Nonsingular Fast Terminal Sliding Mode Research Articles

Research on Global Nonsingular Fast Terminal Sliding Mode Control Strategy of Ball Screw Feed System Based on Improved Double Power Reaching Law

Research on Global Nonsingular Fast Terminal Sliding Mode Control Strategy of Ball Screw Feed System Based on Improved Double Power Reaching Law

Collaborative control of circumferential yarn implantation system for large-scale 3D braiding equipment using fast nonsingular terminal sliding mode

To ensure high performance collaborative control of the circumferential yarn implantation system for a specific large-scale 3D braiding equipment, a multi-motor fast nonsingular terminal sliding mode (FNTSM) controller is proposed using time-delay estimation (TDE) and deviation coupling control (DCC). Then, comparative experiments were conducted among our proposed TDE-based FNTSM controller and PD controller and TDE-based PD controller. As shown in the experimental results, the root-mean-square error (RMSE) and maximum absolute error (MAE) ensured by our FNTSM controller tracking sine signal have decreased by 89.4% and 67.1% compared with the ones by PD controller; while the RMSE of our FNTSM controller tracking slope signal is ensured within 0.03°. Meanwhile, the RMSE and MAE of our FNTSM controller tracking sine signals has been reduced by 48.2% and 56.9% due to DCC, respectively. Afterwards, less than 3% error fluctuation has been observed with load using our FNTSM controller. High control performance and strong robustness have been experimentally observed.

Improved Sliding Mode Model Reference Adaptive System Observer

In order to improve the accuracy and stability of sensorless control system of permanent magnet synchronous motor, considering the influence of external load torque on system performance, the symbol function of sliding mode control system of vehicle-mounted permanent magnet synchronous motor is prone to chattering and the robustness of traditional PI control is insufficient. In this paper, a method of combining Non-singular Fast Terminal Sliding Mode (NFTSM) and Model Reference Adaptive System (MRAS) is proposed. A Non-singular Fast Terminal Sliding Mode Controller (NFTSMC) is designed. A control strategy combining NFTSMC and Model Reference Adaptive System Observer (MRASO) (NFTSMC-MRASO) converts the observed torque value into torque current feedforward compensation to the current loop input. The large sliding mode gain is avoided, and the chattering problem of the system is overcome when the external disturbance is suddenly added. At the same time, the robustness of the system is improved under the premise of suppressing the chattering.

Self-Organizing Fuzzy Neural Nonsingular Fast Terminal Sliding Mode Control of DC-DC Buck Converter

Self-Organizing Fuzzy Neural Nonsingular Fast Terminal Sliding Mode Control of DC-DC Buck Converter

Fixed-time formation tracking for unmanned surface vehicles: A multi-layer neural networks approach

This paper investigates the distributed fixed-time formation problem of unmanned surface vehicles (USVs) in the presence of external disturbances, model uncertainties, input saturation and quantization constraints. To deal with the problem, a fixed-time sliding-mode control algorithm is proposed, where multi-layer neural networks (MNNs) are designed to approximate the unknown dynamics and composite disturbances of the system. The proposed MNNs combine the advantages of fuzzy neural networks (FNNs) and radial basis function neural networks (RBFNNs), exhibiting robust dynamic characteristics. Furthermore, the non-singular fast terminal sliding mode (NFTSM) is integrated into the fixed-time control framework to improve the robustness and speed of convergence for uncertain USV systems. Comparative simulations conducted with USVs demonstrate the superiority and effectiveness of the proposed algorithm.

Improving Direct Yaw-Moment Control via Neural-Network-Based Non-Singular Fast Terminal Sliding Mode Control for Electric Vehicles.

Given the increased significance of electric vehicles in recent years, this study aimed to develop a novel form of direct yaw-moment control (DYC) to enhance the driving stability of four-wheel independent drive (4WID) electric vehicles. Specifically, this study developed an innovative non-singular fast terminal sliding mode control (NFTSMC) method that integrates NFTSM and a fast-reaching control law. Moreover, this study employed a radial basis function neural network (RBFNN) to approximate both the entire system model and uncertain components, thereby reducing the computational load associated with a complex system model and augmenting the overall control performance. Using the aforementioned factors, the optimal additional yaw moment to ensure the lateral stability of a vehicle is determined. To generate the additional yaw moment, we introduce a real-time optimal torque distribution method based on the vertical load ratio. The stability of the proposed approach is comprehensively verified using the Lyapunov theory. Lastly, the validity of the proposed DYC system is confirmed by simulation tests involving step and sinusoidal inputs conducted using Matlab/Simulink and CarSim software. Compared to conventional sliding mode control (SMC) and NFTSMC methods, the proposed approach showed improvements in yaw rate tracking accuracy for all scenarios, along with a significant reduction in the chattering phenomenon in control torques.

Extended state observer-based continuous finite time control for a fixed-wing vertical take-off and landing unmanned aerial vehicle

Dual system Vertical Take-Off and Landing (VTOL) fixed-wing Unmanned Aerial Vehicles (UAVs) combine the advantages of both the rotorcraft and fixed-wing UAV, characterizing horizontal and vertical flight capabilities. However, they face challenges such as aerodynamic coupling between propulsion systems, model uncertainty, and external disturbances, significantly deteriorating the tracking accuracy and robustness. This paper proposes an Extended State Observer based Continuous Finite-Time Control (ESO-CFTC) scheme to solve the attitude and trajectory tracking problem of such a VTOL fixed-wing UAV. Initially, the Nonsingular Fast Terminal Sliding Mode (NFTSM) controller guarantees the tracking errors reach a prescribed manifold in finite time with a continuous reaching law, then converge to the origin in finite time while avoiding singularities. To suppress the inherent chattering problem of the sliding mode control, an ESO technique is incorporated into the ESO-CFTC scheme, which is completely decoupled with the basic NFTSM controller. The supremum of the estimation residual set is derivated theoretically. The scheme forces the tracking errors to converge into the neighborhood of the origin in finite time without requiring prior knowledge of lumped disturbance supremum values. Finally, the numerical simulation results in a Matlab/Simulink environment demonstrate that the presented method outperforms existing benchmark in terms of disturbance estimation, tracking accuracy, convergence rate, and robustness.

Adaptive Non-singular Fast Terminal Sliding Mode Control for Car-Like Vehicles with Faded Neighborhood Information and Actuator Faults

This study addresses the problem of cooperative control design for a group of car-like vehicles encountering fading channels, actuator faults, and external disturbances. It is presumed that certain followers lack direct access to the states of the leader via a directed graph. This arises challenges in maintaining synchronization and coordination within the network. The proposed control strategy utilizes non-singular fast terminal sliding mode control to accelerate consensus tracking and enhance the convergence of the overall system. This controller is designed to mitigate the impact of actuator faults in the presence of fading channels in the communication network. The effects of such issues on team performance are rigorously analyzed. Based on the Lyapunov stability principle, it has been demonstrated that the controller is capable of providing satisfactory performance for the entire system despite these challenges. Moreover, vehicle synchronization can be effectively maintained. Numerical simulations are conducted to verify the theoretical findings.

Robust trajectory tracking of a 3-DOF robotic arm using a Super-Twisting Fast finite time Non-singular Terminal Sliding Mode Control in the presence of perturbations

Extensive research has focused on enhancing the efficiency and stability of robotic arms. Sliding mode control (SMC) is commonly used in industrial robots due to its robustness and simplicity. However, SMC approaches have challenges such as chattering and slow convergence rates which can compromise tracking accuracy. To address these issues, this paper proposes a novel Super-Twisting Fast Non-singular Terminal Sliding Mode Control (ST-FNTSMC) strategy for a 3-DOF arm robot. The proposed approach significantly improves trajectory tracking accuracy, robustness, and convergence time and eliminates chattering. The proposed controller was tested in the presence of model mismatches and external disturbances. The super-twisting methodology avoided chattering effects and increased robustness against perturbations. Two Lyapunov functions ensure closed system stability and finite-time convergence. The designed ST-FNTSMC controller is implemented in real-time using a Smart Man Robot manipulator. Its performance is compared to other sliding mode controllers, such as conventional PID Sliding Mode Control (PID-SMC), Non-singular Terminal Sliding Mode Control (NTSMC), and Fast Non-singular Terminal Sliding Mode Control (FNTSMC). Experimental results demonstrate the superior performance of the proposed controller, highlighting its effectiveness in improving the efficiency and stability of industrial robots.

Direct Instantaneous Torque Control for Six-Phase SRM With Nonsingular Fast Terminal Sliding Mode Controller

Direct Instantaneous Torque Control for Six-Phase SRM With Nonsingular Fast Terminal Sliding Mode Controller

Model‐free based adaptive finite time control with multilayer perceptron neural network estimation for a 10 DOF lower limb exoskeleton

SummaryThis article presents a Model‐Free Adaptive Nonsingular Fast Terminal Sliding Mode Controller with Super Twisting and Multi‐Layer Perceptron (MLP) neural network for motion control of a 10 DOFs lower limb exoskeleton used in rehabilitation. The proposed controller employs a second‐order ultra‐local model to replace the complex dynamics of the exoskeleton and uses an MLP neural network to estimate the lumped disturbance of the ultra‐local model. To ensure accurate tracking of the desired trajectory and address the estimation errors of the MLP, an Adaptive Nonsingular Fast Terminal Sliding Mode Controller is introduced. Moreover, a Super Twisting approach is employed to eliminate the chattering phenomenon. The system's stability is analyzed using Lyapunov theory, and the desired trajectories are obtained from surface electromyography (EMG) signal measurements. The effectiveness of the proposed controller is validated through co‐simulation experiments using SolidWorks, Simscape Multibody, and MATLAB/Robotics Toolbox. Results demonstrate significant improvements in stability and precision compared to existing model‐free controllers.

Research on Neural Network Terminal Sliding Mode Control of Robotic Arms Based on Novel Reaching Law and Improved Salp Swarm Algorithm

Modeling errors and external disturbances have significant impacts on the control accuracy of robotic arm trajectory tracking. To address this issue, this paper proposes a novel method, the neural network terminal sliding mode control (ALSSA-RBFTSM), which combines fast nonsingular terminal sliding mode (FNTSM) control, radial basis function (RBF) neural network, and an improved salp swarm algorithm (ALSSA). This method effectively enhances the trajectory tracking accuracy of robotic arms under the influence of uncertain factors. Firstly, the fast nonsingular terminal sliding surface is utilized to enhance the convergence speed of the system and achieve finite-time convergence. Building upon this, a novel multi-power reaching law is proposed to reduce system chattering. Secondly, the RBF neural network is utilized to estimate and compensate for modeling errors and external disturbances. Then, an improved salp swarm algorithm is proposed to optimize the parameters of the controller. Finally, the stability of the control system is demonstrated using the Lyapunov theorem. Simulation and experimental results demonstrate that the proposed ALSSA-RBFTSM algorithm exhibits superior robustness and trajectory tracking performance compared to the global fast terminal sliding mode (GFTSM) algorithm and the RBF neural network fast nonsingular terminal sliding mode (RBF-FNTSM) algorithm.

Design and validation of a pediatric gait assistance exoskeleton system with fast non-singular terminal sliding mode controller

Existing exoskeletons for pediatric gait assistance have limitations in anthropometric design, structure weight, cost, user safety features, and adaptability to diverse users. Additionally, creating precise models for pediatric rehabilitation is difficult because the rapid anthropometric changes in children result in unknown model parameters. Furthermore, external disruptions, like unpredictable movements and involuntary muscle contractions, add complexity to the control schemes that need to be managed. To overcome these limitations, this study aims to develop an affordable stand-aided lower-limb exoskeleton specifically for pediatric subjects (8-12 years, 25-40 kg, 128-132 cm) in passive-assist mode. The authors modified a previously developed model (LLESv1) for improved rigidity, reduced mass, simplified motor arrangement, variable waist size, and enhanced mobility. A computer-aided design of the new exoskeleton system (LLESv2) is presented. The developed prototype of the exoskeleton appended with a pediatric subject (age: 12 years old, body mass: 40 kg, body height: 132 cm) is presented with real-time hardware architecture. Thereafter, an improved fast non-singular terminal sliding mode (IFNSTSM) control scheme is proposed, incorporating a double exponential reaching law for expedited error convergence and enhanced stability. The Lyapunov stability warrants the control system's performance despite uncertainties and disturbances. In contrast to fast non-singular terminal sliding mode (FNSTSM) control and time-scaling sliding mode (TSSM) control, experimental validation demonstrates the effectiveness of IFNSTSM control by a respective average of 5.39% and 42.1% in tracking desired joint trajectories with minimal and rapid finite time converging errors. Moreover, the exoskeleton with the proposed IFNSTSM control requires significantly lesser control efforts than the exoskeleton using contrast FNSTSM control. The Bland-Altman analysis indicates that although there is a minimal mean difference in variables when employing FNSTSM and IFNSTSM controllers, the latter exhibits significant performance variations as the mean of variables changes. This research contributes to affordable and effective pediatric gait assistance, improving rehabilitation outcomes and enhancing mobility support.

Control of Quadcopter Based on Adaptive Fast Nonsingular Terminal Sliding Mode

This paper presents a novel approach to address the trajectory tracking control problem for quadcopter systems subjected to multiple disturbances. The proposed method integrates sliding mode control with adaptive control techniques, resulting in an effective adaptive fast nonsingular terminal sliding mode (AFNTSM) controller. The controller structure can be divided into an internal attitude control loop and an external position control loop. In the altitude control loop, a strategy employing AFNTSM is utilized to tackle time-varying external disturbances. In the attitude control loop, given the existence of uncertain system parameters, an attitude controller is designed by combining a PID controller with an extended state observer. The asymptotic stability of the system is verified by using Lyapunov’s theorem. Finally, experimental flights validate the superiority of this control strategy over the traditional PID algorithm.

Fixed‐time tracking control of manipulators based on a fast variable power reaching law

SummaryAs for the problem of trajectory tracking of a two‐joint series manipulator, a novel fixed‐time control scheme is proposed based on non‐singular fast terminal sliding mode (NFTSM) control and a fast variable power reaching law. The innovation of the proposed method is: (1) by employing the NFTSM surface, we solve the singularity problem existed in traditional terminal sliding mode surface. (2) The convergence rate is increased by 50% by the combination of fixed‐time control and NFTSM surface control. (3) A new fast variable power reaching law is presented, which combines the advantages of the double power reaching law and the fast power reaching law, and it effectively improves the reaching rate and reduces the amplitude by 40–60 N m. Theoretical analysis proves that the better tracking performance is obtained, and its convergence time upper limit is not affected by the initial states of the system. Finally, the effectiveness and feasibility of our controller are verified through a numerical simulation.

Improved Robust Control of a New Morphing Quadrotor UAV Subject to Aerial Configuration Change

Over these last years, morphing Unmanned Aerial Vehicles (UAVs) control became one of the critical problems, which has not been properly solved by the researchers. This is due to their particular and complex features compared to the ordinary ones as: morphology change, flight transition, model asymmetry, geometric variation, different dynamics, over-actuation and high nonlinearity. To deal with such challenges, this paper addresses the control of a new over-actuated morphing drone that changes its arms in different orientations to form various morphology and configuration models. First, the present system is divided into two principal parts: an attitude subsystem and a position subsystem. Furthermore, an improved Adaptive Nonsingular Fast Terminal Sliding Mode Controller (ANFTSMC) is proposed to stabilize the attitude loop. While the position loop is controlled by Integral Backstepping Controller (IBC) using Lyapunov theory. Second, with the aim to better adjust the control gains, a recent metaheuristic technique based on the Whale Optimization Algorithm (WOA) is adopted. At last, a comparative study with the standard control algorithms is accomplished to evaluate the effectiveness and robustness of the proposed methods.

Retracted: Finite-Time Attitude Cooperative Control of Multiple Unmanned Aerial Vehicles via Fast Nonsingular Terminal Sliding Mode Control

Retracted: Finite-Time Attitude Cooperative Control of Multiple Unmanned Aerial Vehicles via Fast Nonsingular Terminal Sliding Mode Control

Adaptive Proportional Integral Derivative Nonsingular Dual Terminal Sliding Mode Control for Robotic Manipulators

This article aims to develop a new Adaptive Proportional Integral Derivative (PID) Nonsingular Dual Terminal Sliding Mode Control, designed for tracking the position of robot manipulators under disturbances and uncertainties. Compared with existing PID Nonsingular Fast Terminal Sliding Mode (PIDNFTSM) controllers, this work effectively avoids singularity problems in control while significantly enhancing the convergence speed of errors. An adaptive reaching law is proposed to estimate the bound information of the first derivative of lumped disturbance by regulating itself based on sliding variables. The overall system stability is proven by using the Lyapunov approach. Subsequent simulation results verify the effectiveness of the proposed controller regarding tracking error reduction, energy efficiency enhancements, and singularity avoidance.

Robust Adaptive Learning Control of Space Robot for Target Capturing Using Neural Network.

This article investigates the robust adaptive learning control for space robots with target capturing. Based on the momentum conservation theory, the impact dynamics is constructed to derive the relationship of generalized velocity in the pre-impact and post-impact phase. Considering the nonlinear dynamics with contact impact, the robust control using nonsingular terminal sliding mode (NTSM) and fast NTSM is designed to achieve the fast realization of the desired states. Furthermore, for the unknown dynamics of the combination system after capturing a target, the adaptive learning control is developed based on neural network and disturbance observer. Through the serial-parallel estimation model, the prediction error is constructed for the update of adaptive law. The system signals involved in the Lyapunov function are proved to be bounded and the sliding mode surface converges in finite time. Simulation studies present the desired tracking and learning performance.

Fixed‐time fault‐tolerant control of manipulator systems based on sliding mode observer

AbstractA fixed‐time fault‐tolerant control scheme based on sliding mode observer is proposed, which makes the system more stable and stronger anti‐jamming ability. In our design, its distinct characteristic is to combine the passive fault‐tolerant control and non‐singular fast terminal sliding mode (NFTSM). And it ensures that the system states can converge to a very small neighborhood near the equilibrium point in a fixed time no matter in normal condition or fault condition. In addition, a novel sliding‐mode observer and a fast variable power reaching law are added to make the system converge faster and chattering smaller. Finally, the computer simulation results of a two‐joint manipulator demonstrate the feasibility of the proposed strategy.