theory of Lyapunov stability. Moreover, both a thermal power system and a wind power system are applied to provide frequency support in this study. Considering both constant and variable external disturbances, several numerical simulations were carried out in a two-area thermal power system with a wind farm. The results demonstrate the validity and feasibility of the developed method.

Rotor position angle control of permanent magnet synchronous motor based on sliding mode extended state observer

ABSTRACT To achieve fast, accurate control of the position angle of the rotor of permanent magnet synchronous motor (PMSM), traditional auto disturbance rejection control often has many adjustable parameters and complex tuning problems. Sliding mode control technology is introduced into the extended state observer (ESO) part of the auto disturbance rejection controller, and a new sliding mode approach law is designed based on several typical sliding mode approaches, which simplifies parameter tuning while retaining the original anti-interference performance of auto disturbance. In addition, the nonlinear state error feedback control law in active disturbance rejection control is enhanced to improve the component order PID control law, which can improve the response speed and robustness of the system, and prove the stability of the controller. Finally, the simulation of the PMSM rotor position control system based on the sliding mode ESO is carried out, and the results verify the validity of the method.

Stacked recurrent neural network based high precision pointing coupled control of the spacecraft and telescopes

In some space missions especially in the field of space gravitational wave detection, the telescope needs to point to a certain target through attitude movement and pointing control. In several mainstream gravitational wave detection missions, the detector usually consists of a cluster of three identical satellites, flying in a quasi-equilateral triangular formation with a big edge length, so every satellite needs two telescopes to point each other and constitute three giant Michelson-Type interferometers. Therefore, a satellite platform system with two telescopes is researched in this paper. This research helps to characterize the attitude motion of a telescope for space astronomical observation or space gravitational wave detection, provides new method on the telescope’s high-precision pointing control. For this purpose, we derive a satellite-telescope coupling attitude model, design the sliding mode controller for satellite and the stacked recurrent neural network adaptive controller for telescope. In the stacked recurrent neural network adaptive controller design, a sliding mode control technology is adopted. In addition, we propose a combinatorial optimization method for network weights in the stacked recurrent neural network training process, that is, the output layer is corrected by the adaptive law, and the correction of other layers adopt the error backpropagation method. Finally, a numerical simulation method verifies the effectiveness of the controller design.

Observer-based event-triggered sliding mode control of the discrete-time singular networked systems

This article is concerned with the [Formula: see text] observer-based sliding mode control via event-triggered strategy for the discrete-time singular networked systems. To improve network communication efficiency, an event-triggered strategy is introduced. Under the premise of considering the design convenience of the sliding mode surface for discrete-time singular networked systems, the observer is constructed to estimate the states of the system. From the event-triggered strategy–based observer and the sliding mode control technology, the augmented closed-loop discrete-time singular networked system is obtained. Then, new sufficient admissible criteria of discrete-time singular networked systems are derived, satisfying a given [Formula: see text] performance level. The synchronous design method of the event-triggered strategy observer gain and sliding mode control one is provided as solvable linear matrix inequalities. The sliding mode control law is designed to obtain better sliding mode accessibility and less chattering. Finally, two examples are provided to verify the effectiveness of the proposed method.

Adaptive robust finite-time control for active suspension systems via disturbance observation

To improve the ride comfort of vehicles, active suspension control strategy has received widespread attention. Although based on the finite-time and sliding mode control (SMC) technology design scheme, the convergence problem has been solved, the controller chattering and the poor control effect in the face of random interference will definitely limit its application in practice. To address such limitation, considering the variety of driving conditions, based on finite-time and SMC technology, an Adaptive Finite-time High-order SMC Active Suspension control Systems via disturbance observation (AFHASS) is proposed. Firstly, to improve the ride comfort of vehicle, a quarter dynamic model is established for vehicle active suspension; Then, given the advantages of finite-time and SMC technology, an AFHASS method is designed, and based on the Lyapunov analysis function constructed, the stability of the presented AFHASS control strategy has been proved; Finally, the effectiveness of the proposed AFHASS algorithm is validated by performing simulation, and compared with the different methods. Taking the finite-time control algorithm as a benchmark, under the C grade road roughness, the root mean square of vertical displacement has been improved by 29% and the energy consumption has been improved by 8%. The results are presented and discussed to illustrate the advantage and effectiveness of the proposed AFHASS algorithm in terms of energy consumption, vertical performance and controller chattering.

Control Algorithm for Trajectory Tracking of an Underactuated USV under Multiple Constraints

A trajectory tracking control method based on the cascade of optimal guidance and adaptive control laws was proposed for trajectory tracking of an unmanned surface vehicle under multiple motion constraints including an ocean current disturbance environment. Considering the velocity and acceleration constraints, angular velocity, and angular acceleration constraints in guidance law design, motion planning was conducted with three degrees of freedom using a motion model and predictive control, while optimal guidance law was designed through a rolling optimization strategy to stabilize the position error under multiple constraints. Moreover, the stability of the guidance law was proven. In control law design, an adaptive observer was introduced to estimate and compensate for ocean current disturbance, which affected the precision of control. The course and velocity control laws were designed with the adaptive sliding mode control technology to stabilize the course angle and longitudinal velocity errors; the stability of these control laws was further proven. Based on the system design, the stability of the entire closed-loop control system was proven with the cascade system and Lyapunov theory. Theoretical analysis and simulation experiments demonstrated the effectiveness and advancement of the proposed algorithm.

Predefined Time Synchronization Control for Uncertain Chaotic Systems.

In this study, the predefined time synchronization problem of a class of uncertain chaotic systems with unknown control gain function is considered. Based on the fuzzy logic system and varying-time terminal sliding mode control technology, the predefined time synchronization between the master system and the slave system can be realized by the proposed control method in this study. The simulation results confirm the theoretical analysis.