Adaptive Sliding Mode Control Scheme Research Articles

Trajectory Tracking Control of Mobile Manipulator Based on Improved Sliding Mode Control Algorithm

Research on trajectory tracking control for climbing welding robots holds significant importance in the field of automated welding. However, existing trajectory tracking methods suffer from issues such as jitter and slow speed. In this paper, an improved sliding mode control strategy is proposed based on the self-designed wall-climbing welding mobile manipulator. Firstly, a new adaptive sliding mode control strategy is proposed for the mobile platform based on the kinematic model. By introducing a new approach law, the controller is designed when the distance between the center of mass is unknown. Secondly, regarding the manipulator, we analyze simplified dynamic equations, extract uncertain components, and utilize a CNN for compensation. This compensation strategy is integrated into the sliding mode control law, achieving precise control over the manipulator and effectively resolving issues like slow tracking speeds, large errors, and chattering. The stability of the robot control system is proved by the Lyapunov function. Through simulation analysis and experimental validation, the proposed control method is confirmed to be feasible and superior.

Dynamic-matching adaptive sliding mode control for hypersonic vehicles

Hypersonic vehicles exhibit significantly varied dynamic characteristics across different flight regimes. These characteristics, such as model uncertainties and actuator saturation levels, have strong time-varying properties, necessitating a control strategy capable of adaptively matching robustness and responsiveness to such variability. This paper introduces an adaptive sliding mode control strategy tailored for hypersonic vehicles, which dynamically aligns controller performance with the vehicle's varying dynamic properties. Initially, a quantitative model to characterize the dynamic uncertainty of the hypersonic vehicle is constructed, and an online adaptive method to estimate the bounds of model uncertainty is proposed. This method enables real-time adaptation of controller robustness. Furthermore, the study employs artificial potential functions for online estimating control saturation and actuation rates. It adaptively modulates the control response rate coefficients based on these estimations, effectively mitigating saturation while ensuring the rapid convergence of tracking errors. Additionally, the stability of the system is scrutinized through Lyapunov theory, which verifies that the tracking error remains uniformly ultimately bounded. The simulation results corroborate the efficacy of the proposed approach, illustrating advancements in robustness, responsiveness, chattering suppression, and saturation prevention.

Effect of nonlinear stiffness on single link flexible joint robotic manipulator and its control

This study aims to investigate the significant dynamics of a Single Link Flexible Joint (SLFJ) Robotic Manipulator and implement chaotic control using the Adaptive Sliding Mode Control (ASMC) algorithm. The mathematical model of the system incorporates stiffness nonlinearity by introducing the function (x-x3) Various dynamical tools such as stability analysis of equilibrium points, sensitivity to initial conditions, orbit diagrams for parameter variations, Lyapunov spectrum, and frequency spectrum analysis are employed. The ASMC algorithm is utilized to suppress the chaotic behavior of the system. The equilibrium points are determined for critical parameter values, with the Jacobian matrix and corresponding eigenvalues exhibiting conjugate complex with negative real parts, indicating stability resembling a spiral saddle. Phase portraits illustrate the location and range of the chaotic attractor. Investigation of parameter ′a′ using orbit diagrams and Lyapunov spectrum reveals the transition from periodic to chaotic oscillations. The frequency spectrum confirms the chaotic nature of the system. Parameter estimation, state trajectories, and sliding surface analysis demonstrate that the ASMC scheme can effectively control the system in less than 0.3 s. Nonlinear stiffness has not been previously considered in SLFJ Robotic Manipulators, highlighting a novel aspect of this study. The results unveil new chaotic ranges for parameter variation previously undocumented. Frequency spectrum analysis is employed to distinguish between noise and chaotic oscillations, addressing a significant challenge in real-time systems. The ASMC algorithm is specifically designed to control chaotic oscillations, demonstrating its effectiveness in this context.

Design and Control Performance Optimization of Variable Structure Hydrostatic Drive Systems for Wheel Loaders

The traditional loader drive system is based on the hydraulic torque converter as the key component, and its gear is shifted through the coordination of the clutch and gearbox, which greatly increases power loss and operator fatigue. To address the above problem, a variable-structure hydrostatic drive system is proposed. This system adopts a closed-loop design and adjusts the displacement of the pump and dual motors to follow the throttle opening of the vehicle, achieving automatic gear shifting and smooth speed regulation. It can also automatically change the system structure according to the vehicle’s speed, meeting the vehicle’s demand for rapid switching output of high torque and high speed. At the same time, in the displacement matching control process, an adaptive sliding mode control scheme based on radial basis function neural network compensation is proposed. This scheme designs an adaptive hyperparameter update strategy according to the characteristics of the system to effectively compensate for changes in uncertain factors. Experimental results show that, compared to traditional drive systems, this system has the characteristics of simple operation, smooth speed regulation, and high fuel economy.

Nonlinear Robust Adaptive Sliding Mode Control Strategies Involve a Fractional Ordered Approach to Reducing Dengue Vectors

This study presents an innovative approach by integrating adaptive sliding mode control strategies with fractional order modeling to address the challenge of reducing Aedes aegypti mosquito populations, the primary vector of Dengue - a widespread and debilitating disease. By employing the Atangana-Baleanu-Caputo fractional operator to model the dynamics of the mosquito population, we achieve a more precise representation of complex and non-linear behaviors. The motivation behind adopting the Adaptive Sliding Mode Control (ASMC) approach lies in the critical need to efficiently control Aedes aegypti mosquito populations, a key step in combating the prevalence of dengue. The ASMC method dynamically adjusts control parameters based on evolving conditions, enhancing its adaptability to the changing dynamics of mosquito populations.The Lyapunov stability theorem ensures the reliability of tracking convergence and control structure. Additionally, we implement the Toufik Atangana method to solve both state and adjoint fractional differential equations using the ABC derivative operator. This incorporation adds a novel dimension to the study, providing a comprehensive framework for addressing the intricate dynamics inherent in the Aedes aegypti mosquito population. To assess the effectiveness of the proposed strategy, a numerical performance index is introduced at the end of the abstract. This index justifies the controller’s efficacy by comparing it to other conventional controllers. The inclusion of this quantitative measure reinforces the significance of the proposed strategy in the context of dengue prevention and control efforts.

Design of nonsingular second-order terminal sliding mode controller for cyber-physical systems with time-delays and cyber-attack on actuators

This paper introduces an innovative adaptive nonsingular Second-Order Terminal Sliding Mode (SOTSM) control strategy specifically designed to stabilise disturbed nonlinear Cyber-Physical Systems (CPSs) within a finite timeframe. Unlike the conventional methods, our approach incorporates a novel nonlinear sliding surface that eliminates the need for a reaching step, significantly enhancing the system's robustness. Novel real-time adaptive control laws are developed to cope with external perturbations, time-varying delays, and cyber-attack on actuators without requiring the identification of their upper bounds. The proposed method ensures robust performance for time-varying delayed and disturbed nonlinear CPSs, even in the face of strong cyber-attacks targeting the actuators. Moreover, the proposed method has distinct advantages: it delivers rapid response times, enhanced flexibility, exceptional accuracy, smooth and robust control devoid of transient fluctuations or chattering, and ensures finite-time convergence. Simulation results comprehensively demonstrate the superior efficiency and success of our proposed technique compared to traditional methods such as integral Sliding Mode Control (SMC) and State-Feedback Control (SFC) schemes.

Interval type-2 fuzzy sliding mode control for a cable-driven parallel robot with elastic cables using metaheuristic optimization methods

In this paper, a supervisory interval type-2 fuzzy adaptive sliding mode control scheme is addressed for cable robots. In the proposed control scheme, intelligent methods are combined with conventional sliding mode control to achieve optimal adjustment of control parameters. This approach ensures accurate tracking performance, despite the structural constraints of cable robots. These constraints include the production of purely tensile forces and the effects due to inherent elasticity, which will make the design of the controller challenging. For this purpose, the internal force concept is utilized to ensure the tension style of cables. Additionally, considering a compensator part in the proposed controller and applying the singular perturbation theorem, the vibration effects of elastic cables are handled, and stability is proved through the second Lyapunov method. Therefore, the desired performance of the control system will be guaranteed for the movements that stimulate the vibration modes of cables. An interval type-2 fuzzy logic controller is proposed to adjust the control gain, effectively reducing the chattering level. Moreover, a supervisory interval type-2 fuzzy logic control system is introduced to regulate the gains within the sliding surface. The Grasshopper Optimization Algorithm is employed to select the optimal parameters for the membership functions of the fuzzy system. The results of the conducted simulations show that the desired tracking performance is provided, despite different uncertain parameters and the structural constraints of the considered cable robot.

New Class $\mathcal {K}_\infty$ Function-Based Adaptive Sliding Mode Control

To reduce the chattering and overestimation phenomena existing in classical adaptive sliding mode control, this paper presents a new class <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {K}_\infty$</tex-math></inline-formula> function-based adaptive sliding mode control scheme. Two controllers are proposed in terms of concave and convex nonlinear functions to implement this kind of control structure. To avoid large initial control magnitudes, two modified control schemes are provided, which extend the proposed methodology to different scenarios. It is proven that the proposed controllers yield finite-time convergence to a real sliding mode. Finally, simulations and discussions are presented to show the advantages and effectiveness of the proposed control structure.

Decentralized discrete adaptive sliding mode control for interconnected nonlinear systems

This article presents a study on controlling a class of large-scale systems composed of interconnected subsystems. The systems are represented by discrete block-oriented models with unknown parameters. This article proposes a novel adaptive sliding mode control strategy to address the tracking control problem and minimize the impact of interconnection. This approach leverages the robustness of sliding mode control against unmodeled dynamics and disturbances with the advantages of adaptive control. To adapt the system’s parameters, a recursive parametric estimation algorithm using least-squares techniques is employed. The proposed method offers benefits such as robustness against parameter uncertainties, handling of nonlinearities, improved tracking accuracy, and reduced chattering phenomena. The effectiveness of the method is demonstrated through the evaluation of two simulation examples.

An Improved Adaptive Sliding Mode Control Based on Time-Delay Control for Robot Manipulators

This paper proposes a new adaptive sliding mode control (ASMC) scheme for robot manipulators not only by designing a sliding variable and an adaptive law but also by compensating a time-delay estimation (TDE) error induced by time-delay control (TDC). Based on the operating cycle, because TDC utilizes the previous angular acceleration and input torque for the estimation of the dynamics of the manipulators, TDC produces an inevitable TDE error and this paper compensates the present TDE error by using the previous TDE error. For the ASMC, this paper constructs the sliding variable by additionally utilizing the previous error and its derivative. Also, this paper proposes an adaptive law, which guarantees the positive condition of the adaptive parameter, by using the current adaptive parameter value and the sampling period. For the stability analysis, this paper shows uniformly ultimately bounded (UUB) stability of the sliding variable for the manipulators controlled by the proposed ASMC scheme. The simulation and experimental results present the effectiveness of the proposed control schemes.

Adaptive Sliding Mode Control Strategy for Horizontal Vibration of High-speed Elevator Based on Model Identification

The transverse vibration equation of a high-speed elevator car system is established to address the problem of passenger comfort due to transverse vibration caused by the unevenness of guide rails. The Hankel-Toeplitz model of transverse vibration is derived by considering the excitation-response hysteresis phenomenon. The least-squares method is used to identify the model parameters of the car system by combining the measured vibration acceleration data of the high-speed elevator. Then, the model's accuracy is verified by comparing the modeled response with the measured vibration response. Further, based on the theory of sliding mode variable structure control, an adaptive sliding mode active damping control strategy is designed for instantaneous power, and the comparative analysis of vibration acceleration and displacement of the car system under sliding mode control under light and heavy load conditions and different control strategies is carried out by MATLAB to verify the feasibility and effectiveness of the proposed control strategy parameter identification model.

Model-Free Adaptive Sliding Mode Control Method for Unmanned Surface Vehicle Course Control

A novel data-driven-based adaptive sliding-mode control scheme is proposed for unmanned surface vehicle course control in the presence of disturbances. The proposed method utilizes the model-free adaptive control (MFAC) theory. On account of the unknown dynamics of the USV course system, the control scheme is only established by online input and output information of the system. Based on a model-free adaptive control scheme, the system disturbance estimation technique is applied to compensate for the disturbances in the established compact form dynamic linearization data model. The controller is designed and combined with the sliding mode method, and a second-order switching surface with a fast terminal sliding function is employed to achieve finite-time convergence. Furthermore, an analysis of the stability of the control system is provided. Finally, MATLAB simulations are implemented to verify the validity and robustness of the proposed control scheme by comparing it with PID and typical model-free adaptive sliding mode control.

Adaptive fixed-time sliding mode control for spacecraft reorientation with attitude pointing constraints and disturbance rejection

Spacecraft reorientation with attitude pointing constraints and the uncertainty of inertia and external disturbance is investigated in this paper. By introducing the potential function into the design of non-singular fixed-time sliding mode surface, the proposed controller can achieve fixed-time convergence and the convergence time of attitude error can be predetermined by selecting appropriate parameters. Meanwhile, the attitude pointing constraints can be satisfied all the time. The designed sliding surface and potential function have two equilibrium points, which guarantees the unwinding-free performance. Furthermore, an adaptive sliding mode control scheme is developed to handle the system lumped disturbance. Rigorous Lyapunov analyses are employed to ensure practical fixed-time closed-loop stability in the presence of system disturbance uncertainties and attitude pointing constraints. Therefore, the fixed-time stability, the feasibility of attitude pointing constraints and disturbance rejection are achieved simultaneously with the proposed controller. Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed method.

Quasi‐Z based adaptive sliding mode control for three‐phase photovoltaic grid‐connected system

AbstractConsidering the non‐linear characteristics of both the input and output of photovoltaic (PV) modules and quasi‐Z‐source inverters, as well as the unpredictable natural factors such as large disturbances caused by changes in illumination and temperature, an average state model for the PV quasi‐Z‐source inverter is established. This paper uses the output current of photovoltaic module, DC‐link capacitor voltage and its integral as state variables, then an adaptive reaching law with second‐order sliding mode characteristics is designed by combining with power reaching law and variable speed reaching law. By using the sliding mode controller based on the adaptive reaching law to control the stability of the DC‐link voltage of the quasi‐Z‐source inverter and the small capacitor voltage ripple, the photovoltaic system can operate stably at the maximum power point when the temperature and illumination conditions change abruptly, and the grid‐connected effect is improved. Through SIMULINK and RT‐LAB real‐time simulation, the effectiveness of the proposed adaptive sliding mode control strategy is verified when the environment changes, which effectively improves the dynamic response speed and grid‐connected effect of the system, and ensures the global robustness of the grid‐connected system.

Discrete‐time extended state observer‐based model‐free adaptive constrained sliding mode control with modified prescribed performance via CFDL and PFDL

AbstractTo tackle the trajectory tracking problem and achieve high control accuracy in many actual nonlinear systems with unknown dynamics and input saturation, a novel discrete‐time extended state observer‐based model‐free adaptive constrained sliding mode control with modified prescribed performance is investigated via compact‐form dynamic linearization (CFDL) and partial‐form dynamic linearization (PFDL). Firstly, the original non‐affine system is turned into an affine one comprising an unknown nonlinear term and a linearly parametric term affine to the input via both PFDL and CFDL. Then, a discrete‐time extended state observer (DESO) is used to estimate the lumped disturbance containing the unknown nonlinear time‐varying term and the term relevant to the estimation error of pseudo partial derivative (PPD) parameter. Furthermore, a modified prescribed performance function is introduced in the model‐free adaptive sliding mode control scheme to keep the output tracking error in the prescribed bound without causing any asymmetric offset error in the steady‐state. Meanwhile, to suppress the influence of input saturation on the control system, an anti‐windup compensator is used. Finally, rigorous theoretical analyses show the robust convergence of the tracking error via the proposed CFDL and PFDL‐based methods under external disturbances. Simulations verify the superiority of the modified prescribed performance function, DESO, and anti‐windup compensator in the proposed method. Also, the effects of the PFDL‐based method and the CFDL‐based one are compared during the simulation.

Vibration control of a thin rectangular plate subjected to moving masses using an adaptive sliding mode control method

AbstractThis study investigates the vibration control of a plate subjected to moving masses. The plate model reflects the dynamic behavior more accurately than the beam model which is usually used in the existing literature. However, the vibration control of plates subjected to moving masses is also more challenging as more degrees of freedom need to be taken into account. In addition, the measurement of system status and uncertainty problems in practical application is another nodus. In this paper, combining an adaptive sliding‐mode control (ASMC) strategy and a modal coordinate reconstruction (MCR) method, the MCR‐ASMC method is proposed. The MCR method is employed to capture the plate dynamic behavior for feedback to the ASMC. The ASMC strategy realizes vibration control through the adaptive updating of parameters. Numerical results demonstrate the effectiveness of the proposed method and excellent control performance in vibration suppression of moving mass problems.

Improved Fixed-Time Stabilization of Fuzzy Neural Networks With Distributed Delay via Adaptive Sliding Mode Control

This paper investigates fixed-time stabilization of fuzzy neural networks with distributed delay by designing an adaptive sliding mode controller. Firstly, according to stability theory and related inequalities, a new fixed-time stability theorem is put forward, and the settling time is given. In order to stabilize the system, a new integral sliding mode surface is designed, and the corresponding sliding mode control strategy and adaptive sliding mode control strategy are established. Some criteria that can be obtained, and it is shown that the neuronal states of neural networks will arrive at the sliding surface in a fixed time, and then approach zero along the sliding surface. Compared with existing sliding mode control techniques, this work extends the previous related results by choosing different parameters of the controller and the sliding mode manifold to gain various protocols. Finally, two examples are provided to verify the validity of the theorems in this work.

Automatic carrier landing for UAV based on integrated disturbance observer and fault-tolerant control

PurposeAccurate glide path tracking is vital to the automatic carrier landing task of unmanned aerial vehicle (UAV). The purpose of this paper is to develop a reliable flight controller that can simultaneously deal with external disturbance, structure fault and actuator fault.Design/methodology/approachThe automatic carrier landing task is resolved into the glide path tracking problem and attitude tracking problem. The disturbance observer-based adaptive sliding mode control scheme is proposed for system stabilization, disturbance rejection and fault tolerance.FindingsBoth the Lyapunov method and exemplary simulations can prove that the disturbance estimation error and the attitude tracking error converge in finite time in the presence of external disturbances and various faults.Practical implicationsThe presented algorithm is testified by a UAV automatic carrier landing simulation, which shows the potential of practical usage.Originality/valueThe barrier function is introduced to adaptively update both the sliding mode observer gain and sliding mode controller gain, so that the sliding mode surface could converge to a predefined region without overestimation. The proposed flight controller ensures a secure carrier landing task.

Adaptive Sliding Mode Control for Yaw Stability of Four-Wheel Independent-Drive EV Based on the Phase Plane

Aiming at the yaw stability problem of a four-wheel independent-drive electric vehicle (EV) during steering, this paper proposes an adaptive sliding mode control strategy (ASMC) for yaw stability based on the phase plane. The control strategy adopts hierarchical control. The upper layer is the ASMC controllers based on particle swarm optimization (PSO). Aiming at the chattering problem of sliding mode controller, the approach law is designed as the adaptive approach law, which changes with the change of system state by using the adaptive control principle; to minimize the response delay and tracking error, the control system is taken as the object to find a set of optimal parameters for a constant velocity approach rate based on PSO. The middle level is a joint controller, which uses the established β−β˙ phase plane stability region boundary model to control the upper-level controllers jointly. When the vehicle is in the stable region, the ASMC controller for the yaw rate is used to determine the yaw moment; when the vehicle is outside the stable region, the final yaw moment is determined by the ASMC controller for the yaw rate and the ASMC controller for the sideslip angle, to restore the stability of the vehicle. The lower layer is a torque optimal distribution controller, which converts the yaw moment into torque and optimally distributes it to four wheels. Finally, Simulink and CarSim platforms are used for joint simulation. The results prove that the proposed control strategy can effectively reduce the error between the actual and the ideal value of control parameters and improve the vehicle’s stability when steering.

Parameter adaptive sliding mode trajectory tracking strategy with initial value identification for the swing in a hydraulic construction robot

A novel trajectory tracking strategy is developed for a double actuated swing in a hydraulic construction robot. Specifically, a nonlinear hydraulic dynamics model of a double actuated swing is established, and a parameter adaptive sliding mode control strategy is designed to enhance the trajectory tracking performance. When an object is grabbed and unloaded, the moment of inertia of a swing considerably changes, and the performance of the estimation algorithm is generally inadequate. Thus, it is necessary to establish an algorithm to identify the initial value of the moment of inertia of the object. To this end, this paper proposes a novel initial value identification algorithm based on a two-DOF robot gravity force identification method combined with stereo vision information. The performance of the identification algorithm is enhanced. Simulations and experiments are performed to verify the effect of the novel control scheme.