Adaptive Sliding Mode Control Research Articles

Tracking control of a flexible‐link manipulator based on an improved barrier function adaptive sliding mode

AbstractIn this paper, a novel controller designed for robust tracking control of a flexible‐link manipulator operating in the presence of parameter uncertainties and external disturbances within the joint space is introduced. The proposed controller employs an adaptive sliding mode control approach, incorporating an improved barrier function, to ensure that trajectory errors remain within predefined performance bounds. This design enhances the tracking performance without overestimating control‐switching gains. Additionally, a fixed‐time adaptive sliding mode control, featuring a rapid nonsingular terminal sliding mode variable, is introduced to expedite the convergence rate of the system state during the initial stages. The efficacy of the proposed control scheme is established through the Lyapunov method, demonstrating finite‐time convergence of the trajectory error to a specified neighborhood of zero. Experimental validation on a flexible‐link system supports the effectiveness and advantages of the proposed control strategy, as evidenced via comparisons with two existing adaptive control schemes.

Iterative Learning with Adaptive Sliding Mode Control for Trajectory Tracking of Fast Tool Servo Systems

To address the tracking control problem of the periodic motion fast tool servo system (FTS), we propose a control method that combines adaptive sliding mode control with closed-loop iterative learning control. Adaptive sliding mode control enhances the system’s robustness to external non-repetitive disturbances, and exponential gain iterative learning control compensates for the influence of periodic disturbances such as cutting force. The experimental results show that the proposed iterative learning controller based on adaptive sliding mode control can effectively eliminate the influence of various interference factors, achieve accurate tracking of the FTS system’s motion trajectory within a limited number of iterations, and ensure the stability of the system, which has the advantages of a fast convergence speed, high tracking accuracy, and strong robustness.

An Attitude Adaptive Integral Sliding Mode Control Algorithm with Disturbance Observer for Microsatellites to Track High-Speed Moving Targets

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution, narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.03°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

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.

Sliding mode control for nonlinear semi-Markov jump systems with cyber attacks via fuzzy logic

This paper studies the security control problem of semi-Markov jump systems. First, the parameter uncertainty, the time-varying delay, the nonlinear function and the cyber attack are considered in the system. Second, the nonlinear function is linearized by the fuzzy logic rule. A sliding mode surface is designed to obtain an equivalent controller and get a sliding mode dynamic system. By constructing Lyapunov functions of the mode dependence, a sufficient condition for H∞ asymptotic stability of the system is obtained. Then, an adaptive sliding mode controller is established, and the original system reaches the sliding mode surface in a finite time. Finally, two examples verify the correctness and practicality of the proposed theory.

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.

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.

A hovering micro autonomous underwater vehicle with integrated control and positioning system

Autonomous underwater vehicle (AUV) is currently the mainstream equipment for ocean exploration due to its long endurance and large operating range. However, the torpedo profile of traditional AUVs limits their maneuverability and hovering capabilities. This hinders the application and popularity of AUVs in near-seabed operations and accurate detection in small areas. This paper presents a novel disc-shaped micro AUV characterized by using a multi-core heterogeneous architecture to integrate control and positioning systems to obtain a lightweight design with complete functionality. Through the special structure and adaptive sliding mode controller, it can achieve high maneuvering navigation and stable hovering under different working conditions. A passive inverted ultra-short baseline (piUSBL) underwater positioning system is developed to provide accurate and instantaneous underwater position at low cost and power consumption. Field experiments, including special circular cruising and acoustic docking, were conducted in an open-water environment. The experimental results show that this vehicle has a depth control accuracy of 5 cm and a heading control accuracy of 3°, which well proves that this prototype can carry out accurate detection in a small range. In addition, this vehicle has a diameter of only 42 cm, a height of 23 cm, and a weight of 14 kg, making it easy to deploy and recover. To the best of our knowledge, this is the first AUV to be successfully tested in the field using a multi-core heterogeneous architecture with such small size and light weight.

Finite‐time sliding mode fault‐tolerant control of PEM fuel cell air supply system

AbstractProton exchange membrane (PEM) fuel cell air supply system is primarily responsible for delivering air to the fuel cell at a specific stoichiometric ratio for chemical reaction. The stoichiometric ratio will be impacted by the sudden change in load and system failure. Under the aforementioned circumstances, precise and timely air supply regulation is required to avoid irreparable PEM damage. In order to enhance the robustness and performance of the fuel cell, a cascaded finite time sliding mode fault‐tolerant control method is proposed for the air supply system of PEMFC. The control objective is to adjust the oxygen excess ratio at the cathode flow field, which can avoid the occurrence of oxygen starvation in the PEM fuel cell when the load current changes rapidly or when fault occurs. A cascaded controller structure is introduced, where, in the inner loop, an adaptive sliding mode controller is designed to reconstruct fault signal and track the optimal output trajectory and, in the outer loop, a finite‐time observer is employed to obtain the expected output trajectory. The proposed control scheme is capable of fault‐tolerant tracking of the optimal oxygen excess ratio within finite time. The effectiveness of proposed fault‐tolerant control algorithm is verified through hardware‐in‐the‐loop (HIL) studies.

Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment.

This study develops an adaptive sliding mode control approach for a drilling tool attitude adjustment system, aiming at solving the problems of model uncertainties and insufficient ability of disturbance suppression during the regulation behavior. To further improve the performance of the position-tracking loop in terms of response time, tracking accuracy, and robustness, a state observer based on an improved radial basis function is designed to approximate the model uncertainties, a valve dead-zone compensate controller is used to reduce control deviation, an adaptive sliding mode controller is designed to improve the position-tracking precision and attenuate sliding mode chattering. Finally, simulation and experimental results are carried out to verify the observability of the model uncertainties and position-tracking errors of the drilling tool attitude adjustment system, which can effectively improve the position-tracking performance and robustness of the drilling tool attitude adjustment system.

Enhancing pressure control of low-friction pneumatic actuator with eddy current damper via valve dead-zone compensation

This article addresses the high-performance pressure control of a pneumatic actuator that incorporates an air-bearing piston and an eddy current damper (ECD). After optimizing the pneumatic actuator, achieving precise pressure control relies on maintaining an accurate and stable airflow through the control valve. A terminal sliding mode adaptive control method (TSMAC) is proposed, proficiently integrating considerations for dead zone nonlinearities in the proportional valve and the effects of unmodeled disturbances in the pneumatic actuator. Using the opening area of the proportional valve as the input to the pneumatic system greatly simplifies the control process and reduces the workload required for valve parameter calibration. The Lyapunov-based stability analysis demonstrates that excellent asymptotic output tracking can be achieved with low steady-state error simply by knowing the boundaries of the valve opening area. The control effect of the proposed control strategy is compared with an adaptive backstepping sliding mode control method based on a linearly fitted proportional valve model on an established constant pressure control test bench. Experimental results under various loads and operating conditions illustrate the effectiveness of the proposed approach.

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.

Event-triggered adaptive sliding mode control design for a class of uncertain linear systems

Event-triggered adaptive sliding mode control design for a class of uncertain linear systems

Event‐triggered based finite‐frequency control for vehicle electrohydraulic suspension with force tracking

AbstractThis study investigates the problem of event‐triggered based finite‐frequency control for vehicle electrohydraulic suspensions with force tracking. A novel hierarchical control methodology is proposed by designing event‐triggered finite frequency and active force tracking controllers to improve the suspension performance. In practical application, active suspension system can be constructed as the network control system under consideration of the electrohydraulic actuator's nonlinear dynamics and parametric uncertainties, and in‐vehicle network delay in a unified framework. Then, due to the more sensitiveness of the human body to vertical vibrations in 4–8 Hz and limited in‐vehicle network communication resource, an event‐triggered finite frequency controller is developed based on the generalized KYP lemma and Lyapunov stability theory. The triggered condition is designed for the network control system with in‐vehicle network delay. Other physical constraints including suspension working space, tire dynamic load and actuator saturation are also introduced in this controller design. It can generate the target force to satisfy suspension performance requirements under each triggered instant period. Furthermore, since the nonlinearity and uncertainty always exist in the electrohydraulic actuator, a filter‐based adaptive sliding mode control method is employed to design the active force tracking controller. It can precisely drive electrohydraulic actuator to track the target constant force generated by event‐triggered finite frequency controller. Finally, the results validate the effectiveness and saving communication resource capability of the proposed control methodology.

Adaptive fuzzy-neural network effectively disturbance compensate in sliding mode control for dual arm robot

In this study, an Adaptive Backstepping Sliding Mode Controller (ABSMC) is introduced based on the Radial Basis Function (RBF) neural network and a fuzzy logic modifier. The proposed method is used to control a Dual-Arm Robot (DAR) – a nonlinear structure with unstable parameters and external disturbances. The control aims to track the motion trajectory of both arms in the flat surface coordinate within a short time, maintaining stability, and ensuring that the tracking error converges in finite time, especially when influenced by unforeseen external disturbances. The nonlinear Backstepping Sliding Mode Control (BSMC) is effective in trajectory tracking control; however, undesired phenomena may occur if there are uncertain disturbances affecting the system or model parameters change. It is proposed to use a neural network to estimate a nonlinear function to handle unknown uncertainties of the system. The neural network parameters can be adaptively adjusted to optimal values through adaptation rules derived from Lyapunov's theorem. Additionally, fuzzy logic theory is also employed to adjust the controller parameters to accommodate changes or unexpected impacts. The performance of the Fuzzy Neural Network Backstepping Sliding Mode Control (FNN-BSMC) is evaluated through simulation results using Matlab/Simulink software. Two simulation cases are conducted: the first case assumes stable model parameters without uncertain disturbances affecting the joints, while the second case considers a model with changing parameters and disturbances. Simulation results demonstrate the effective adaptability of the proposed method when the system model is affected by various types of uncertainties from the environment

An adaptive predefined time sliding mode control for uncertain nonlinear cyber-physical servo system under cyber attacks

Malicious attacks are often inevitable in cyber-physical systems (CPS). Accuracy in Cyber physical system for position tracking of servos is the major concern now a days. In high precision industrial automation, it is very hard to achieve accuracy in tracking especially under malicious cyber-attacks, control saturations, parametric perturbations and external disturbances. In this paper, we have designed a novel predefined time (PDT) convergence sliding mode adaptive controller (PTCSMAC) for such kind of cyber physical control system. Main key feature of our control is to cope these challenges that are posed by CPS systems such as parameter perturbation, control saturation, and cyber-attacks and the whole system then upgrade to a third-order system to facilitate adaptive control law. Then, we present an adaptive controller based on the novel PDT convergent sliding mode surface (SMS) combined with a modified weight updated Extreme Learning Machine (ELM) which is used to approximate the uncertain part of the system. Another significant advantage of our proposed control approach is that it does not require detailed model information, guaranteeing robust performance even when the system model is uncertain. Additionally, our proposed PTCSMAC controller is nonsingular regardless of initial conditions, and is capable of eradicating the possibility of singularity problems, which are frequently a concern in numerous CPS control systems. Finally, we have verified our designed PTCSMAC control law through rigorous simulations on CPS seeker servo positioning system and compared the robustness and performance of different existing techniques.

Design and position-tracking control of a flexible joint based on the tendon-sheath mechanism

In this study, a flexible joint comprising active and passive driving modes was designed based on the tendon-sheath mechanism. Further, angle sensors and series elastomers (SE) were integrated inside the joint to produce a compact and flexible structure. First, a model of the flexible joint was established based on the involved stiffness relation, and this model was validated using the dSPACE system. Next, to respond to the low control accuracy and poor anti-interference ability of the flexible joints, a sliding-mode controller (SMC) was designed to facilitate the precise position control, as well as achieve improved robustness. However, the flexible joint was prone to considerable tremors when the overall system was subjected to a large load mass. Therefore, a fuzzy-modified adaptive SMC (FMASMC), which adaptively adjusts the SMC parameters, was designed based on the historical-state data of the system. This control method could suppress the trembling phenomenon of the system while improving its control accuracy. Finally, it was experimentally verified that the compliant joint could achieve the expected functions. Compared with the proportional–integral–derivative (PID) and SMC control algorithms, the FMASMC algorithm could effectively overcome the tremors of the compliant actuation system and improve its control accuracy; moreover, it is also suitable for controlling other compliant joints.

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 sliding mode control of robotic manipulator based on reinforcement learning

AbstractRobotic manipulators usually exhibit time‐varying, nonlinear, and coupled dynamics due to the parameter perturbations, disturbances, and other uncertainties. Traditional control algorithms typically do not possess parameters' self‐adaptive learning ability, limiting the tracking performance of the robot. In order to address these issues, an adaptive sliding mode control method based on reinforcement learning (ASMRL) is proposed in this paper, where a proportional–integral sliding mode (PISM) controller is used to address the nonlinear problem in the system, and deep deterministic policy gradient (DDPG) agent is adopted to conduct the parameters' learning of the PISM controller using its adaptive characteristics and the autonomous learning ability. The simulation results illustrate that the proposed method can effectively achieve better tracking performance compared with two other control methods, demonstrating the effectiveness of the proposed approach.

Adaptive Dual-Layer Sliding Mode Control for Ball on Plate System Driven by Shape Memory Alloy Wire

Adaptive Dual-Layer Sliding Mode Control for Ball on Plate System Driven by Shape Memory Alloy Wire