Nonsingular Terminal Sliding Mode Research Articles

A modified sliding mode controller based on Fuzzy logic to control the longitudinal dynamics of the autonomous vehicle

This article delves into the intricate world of controlling the longitudinal dynamics of autonomous vehicles. In the first part, we studied two distinct controllers: the Super Twisting Sliding Mode Control and its modified version enriched with the integration of fuzzy logic, applied to the longitudinal dynamics of the autonomous automobile to follow a desired speed longitudinal profile, the two controllers are compared with a Neural Network-Based Non-singular Terminal Sliding-Mode Control, the system takes the throttle and brake as its inputs and delivers speed and acceleration as outputs. The overarching objective is to ensure that the controlled vehicle maintains a close and precise alignment with the desired speed profile. The second part of our research is dedicated to the development of adaptive cruise control systems and cruise control according to the safety conditions. This controller consists of two blocks low and upper controller, in upper controller the inputs are the speeds of the automobile in front and of the autonomous automobile itself, the safety distance, the measured distance. The output is the desired acceleration. The objective is to maintain a distance between the front vehicles, greater than or equal to the safety distance. For this, to achieve this task, we have implemented a control system known as the Proportional Integral Derivative (PID) controller in the adaptive cruise control system to control this system. In the low controller block, the same controllers used in the first part: the Super Twisting Sliding Mode Control and its modified version based on fuzzy logic, are applied, the system inputs are throttle and brake, and the outputs are speed and acceleration. This system is processed by MATLAB code, we obtained a better result with our proposed controller such that the maximum absolute speed error is equal to 0.0144 m/s in the first case of speed tracking, and to 0.006 m/s in the second case of the using adaptive cruise control, the illustrations below show the efficiency and robustness of these controllers.

Visualized neural network-based vibration control for pigeon-like flexible flapping wings

This study investigates pigeon-like flexible flapping wings, which are known for their low energy consumption, high flexibility, and lightweight design. However, such flexible flapping wing systems are prone to deformation and vibration during flight, leading to performance degradation. It is thus necessary to design a control method to effectively manage the vibration of flexible wings. This paper proposes an improved rigid finite element method (IRFE) to develop a dynamic visualization model of flexible flapping wings. Subsequently, an adaptive vibration controller was designed based on non-singular terminal sliding mode (NTSM) control and fuzzy neural network (FNN) in order to effectively solve the problems of system uncertainty and actuator failure. With the proposed control, stability of the closed loop system is achieved in the context of Lyapunov’s stability theory. At last, a joint simulation using MapleSim and MATLAB/Simulink was conducted to verify the effectiveness and robustness of the proposed controller in terms of trajectory tracking and vibration suppression.The obtained results have demonstrated great practical value of the proposed method in both military (low-altitude reconnaissance, urban operations, and accurate delivery, etc.) and civil (field research, monitoring, and relief for disasters, etc.) applications.

Adaptive Neural Network-Based Practical Predefined-Time Nonsingular Terminal Sliding Mode Control for Upper Limb Rehabilitation Robots

This article investigates the predefined time trajectory tracking control problem of upper limb rehabilitation robots in the presence of the model uncertainty and external disturbances. An adaptive neural network-based practical predefined-time fast nonsingular terminal sliding-mode control (PPT-FNTSMC) strategy is proposed, in which a novel sliding mode surface is constructed to achieve predefined-time convergence and avoid the singularity problem as well. Additionally, a neural network is employed to approximate the lumped disturbances, and the estimated values are utilized in the controller for compensation, thereby reducing the required switching gain and mitigating chattering phenomenon. A rigorous theoretical analysis is provided to illustrate that the tracking errors can converge to a vicinity of the origin in a predefined time. Finally, simulations on a two-joint single-arm robot and a 5-DOF upper-limb exoskeleton are conducted and compared with an existing control method to demonstrate the effectiveness and superiority of the proposed control strategy.

Predefined-time trajectory tracking control of free-flying space manipulator subject to uncertainties and disturbances

This article addresses the predefined-time trajectory tracking control of free-flying space manipulator (FFSM) subject to uncertainties and disturbances. First, a predefined-time nonsingular terminal sliding mode (NTSM) controller is developed with the high insensitivity to uncertainties and strong robustness against disturbances. The generalized attitude and angular velocity tracking errors under the predefined-time NTSM controller can stabilize to zero in predefined time. Then, an adaptive version of the predefined-time NTSM controller is presented. The parametric adaptation mechanism is incorporated to identify the square of the upper bound of the lumped unknown item. Thus, the predefined-time adaptive NTSM (ANTSM) controller is smooth with no obvious chattering phenomenon and can maintain the high tracking accuracy simultaneously. The generalized attitude and angular velocity tracking errors under the predefined-time ANTSM controller can stabilize to the minor bounded regions around zero in predefined time. Simulations are provided to demonstrate the exploited controllers.

Quadrotor UAV Trajectory Tracking Control Based on Adaptive Non-singular Terminal Sliding Mode

To address the issue of the quadrotor unmanned aerial vehicle (UAV) being susceptible to external disturbances and model uncertainties during flight, an adaptive non-singular terminal sliding mode controller with disturbance compensation is proposed. Firstly, the quadrotor UAV dynamic model considering system disturbances is constructed using the Newton-Euler method. Next, the trajectory tracking problem is transformed into a command tracking control problem for each channel. To enhance the adaptability and robustness of trajectory tracking for the quadrotor UAV, an adaptive law is designed to dynamically adjust the sliding mode surface gain. In addition, a disturbance observer is introduced to estimate and compensate for external disturbances and model uncertainties. Finally, the stability of the designed controller is proven through the Lyapunov function. Simulation results demonstrate that the proposed controller effectively enhances the disturbance resistance and trajectory tracking response speed of the quadrotor UAV.

Adaptive Terminal Sliding Mode Trajectory Tracking Control for Autonomous Vehicles Considering Completely Unknown Parameters and Unknown Perturbation Conditions

In the actual implementation of autonomous vehicle controller and related applications, it is difficult to obtain all the actual parameters of the vehicle. Considering factors such as uneven pavement and different pavement conditions, it is difficult to accurately establish the vehicle dynamic system model. Based on the non-singular terminal sliding mode and adaptive control theory, this paper establishes a trajectory tracking control strategy for an autonomous vehicle with unknown parameters and unknown disturbances. Firstly, the complex trajectory tracking problem is decoupled from the position and heading angle tracking problem, and the preview error equation is established. Secondly, a non-singular terminal sliding mode (NTSM) controller is established to stabilize the trajectory tracking error to the origin in a finite time, and adaptive laws are proposed to estimate the unknown vehicle parameters to adapt to environmental changes. Through the CarSim–Matlab platform, typical working conditions are implemented to verify the proposed controller. Our experimental outcomes affirm that the NTSM controller effectively guarantees the autonomous vehicle’s accurate following of the reference path, ensuring smooth control inputs throughout the entire process.

A Robust Adaptive Non-Singular Terminal Sliding Mode Control: Application to an Upper-Limb Exoskeleton with Disturbances and Uncertain Dynamics

This paper presents a new control strategy for uncertain upper-limb exoskeleton systems, which are known to have high nonlinearities, unmodeled dynamics, and uncertainties. The proposed technique is based on the terminal sliding mode control algorithm and its nonsingular design method and incorporates an adaptive control approach to estimate the upper bounds of the unknown system uncertainties, which helps to improve the accuracy of the control and reduce the effects of disturbances. The stability of the proposed control strategy is confirmed using Lyapunov theory, and its effectiveness is tested on a two-degrees-of-freedom upper-limb exoskeleton. The results demonstrate that the proposed control scheme provides robust, fast, and finite-time convergence as well as an effective control approach capable of dealing with the disturbances and uncertainties that such systems are prone to.

Adaptive Second-Order Fixed-Time Nonsingular Terminal Sliding Mode Control Based on Barrier Function for Nonlinear Systems

Adaptive Second-Order Fixed-Time Nonsingular Terminal Sliding Mode Control Based on Barrier Function for Nonlinear Systems

Disturbance observer‐based control for cable‐driven parallel robots with external disturbance using deep reinforcement learning

AbstractIn cable‐driven parallel robots (CDPRs) practical applications, external disturbances inevitably influence the actuator performance, leading to low positioning accuracy of end‐effector (EE), and even system crashes. This paper addresses a disturbance observer‐based control scheme using deep reinforcement learning (RL) to suppress the effect of external disturbances. A controller via the non‐singular terminal sliding mode (NTSM) is proposed to enhance the system robustness. The estimation of the disturbance is investigated, and the deep RL is employed to enhance the model‐based disturbance observer, namely, the RLDO, and a corresponding controller via NTSM (RLDO‐NTSMC) is proposed. Simulations and experimental results validate that the RLDO effectively improves the estimation accuracy, and the RLDO‐NTSMC significantly increases the control accuracy of CDPRs. The root mean square errors of the EE's positioning errors controlled by the RLDO‐NTSMC decreased by over 93% compared with the classical augmented proportional–derivative (APD) controller.

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.

Fractional Order Complementary Non-singular Terminal Sliding Mode Control of PMSM Based on Neural Network

Fractional Order Complementary Non-singular Terminal Sliding Mode Control of PMSM Based on Neural Network

Adaptive Nonsingular Terminal Sliding Mode Tracking Control for High-speed Trains With Input Constraints and Parametric Uncertainties

Adaptive Nonsingular Terminal Sliding Mode Tracking Control for High-speed Trains With Input Constraints and Parametric Uncertainties

Integrated guidance and control design by active disturbance rejection method for high-velocity target interceptor with DCS thruster

The present paper proposes a novel integrated guidance and control (IGC) method for engaging with high-speed targets such as ballistic projectiles. considering an extreme short period of terminal engagement due to high relative velocity between target and interceptor, it is particularly important for IGC law to show desirable performance in the presence of various uncertainties (e.g. variation in aerodynamic coefficients) and disturbances (e.g. target maneuver and drag). This article extends the ICG law for mismatched and feedback form equations based on the Active Disturbance Rejection Control (ADRC) method using the back-stepping technique and the Reduced-order Extended State Observer (RESO). The primary consideration is the application of thrusters on the center of mass as the Divert Control System (DCS), along with the daisy-chain technique for control allocation between the fins and thruster commands. Contrary to previous research, the filter and angle measurement error are modeled for the seeker as a crucial parameter to highlight the significance of the thruster. The simulation results indicate the efficiency of the developed method for near-miss or hit-to-kill engagement with tactical ballistic targets. It is shown that the thruster plays a significant role in high-altitude engagements, specifically in the presence of non-ideal seeker. Finally, using the Monte Carlo simulation, it is proved that adding inner loops to the developed technique will not remove the IGC’s advantage over the conventional approach and Non-singular Terminal Sliding Mode (NTSM) guidance law.

Application of Backstepping Control With Nonsingular Terminal Sliding Mode Surface Technique to Improve the Robustness of Stator Power Control of Asynchronous Generator-Based Multi-Rotor Wind Turbine System

The conventional backstepping control (CBC) technique for the asynchronous generator (AG) incorporated in a multi-rotor wind turbine (MRWT) system faces several challenges, including torque and stator power ripples, lack of robustness, and low-quality stator currents. Furthermore, the CBC performs poorly under distorted grid voltage conditions. To address these issues, this study proposes applying backstepping nonsingular terminal sliding mode control (BNTSMC). The controller design involves incorporating a NTSMC into the control law of the CBC technique, where Lyapunov theory was used to analyze the stability of the suggested approach. The synthesis of the suggested controller revolves around two sliding mode surfaces, specifically the stator powers of the AG, which are used to determine the final control laws. The advantages of this technique are excellent robustness against internal and external disturbances based on NTSMC, and the controller exhibits asymptotic stability based on the backstepping technique. Simulation tests in MATLAB software on a 1.5 MW AG-based MRWT system clearly demonstrate the advantages of BNTSMC over CBC.

The Non-Singular Terminal Sliding Mode Control of Underactuated Unmanned Surface Vessels Using Biologically Inspired Neural Network

Underactuated Unmanned Surface Vessels (USVs) are widely used in civil and military fields due to their small size and high flexibility, and trajectory tracking control is a critical research area for underactuated USVs. This paper proposes a trajectory tracking control strategy using the Biologically Inspired Neural Network (BINN) for USVs to improve tracking speed and accuracy. A virtual control law is designed to obtain the required virtual velocity for trajectory tracking control, in which the velocity error is calibrated to ensure that the position error converges to zero. To observe and compensate for unknown and complex environmental disturbances such as wind, waves, and currents, a nonlinear extended state observer (NESO) is designed. Then, a controller based on Non-singular Terminal Sliding Mode (NTSM) is designed to resolve the problems of singular value and controller chattering and to improve the controller response speed. A BINN is introduced to simplify the process of differentiation, reduce the input values of the initial state, and solve the problem of thruster input saturation. Finally, the Lyapunov stability theory is utilized to analyze the stability of the proposed algorithm. The simulation results show that the proposed algorithm has a higher trajectory tracking accuracy and speed than traditional methods.

Non-singular terminal sliding mode control for trajectory-tracking of a differential drive robot

This paper presents a trajectory control scheme for a non-holonomic differential drive mobile robot using the Non-singular Terminal Sliding Mode (NTSM) control method. The proposed approach, in fact, is a cascade control system scheme with the NTSM based dynamic controller at the internal loop which tracks the robot’s velocity quantities and a kinematic controller at the outer loop to regulate the robot’s position. In this manner, the control performance is robust to both disturbances and model’s uncertainties, as well as guarantees fast, finite-time convergence at better tracking precision. The simulation results demonstrate the merit of the anticipated control scheme.

Output-Constrained Adaptive Composite Nonsingular Terminal Sliding Mode Attitude Control for a Class of Spacecraft Systems with Mismatched Disturbances and Input Uncertainties

Output-Constrained Adaptive Composite Nonsingular Terminal Sliding Mode Attitude Control for a Class of Spacecraft Systems with Mismatched Disturbances and Input Uncertainties

New non-singular terminal sliding mode control of DC motor

Terminal Sliding Mode control (TSM) is created by equivalent control and discontinuous control, but when the states are close to zero the singularity may occur. To avoid this phenomenom Non-Singular Terminal Sliding Mode Control is introduced. But this technique also makes the convergence time longer. This article proposes a new Non-Singular Terminal Sliding Mode Control (NSTSM) to keep the convergence time short when avoiding sigularity. The process of synthesizing the control law is strictly mathematically guaranteed. Simulations in Matlab visually represent the research results.

A New Reaching Law Based Nonsingular Terminal Sliding Mode Control Scheme for the Servo System With Periodic Uncertainties

A New Reaching Law Based Nonsingular Terminal Sliding Mode Control Scheme for the Servo System With Periodic Uncertainties

Hierarchical Non-Singular Terminal Sliding Mode Control with finite-time disturbance observer for PMSM speed regulation system

Hierarchical Non-Singular Terminal Sliding Mode Control with finite-time disturbance observer for PMSM speed regulation system