Sliding Mode Control Technology Research Articles

Design of adaptive parameter observer and laser network controller based on sliding mode control technology

In this work, we extend the sliding mode control technology so that it can be applied to laser network synchronization. Firstly, the adaptive parameter observer is designed and the uncertain parameters in the synchronization target are effectively identified based on the extended sliding mode control technology. Furthermore, we design the laser network controller in order to achieve complete synchronization between the laser network and the synchronization target. In our strategy, the designed network controller is very simple. The complex Lyapunov function is not required, and the only work required is to determine the range of adjusting parameters for achieving synchronization. Therefore, this technology is simple and practical.

The Dual-Core Sliding Mode Control Technology of Permanent Magnet Synchronous

Based on the structure and working principle of permanent magnet synchronous motor, a mathematical model suitable for engineering practice is established. For the system chattering problem caused by sliding mode control, a variable gain sliding mode controller is proposed to suppress chattering. Based on the MTLAB simulation platform, the permanent magnet synchronous motor servo control system model is designed and verified by simulation to verify the static and dynamic performance of the system. An experimental platform with DSP and FPGA as the core is built, and a new sliding mode control algorithm with DSP and FPGA as the core is verified. To verify the feasibility of the control strategy described in this article, the load experiment was carried out on the platform. Simulation and experimental results shown that the permanent magnet synchronous motor servo system based on dual-core sliding mode control technology has high response speed, high steady-state accuracy and robustness, and has good static and dynamic performance.

Trajectory tracking control of quadrotor under variable payloads with model-free controller and sliding mode control technology

Purpose This study aims to deal with the problem of trajectory tracking control for the quadrotor under external environmental disturbance and variable payloads. Design/methodology/approach In the field of unmanned aerial vehicle (UAV) control, external environmental disturbance and internal variable payloads as two major interference factors lead to control performance degradation or even instability, thus a trajectory tracking controller which innovatively combines sliding mode control technology and model-free control technique is proposed. The proposed controller is constructed with a learning rate-based sliding mode controller and an ultra-local model. Based on the proposed controller, the nonlinear system model of variable load quadrotor is locally estimated and the system’s uncertainties and disturbances can be compensated. Findings The simulation and actual test results demonstrate the satisfactory control performance and the robustness of the proposed controller compared with the PID and Backstepping controller under external environmental disturbance and variable payloads. Moreover, the proposed controller solves the trajectory tracking control problem not only when payloads change at the center of gravity but also when the position of load variation deviates from the center of gravity. Practical implications In both military and civilian domains, the quadrotor may encounter such situations that the payloads change, such as transporting goods, aerial refueling and so on. As a large internal interference factor, variable load tends to lead to unstable control. The research results provide theoretical guidance and technical support for trajectory tracking control of quadrotor under variable payloads. Originality/value The proposed controller combines learning rate-based sliding mode controller and model-free control technique to achieve a more efficient and accurate trajectory control of the quadrotor when considering system uncertainties and the load variation that happens in the unknown location.

Event-triggered adaptive neural network backstepping sliding mode control of fractional-order multi-agent systems with input delay

This article investigates the consensus problem for a class of fractional-order multi-agent systems with input delay. Each follower is modeled as a system with input delay and nonlinear dynamics. To avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously, dynamic surface control technology is introduced into an adaptive neural network backstepping controller. A dynamic event-triggered scheme without Zeno behavior is considered, which can reduce the utilization of communication resources. The sliding mode control technology is introduced to enhance robustness. The Pade delay approximation method is extended to fractional-order systems, which converts the original systems into systems without input delay. The stability of systems is ensured by the constructed Lyapunov functions. Examples and simulation results show that the consensus tracking errors can quickly converge and all the followers can synchronize to the leader by the proposed method.

Fixed-time neural network trajectory tracking control for underactuated surface vessels

This paper provides a robust fixed-time trajectory tracking controller for underactuated surface vessels (USVs) suffering from unmodeled dynamics and external disturbances. Initially, a novel model transformation is firstly applied for the possible application of sliding mode control technology. Then, fixed-time convergence for tracking errors can be guaranteed by stabilizing the transformed system. During the design process, a constructive sliding mode surface is structured with the application of hyperbolic tangent function, which could ensure the settling time of the designed system independent of initial states. To accommodate unknown system dynamics and perturbations, the Minimum-Learning-Parameter based neural network and adaptive updating laws are adopted. Theoretical analysis shows that tracking errors enjoy practical fixed-time stability under the proposed controller. Numerical simulation results illustrate the effectiveness and superiority of the proposed control scheme.

Observer-based adaptive neural network backstepping sliding mode control for switched fractional order uncertain nonlinear systems with unmeasured states

This paper proposes an observer-based adaptive neural network backstepping sliding mode controller to ensure the stability of switched fractional order strict-feedback nonlinear systems in the presence of arbitrary switchings and unmeasured states. To avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously, the fractional order dynamic surface control (DSC) technology is introduced into the controller. An observer is used for states estimation of the fractional order systems. The sliding mode control technology is introduced to enhance robustness. The unknown nonlinear functions and uncertain disturbances are approximated by the radial basis function neural networks (RBFNNs). The stability of system is ensured by the constructed Lyapunov functions. The fractional adaptive laws are proposed to update uncertain parameters. The proposed controller can ensure convergence of the tracking error and all the states remain bounded in the closed-loop systems. Lastly, the feasibility of the proposed control method is proved by giving two examples.

Leader-Following Bipartite Formation Control of Multiple Nonholonomic Robot Systems Over Signed Graph

This paper studies the bipartite formation control problem of multiple nonholonomic robot systems over signed graph. To overcome nonholonomic and underactuated control challenges, the hand position output is defined to obtain a linear hand position subsystem. A distributed control law is designed, which uses sliding mode control technology to eliminate the influence of dynamic leader, so that the global index of position formation error converges to an arbitrary small neighborhood of the origin. Then, the zero dynamic equation is computed, and based on it and Lyapunov method, the convergence conditions on controller parameters and on leader’s velocities are derived to guarantee the angle error is bounded and convergent. Finally, a simulation example containing eight robots and one leader is given to demonstrate the effectiveness of the proposed control strategy. In contrast to related results, this paper presents the complete stability analysis and corresponding stability conditions, in addition to the control law and stability of position subsystems.

Adaptive Backstepping Sliding Mode Tracking Control for Underactuated Unmanned Surface Vehicle With Disturbances and Input Saturation

This paper presents an adaptive backstepping sliding mode tracking control method for underactuated unmanned surface vehicle. The tracking controller is designed by combining backstepping and adaptive sliding mode control technology. The virtual control law is used to replace the control strategy of position error, and the position tracking control is transformed into velocity control, which can effectively avoid the input saturation and singular value problem existing in the design of traditional backstepping control law. The neural shunt model method is used to solve the differential explosion problem caused by virtual control law. The adaptive technology based on backstepping sliding mode theory is introduced to compensate the model uncertainty and time-varying disturbances of the system, and the robustness of the underactuated USV is enhanced by this method in the unknown environment. Based on the Lyapunov stability theory, it is proved that the control system error is ultimately uniformly bounded. The simulation results show that the proposed adaptive backstepping sliding mode tracking control method can achieve stable tracking in the case of system parameter uncertainty and time-varying disturbances, so it can be concluded that this method is reasonable and effective.

Finite-time synchronization in the laser network based on sliding mode control technology

We research finite-time synchronization in the laser network based on sliding mode control technology. Firstly, we modify the traditional sliding mode control technology so that it can be applied to finite-time synchronization of the network. Further, we determine the structure of the network correlation input by designing the appropriate sliding surface, and obtain finite-time synchronization criterion of the network. The advantage of our synchronization technology is that the network correlation input is very simple, and the topological structure of the network can be selected as needed.

Nonlinear adaptive position control of hydraulic servo system based on sliding mode back-stepping design method

Electro-hydraulic servo system is often affected by parameter uncertainties and mismatched random disturbances, which are two major obstacles to achieving high-performance servo control. In this article, a sliding mode adaptive controller is proposed to solve these two problems. The proposed controller employs sliding mode control method to eliminate unknown mismatched disturbances, adaptive design to deal with parametric uncertainties. A new smooth and continuous sliding mode control law is proposed to solve the design conflicts between sliding mode control technology and back-stepping adaptive control technology. The stability of the algorithm is proved based on the Lyapunov theory. Theoretically, the algorithm can make the position tracking error arbitrarily small. Through the co-simulation platform of AMESim and MATLAB/Simulink, the control performance of the developed control algorithm is verified. The results show that the developed sliding mode adaptive controller scheme can achieve high-performance tracking under the condition of parametric uncertainties and unknown mismatched disturbances.

Predefined-Time Modified Function Projective Synchronization for Multiscroll Chaotic Systems via Sliding Mode Control Technology

In the context of chaotic secure communication and based on the sliding mode control technology, this article investigates the predefined-time modified function projective synchronization for the Colpitts oscillator multiscroll hyperchaotic systems. Firstly, a four-dimensional multiscroll hyperchaotic system is introduced and the predefined-time synchronization is defined. Subsequently, applying a novel predefined-time stability criterion, an integral terminal sliding mode surface is constructed for the synchronization error system to ensure that the sliding motion is stable within a predefined time; meanwhile, an approaching controller is designed to enable the error system to reach and remain on the sliding mode surface within another predefined time, so as to ensure the realization of the predefined-time synchronization. Finally, the simulation experiments are presented to verify the effectiveness of derived theoretical results.

Signal transmission and parameter measurement in quantum bits interacting with a single-mode radiation field

Quantum systems can display the quantum chaos characteristics under non-rotating wave approximation. Because of the complex multi-body effect, the inevitability of coupling with the environment and the existence of uncertainty relation, some parameters in quantum system are often uncertain. In order to determine the properties of quantum system, we need to accurately measure any parameters in the system. In this work, we first analyse the characteristics of quantum bits interacting with a single-mode radiation field. On this basis, we design a unique technique to accurately measure the uncertain parameter in the quantum bits. Finally, we complete the synchronization transmission of signal in quantum bits based on the sliding mode control technology.

Event-triggered reinforcement learning [formula omitted] control design for constrained-input nonlinear systems subject to actuator failures

In the paper, a novel input-constrained H∞ fault-tolerant control approach is developed by using sliding mode control technology and event-triggered reinforcement learning (RL) algorithm. To reduce or even eliminate the impacts of the time-varying actuator failures, a properly sliding mode control strategy is proposed for the controlled system, while the event-triggered H∞ control scheme is established via RL algorithm for the equivalent sliding mode dynamics. By utilizing a single neural network (NN), the Hamilton–Jacobi–Bellman (HJB) equation can be solved approximately, thereby gaining time-triggered worst-case disturbance law, as well as event-triggered optimal control policy. Besides, it is unnecessary to given a initial stabilizing control input in the learning process of neural networks (NNs) in this paper. Moreover, the Lyapunov stability principle is applied to guarantee that the controlled system is uniformly ultimately bounded (UUB). Finally, to verify the feasibility and efficient performance of the developed approach, three simulations are carried out.

Stabilization of Canonical Systems via Adaptive Chattering Free Sliding Modes With No Singularity Problems

In the system and control community, the sliding mode control technology has been known as a tool which is able to handle system uncertainties and external disturbances. Simplicity in implementation and good stability performance are the other interesting features of the sliding modes. However, traditional sliding mode controllers exhibit two weaknesses, as follows: 1) generally, they have asymptotic stability in sliding mode dynamics which results in a slow speed system and 2) the so-called chattering phenomenon exists, which produces undesirable high frequency oscillations in the control signal. In this paper, the former problem is solved using a twofold terminal sliding manifold displaying desired transient and steady state behavior. The latter issue is responded to by a twofold sliding mode technology which leads to a continuous sliding control rule instead of a discontinuous switching control. The effects of uncertain terms as well as external perturbations with unknown bounds are fully compensated using updated parameters. The values of the updated parameters approach fixed values as the system trajectories converge to the equilibrium states. The analytical results of this paper are theoretically proved using the Lyapunov technique and the finite-time control strategy. Comparative computer simulations on a robotic manipulator confirm the fast convergence attribute and robust performance of the introduced adaptive robust nonsingular terminal sliding control algorithm.

Fixed-time synchronization of delayed Cohen–Grossberg neural networks based on a novel sliding mode

This paper has discussed fixed-time synchronization of discontinuous Cohen–Grossberg neural networks with time-varying delays and matched disturbances based on sliding mode control technology. First, a novel sliding-mode surface is established. And, the dynamics on the sliding-mode surface can be achieved in the fixed time by employing the Gudermannian function. Then, considering the effect of delay, two different control schemes are introduced to ensure the fixed time reachability of the sliding mode. In addition, some useful criteria are given out for fixed-time synchronization of neural networks, and the setting time is formulated in a straightforward way. Finally, some examples and simulations are presented to verify the validity of the proposed results.

Hyperbolic Tangent Function-Based Finite-Time Sliding Mode Control for Spacecraft Rendezvous Maneuver Without Chattering

This paper investigates the robust finite-time rendezvous maneuver control for spacecraft via sliding mode control technology. Two control architectures are devised for realizing the control objective, where a novel-developed sliding mode surface (SMS) is designed by resorting to the hyperbolic tangent function. Without considering the chattering problem inherent in sliding mode control, a basis control scheme is constructed to force the tracking errors entering a compact set in finite time. To reduce the effect of the chattering phenomenon, a modified controller is established by resorting to the well-designed adaptive laws. Both of these two controllers can ensure finite-time convergence for the entire system. Theoretical analysis and numerical simulations have shown the effectiveness and superiorities of the proposed methods.

Speed Regulation for PMSM Drives Based on a Novel Sliding Mode Controller

This paper develops a novel sliding mode control technology and a comprehensive evaluation methodology for speed control of permanent magnet synchronous motor (PMSM). In most of the existing literature, only control precision of the speed corrector is investigated. However, the control strategy should be stable to the noise and disturbance caused by the environment and parameter uncertainties. In order to possessing faster dynamic response, stronger anti-interference ability and high stability of input, a highly stable sliding surface is proposed for siding mode control. Unlike most of reaching laws that requires the variation of designed sliding surfaces, this method takes state vectors in consideration. In addition, a comprehensive evaluation algorithm is presented to obtain reasonable assessment on speed control for synchronous PMSMs in different operating phases (starting, transient, steady-state rating). Finally, the simulation results verify the effectiveness and validity of the proposed sliding mode speed controller.

Integrated fault estimation and fault tolerant attitude control for rigid spacecraft with multiple actuator faults and saturation

This study proposes an integrated fault estimation (FE) and fault-tolerant control design for a rigid spacecraft attitude system with inertia uncertainties, external disturbances, input saturation, and different type multiple actuator faults. A barrier function is first introduced to eliminate the effects of inertia uncertainties and disturbances in the design of the sliding mode FE observer. By using the non-singular fast terminal sliding mode control technology, a finite-time fault-tolerant attitude stabilisation controller and a finite-time fault-tolerant attitude tracking controller are designed to guarantee that the closed-loop attitude system has a good fault-tolerant performance under actuator faults. Furthermore, when considering actuator saturation, an auxiliary system is utilised to compensate for the saturation. The stability of the closed-loop system is analysed by Lyapunov theory. Finally, the effectiveness of the proposed control approach is demonstrated via simulation results.

The weighted synergetic speed control for single inverter, parallel-connected induction motor drive

In the case of unbalanced load performance, the key issue in speed control of a single inverter-powered parallel motor coupling system is how to overcome the difference in motor parameters and the effect of slip between the induction motors to maintain the same speed. Based on the synergetic control theory and synergy manifold design techniques, the model which is field-oriented vector control with reduced order induction is proposed, as well as a synergetic control strategy. Moreover, the accuracy of the rotor flux observation is one of the most important steps in the motor control. In order to improve the convergence speed of rotor flux error, a new flux observer based on the sliding mode theory is proposed. Introducing the Sig function instead of the symbol function, the sliding mode control technology is improved to observe rotor to eliminate the control chattering. Then, two motor speed coupling weighted synergetic control models are given by using the new weight vector of the parallel induction motor. These models can directly obtain the stator excitation current and torque current of the two motors. The simulation and experimental results show that the newly proposed motor synergetic control method has better steady operation performance, overcomes the shortcomings of the existing average vector control method in load imbalance and motor parameter difference and proves the validity and advancement of the design strategy.

Model predictive and adaptive neural sliding mode control for three-dimensional path following of autonomous underwater vehicle with input saturation

With model uncertainties and input saturation, a novel control method is developed to steer an underactuated autonomous underwater vehicle that realizes the following of the planned path in three-dimensional (3D) space. Firstly, Serret–Frenet frame is applied as virtual target, and the path following errors model in 3D is built. Secondly, the control method which includes kinematic controller and dynamic controller was presented based on cascade control strategy. The kinematic controller, which is responsible for generating a series of constrained velocity signals, is designed based on model predictive control. The adaptive radial basis function neural network is used to estimate the model uncertainty caused by hydrodynamic parameters. Moreover, sliding mode control technology is applied in the design of dynamic controller to improve its robustness. Then, the control effect is compared with that of LOS guidance law and PID controller by simulation experiment. The comparison results show that the proposed algorithm can improve path following effect and reduce input saturation.