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• We propose a novel adaptive sliding mode based spacecraft attitude controller. • The boundary of the model uncertainty and external disturbance is not required. • Actuator failure and saturation problem is considered by using an RBF network. • A control gains reduction technique is applied to weaken chattering phenomenon. Taking the external disturbance, model uncertainty, actuator failure, and actuator saturation into consideration, this paper investigates the nonlinear fault-tolerant attitude control problem for the spacecraft. First, to deal with the disturbance and uncertainty with unknown boundaries, an adaptive sliding mode control method is proposed to stabilize the state variables of the spacecraft attitude control system. Then the actuator failure and saturation are further considered, and the second spacecraft fault-tolerant attitude controller is derived based on adaptive sliding mode control and radial basis function (RBF) neural networks. The adaptive control gains reduction technique is applied in the design process, which can weaken the chattering phenomenon of the controller to some extent, and the stability of the attitude control system is analyzed through Lyapunov theory. In the proposed controller, model information and external disturbance are not required and only the system states are needed. Furthermore, the boundaries of the model uncertainty, external disturbance, actuator fault and saturation are assumed to be existing but unknown by the proposed controllers. These features make the proposed attitude controllers need few modeling information of the spacecraft, or maintain strong robustness even if the model or external environment occurs significant changes. Finally, numerical simulations demonstrate the great performance of the proposed fault-tolerant attitude control method. [ABSTRACT FROM AUTHOR]

This paper presents an innovative adaptive fractional-order (FO) terminal sliding mode (TSM) controller designed for a 5-degree-of-freedom (5-DOF) upper-limb exoskeleton robot. The primary focus is on addressing the challenges posed by nonlinearities and uncertainties in parameter values. The proposed approach integrates several key elements, including a novel fractional-order non-singular terminal sliding mode (FONSTSM) surface, an exponential reaching law, and the utilization of the extreme learning machine (ELM). This comprehensive strategy guarantees not only finite-time convergence but also robust stability, effectively alleviating the well-known chattering phenomenon. Furthermore, it successfully overcomes the singularity issues typically observed in conventional TSM controllers. The incorporation of the ELM with rectified linear unit (ReLU) activation function enhances robustness by facilitating the estimation of parameters related to the exponential control law. Numerical simulations provide compelling evidence of improved tracking, increased robustness against uncertainties, achievement of finite-time convergence, and notable reductions in control signal oscillations and singularity problems. [ABSTRACT FROM AUTHOR]

Formation control is a fundamental task in the realm of autonomous multiagent systems. To drive a group of agents to maneuver continuously with the desired formation, this paper studies the finite‐time affine formation control problem with disturbances, input constraints and safety guarantee. A non‐singular terminal sliding mode control (NTSMC) is implemented to achieve finite‐time convergence of all followers to their desired positions. Additionally, an auxiliary system is deployed to address input constraints resulting from the physical properties of the affine formation system. To mitigate the impact of lumped disturbances, a finite‐time disturbance observer (FTDO) is employed to estimate the disturbances and compensate for their effects. Based on FTDO, the auxiliary system and the above NTSMC, a finite‐time robust controller is developed as the nominal controller. By modifying the nominal controllers to comply with safety constraints, control barrier functions are employed to ensure the safety of the formation system in obstacle‐filled environment. Finally, the effectiveness and feasibility of this method are validated through simulations and real‐world experiments. [ABSTRACT FROM AUTHOR]

This paper proposes a novel control methodology to achieve fixed-time stabilisation for a class of three-order nonlinear systems based on fast nonsingular terminal sliding mode control. In this research, based on the combination of integral fast nonsingular terminal sliding mode (IFNTSM) surface and fixed-time control theory, a novel backstepping fast nonsingular terminal sliding mode (FNTSM) controller is being studied. The interests of this method are that the presented controller can not only maintain the characteristics of integral fast nonsingular terminal sliding mode control (IFNTSMC) but also has the advantages of fixed time convergence and fast transient response. Piecewise function is introduced to solve the singularity problem caused by negative exponential term. Our control strategy achieves the stabilisation performance within finite convergent time being independent of initial condition. The control scheme is applied to the gyros system with chaotic state and suppress its chaotic phenomenon. The theoretical results are supported by simulation results. [ABSTRACT FROM AUTHOR]

This paper describes a new approach to control stall and surge instabilities in the compressor system by using of finite time backstepping-based adaptive sliding mode method. The most important innovation of this study is to provide a finite time adaptive control method to simultaneously prevent the stall and surge instabilities in a compressor system in the presence of disturbance and uncertainty in the compressor characteristic curve as well as the throttle valve. The disturbance and uncertainty issues are covered by a robust sliding mode control and the gain coefficients of this controller as well as the estimation of uncertain terms are obtained by using the adaptive method. The Lyapunov stability criterion is used to evaluate the finite-time stability of the closed-loop system. The performance of the proposed method is compared with other literature methods through simulation in Matlab. The simulation results show that the proposed controller is better than the existing methods in terms of surge preventing and robustness against uncertainty and disturbance. [ABSTRACT FROM AUTHOR]

The concurrent existence of model uncertainties, external disturbances, and actuator faults in a nonlinear system such as a robotic manipulator can significantly affect the trajectory tracking performance of these systems. Therefore this study is devoted to proposing a control approach based on fixed‐time control theory to improve the trajectory tracking performance of the robotic manipulator in the presence of lumped disturbance, including uncertainties, external disturbances, and actuator faults. The control approach in this paper is designed based on the integration of a fixed‐time adaptive sliding mode observer and a fixed‐time non‐singular fast terminal sliding mode control design strategy. Firstly, a new fixed‐time adaptive sliding mode observer is designed based on fixed‐time theory and adaptive control theory to estimate the lumped disturbance present in the system. Then, using the information from the disturbance observer, the fixed‐time non‐singular fast terminal sliding mode control is devised based on a non‐singular fixed‐time sliding surface and a fixed‐time reaching approach. Furthermore, in the sense of the Lyapunov theorem, through rigorous analysis, it is demonstrated that the tracking errors of the closed‐loop system converge to a small neighbourhood within a fixed time, regardless of the information about the initial conditions of the states of the system. Finally, extensive comparative simulations are performed using the PUMA560 robot to manifest the feasibility and validity of the proposed control strategy in terms of trajectory tracking accuracy and fast convergence in the presence of uncertainties, disturbances, and actuator faults. [ABSTRACT FROM AUTHOR]

This document is an editorial for a special issue of the International Journal of Robust & Nonlinear Control on the topic of time-delay systems. It provides a historical overview of functional differential equations and highlights the contributions of Nikolay Nikolayevich Krasovskii and Aristide Halanay to the field. The special issue includes 21 research papers covering stability, robustness, observer theory, predictors, and delay-based approaches to partial differential equation models. Each paper is briefly described, covering topics such as stabilization of uncertain systems, sampled-data control for nonlinear systems, observer theory for differential delay systems, sensor fault estimation, and control approaches for vehicular platoons. The summaries aim to provide library patrons with a quick understanding of the papers' contents and their relevance to their research interests. [Extracted from the article]

The shearer is an important component of the smart mining workface, and its effective control is a key aspect that guarantees safe and high-efficient production in coal mines. To address the issue of autonomous height adjustment during the shearer's cutting process, a self-adaptive speed control method driven by digital twin technology is proposed. A digital twin-based control architecture for the shearer is first established, which consists of physical and the corresponding virtual entities, as well as reality–virtual interaction between them. Based on the mathematic model formulated for height adjustment system of the shearer, an adaptive fuzzy sliding mode controller (AFSMC) with the displacement estimation is designed for the virtual entity, with the purpose of guiding the operation of the corresponding physical entity. Simulation experiments on MATLAB compares the control performance among the proposed method and four comparative ones, including PID controller, integral sliding mode controller (ISMC), feedback linearization controller (FLC), and fuzzy sliding mode controller (FSMC). The experimental results confirm the effectiveness of the proposed AFSMC. More specifically, its steady-state error is 0.024, the maximum absolute control input is 8.43, and the settling time is 1.74 s. This also proves that the digital twin-based control method enables the precise adaptive height adjustment of the shearer, providing potential reference for the intelligent development of a smart mining workface. [ABSTRACT FROM AUTHOR]

This study proposes two adaptive controllers and applies them to the vibration control of an in-wheel motor vehicle's (electric vehicle) suspension system, in which a semi-active magnetorheological (MR) damper is installed as an actuator. As a suspension model, a nonlinear quarter car is used, providing greater practical feasibility than linear models. In the synthesis of the controller design, the values of the sprung mass, damping coefficient and suspension stiffness are treated as bounded uncertainties. To take into account the uncertainties, both direct and indirect adaptive sliding mode controllers are designed, in which the principal control parameters for the adaptation law are updated using the auto-tune method. To reflect the practical implementation of the proposed controller, only two accelerometers are used, and the rest of the state values are estimated using a Kalman observer. The designed controller is applied to a quarter car suspension model of an in-wheel motor vehicle featuring an MR damper, followed by a performance evaluation considering factors such as ride comfort and road holding. It is demonstrated in this comparative work that the proposed adaptive controllers show superior control performance to the conventional proportional–integral–derivative (PID) controller by reducing the vibration magnitude by 50% and 70% for the first and second modes, respectively. In addition, it is identified that the second mode (wheel mode) of the in-wheel motor vehicle is more sensitive than the first body mode depending on the mass ratio between the sprung and unsprung mass. [ABSTRACT FROM AUTHOR]

A novel combination of three control systems is presented in this paper: an adaptive control system, a type-two fuzzy logic system, and a super-twisting sliding mode control (STSMC) system. This combination was developed at the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity (LARCASE). This controller incorporates two methods to calculate the gains of the switching term in the STSMC utilizing the particle swarm optimization algorithm: (1) adaptive gains and (2) optimized gains. This methodology was applied to a nonlinear model of the Cessna Citation X business jet aircraft generated by the simulation platform developed at the LARCASE in Simulink/MATLAB (R2022b) for aircraft lateral motion. The platform was validated with flight data obtained from a Level-D research aircraft flight simulator manufactured by the CAE (Montreal, Canada). Level D denotes the highest qualification that the FAA issues for research flight simulators. The performances of controllers were evaluated using the turbulence generated by the Dryden model. The simulation results show that this controller can address both turbulence and existing uncertainties. Finally, the controller was validated for 925 flight conditions over the whole flight envelope for a single configuration using both adaptive and optimized gains in switching terms of the STSMC. [ABSTRACT FROM AUTHOR]

In this paper, a fractional adaptive backstepping sliding mode control system based on the Caputo-Fabrizio derivative for a 2-DoF mobile robot manipulator is designed and described. The fractional dynamics of the system are obtained using the Atangana-Baleanu derivative and the Euler-LaGrange formalism, which include external disturbances, parametric uncertainties, and nonholonomic constraints. A fractional sliding mode control strategy is designed for trajectory tracking tasks. In order to compensate for the chattering phenomenon, the proposed controller is combined with a fractional backstepping strategy. Additionally, the Caputo-Fabrizio derivative is introduced to further reduce the chattering effects and improve the driver performance. A fractional adaptive control law is used to cope with the parametric uncertainties, while adding robustness to external disturbances. To further improve system performance, a tracking control strategy based on a fractional neural network is added. For a comparative analysis, the conventional adaptive neural network backstepping sliding mode control is implemented. Numerical simulations are described and discussed to validate the effectiveness of our control system for trajectory tracking tasks under different operating conditions such as trajectory changes and external disturbances. Our proposed control system and its traditional counterpart were tuned using the Cuckoo optimization approach. [ABSTRACT FROM AUTHOR]

Summary This paper proposes a sliding‐mode‐based adaptive boundary control law for stabilizing a class of uncertain diffusion processes affected by a matched disturbance. The matched disturbance is assumed to be uniformly bounded along with its time derivative, whereas the corresponding upper bounding constants are not known. This motivates the use of adaptive control strategies. In addition, the spatially‐varying diffusion coefficient is also uncertain. To achieve asymptotic stability of the plant origin in the L2$$ {L}_2 $$‐sense in the presence of the disturbance, a discontinuous boundary feedback law is proposed where the gain of the discontinuous control term is adjusted according to a gradient‐based adaptation law. A constructive Lyapunov analysis supports the stability properties of the considered closed‐loop system, yielding sufficient convergence conditions in terms of suitable inequalities involving the controllers' tuning parameters. Simulation results are presented to corroborate the theoretical findings. [ABSTRACT FROM AUTHOR]

The operation of the three-phase standalone inverter is affected by many factors, such as heavy changes in load, unbalanced loads, nonlinear loads, system uncertainties and external disturbances. These are critical weaknesses for the control system of the three-phase inverter to reach robust optimal performance. This paper proposes an adaptive optimal sliding mode control (AOSMC) scheme for a three-phase nonlinear uncertain inverter. This AOSMC strategy solves the problems of nonlinear optimization by adaptive dynamic programming, one of the techniques of reinforcement learning, and overcomes the uncertainties and disturbance effects by a disturbance observer–based sliding mode controller. This algorithm uses only one neural network to approximate the critic; therefore, the burden of computation is significantly reduced. Both the weight matrix of the critic network and the disturbance observer are asymptotically stable. The overall system is guaranteed to be ultimately uniformly bounded stable via Lyapunov stable theory. The simulation is conducted to validate the insensitivity of the proposed AOSMC algorithm to working conditions. Also, the competitive results are presented to demonstrate the improvement of the proposed AOSMC scheme in comparison to some other existing controllers. [ABSTRACT FROM AUTHOR]

Photovoltaic inverters are widely utilized in microgrid systems working as the key equipment for converting solar energy into usable electricity. This paper presents a fuzzy sliding mode control (FSMC) method for the photovoltaic inverter in a microgrid. The inverter module uses voltage control to achieve stable AC output voltage. Moreover, to deal with system uncertainty and non-linearity in the photovoltaic inverter, a fuzzy controller was designed to realize real-time adaptation of the gains of the constant term and the reaching term in the sliding mode control law, which serves as a compensating controller for traditional sliding mode control. The gains of the exponential reaching law can be adjusted according to the system state instead of fixed gains, which can effectively reduce the chattering phenomenon and improve the robustness of the photovoltaic microgrid. Finally, the Lyapunov stability theory was used to ensure the stability of the entire control system, achieving a high-performance independent power supply for loads in a microgrid. Simulation results show that the designed control system is more robust to load disturbances and has superior dynamic performance. [ABSTRACT FROM AUTHOR]

While using multirotor UAVs for transport of suspended payloads, there is a need for stability along the desired path, in addition to avoidance of any excessive payload oscillations, and a good level of precision in maintaining the desired path of the vehicle. However, due to the nonlinear and underactuated nature of the system, in addition to the presence of mismatched uncertainties, the development of a control system for this application poses an interesting research problem. This paper proposes a control architecture for a multirotor slung load system by integrating a Multi-Surface Sliding Mode Control, aided by a Radial Basis Function Neural Network, with a Deep Q-Network Reinforcement Learning agent. The former will be used to ensure asymptotic tracking stability, while the latter will be used to suppress payload oscillations. First, we will present the dynamics of a multirotor slung load system, represented here as a quadrotor with a single pendulum load suspended from it. We will then propose a control method in which a multi-surface sliding mode controller, based on an adaptive RBF Neural Network for trajectory tracking of the quadrotor, works in tandem with a Deep Q-Network Reinforcement Learning agent whose reward function aims to suppress the oscillations of the single pendulum slung load. Simulation results demonstrate the effectiveness and potential of the proposed approach in achieving precise and reliable control of multirotor slung load systems. [ABSTRACT FROM AUTHOR]

This paper provides a new sliding mode control (SMC) approach, by which both the nominal and robust stability associated with a trajectory tracking problem for an uncertain robot manipulator are achieved. More precisely, the new control law consists of linear and nonlinear functions of tracking errors, in which the former is for the nominal stability and the latter is to ensure the robust stability of the resulting closed‐loop systems. The nonlinear function can be interpreted as an extended version of conventional SMC approach, and the reaching phase corresponding to a pregiven sliding surface is shown to be completed in a finite time; the tracking errors arrive at the sliding surface in a finite time and do not deviate from it after the arrival. In the sliding phase, the tracking errors are also ensured to converge to the origin. Finally, some simulation results are given to demonstrate both the theoretical validity and practical effectiveness of the proposed control approach. [ABSTRACT FROM AUTHOR]

This paper concerns the problem of asymptotic attitude stabilization for uncertain spacecraft subject to actuator constraints and bounded external disturbances. A simple model‐free saturated robust PD control is proposed within the framework of PD design methodology combining sliding mode control strategy. Asymptotic stabilization stability is proved in terms of Lyapunov's direct method and Barbalat's lemma. Advantages of the proposed control include the easy‐going implementation with simple and intuitive structure and explicit tuning procedure and abilities to guarantee the asymptotic attitude stabilization and bounded disturbance rejection and ensure the actuator constraint is not violated by selecting the control gains a priori. Simulation comparisons demonstrate the improved performance of the proposed approach. [ABSTRACT FROM AUTHOR]

We propose a data-driven, model-free adaptive sliding mode control (MFASMC) approach to address the Haidou-1 ARV under-actuated motion control problem with uncertainties, including external disturbances and parameter perturbations. Firstly, we analyzed the two main difficulties in the motion control of Haidou-1 ARV. Secondly, in order to address these problems, a MFASMC control method was introduced. It is combined by a model-free adaptive control (MFAC) method and a sliding mode control (SMC) method. The main advantage of the MFAC method is that it relies only on the real-time measurement data of an ARV instead of any mathematical modeling information, and the SMC method guarantees the MFAC method's fast convergence and low overshooting. The proposed MFASMC control method can maneuver Haidou-1 ARV cruising at the desired forward speed, heading, and depth, even when the dynamic parameters of the ARV vary widely and external disturbances exist. It also addresses the problem of under-actuated motion control for the Haidou-1 ARV. Finally, the simulation results, including comparisons with a PID method and the MFAC method, demonstrate the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

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Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for robot hands is always an attractive topic in the research community. This is a challenging problem because robot manipulators are complex nonlinear systems and are often subject to fluctuations in loads and external disturbances. This article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller ensures that the positions of the joints track the desired trajectory, synchronize the errors, and significantly reduces chattering. First, the synchronous tracking errors and synchronous sliding surfaces are presented. Second, the synchronous tracking error dynamics are determined. Third, a robust adaptive control law is designed, the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy logic. The built algorithm ensures that the tracking and approximation errors are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results. Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is significantly reduced. [ABSTRACT FROM AUTHOR]

In this article, a dissipativity based discrete time sliding mode controller is proposed for bilateral tele‐operation in presence of communication delays and packet losses. The controllers for both master and slave arm are designed to follow a predefined impedance dynamics with dissipative characteristics. The slave arm controller is designed as a two layered structure. The first layer uses the tracking error between master and slave to create a target velocity profile based on the user defined impedance dynamics. The second layer uses this target velocity profile, slave motion and the contact forces to design a reaching law based discrete time sliding mode controller. A model following reaching law approach is used to design the sliding mode control which alleviates the chattering in the input by removing the impact of the accumulated effects of the past disturbance from the system. Moreover, an adaptive tuning method is used for the switching gain of the sliding mode control so that the controller can be designed even when exact information on the uncertainty bounds are unknown. Numerical simulations are presented for Phantom Omni arm to show the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

An adaptive super-twisting sliding mode control (AST-SMC) is proposed for the power-line inspection (PLI) robot system with two degrees of freedom and single control input underactuated with multiple balances. Firstly, the nonlinear dynamic equation of PLI robot is established, and the model is linearized at the nominal equilibrium point. Secondly, a special transformation is introduced to transform the original input delay system into a delay-free model, and an equilibrium manifold linearization (EML) model is established by using scheduling variables to expand the operating range of the controlled system, as a result of which the disturbance observer control (DOC) is designed to estimate the external disturbance. Thirdly, in order to achieve fast convergence and continuous control, the super-twisting sliding mode control(ST-SMC) method is proposed to decrease chattering in the control law. Finally, it can be verified by Lyapunov stability theory that the system reaches the sliding mode surface in finite time and the trajectory tracking error converges to zero in finite time. The simulation results verify that the combination of DOC and AST-SMC has a optimal disturbance approximation and control convergence ability, clarifying the effectiveness and robustness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper proposes an enhanced and robust tracking control method for the class of uncertain and disturbed affine nonlinear systems. The approach is based on predictive sliding mode control (PSMC) to combine the advantages of sliding mode control (SMC) with those of model predictive control (MPC). The resulting controller offers numerous benefits, including high robustness, quick transient response, finite-time convergence, and robustness against uncertainties and external disturbances. However, a significant limitation of the proposed PSMC is its reliance on prior knowledge of the disturbance and uncertainty bounds. To address this drawback, a sliding mode observer (SMO) is synthesised to identify uncertainties and disturbances. The proposed controller successfully eliminates the chattering effect without compromising robustness and precision. The Lyapunov theory is used to prove the stability of the closed-loop system. The effectiveness of the proposed approach is validated through simulations on a well-known benchmark. [ABSTRACT FROM AUTHOR]

This paper proposes a novel, robust flight control system using adaptive nonlinear sliding mode control for a quadrotor UAV in the presence of parametric uncertainties and aerodynamical disturbances. The proposed control system is based on a proportional derivative sliding surface combined with a non-singular fast terminal sliding mode control to enhance the tracking accuracy and reduce the chattering influence. Moreover, an adaptive mechanism is proposed to approximate the unknown upper limit of external disturbances/uncertainties. The Lyapunov criteria is used to prove the closed-loop stability and calculate the adaptive mechanism. The proposed adaptive PD-NFTSMC (APD-NFTSMC) can cope with the negative influence of modeling uncertainties, external disturbances, and measurement noise, allows null error in the steady state, and solves the chattering problem. Moreover, intensive simulation experiments under various external conditions are carried out to highlight the sovereignty of the developed control approach. Finally, comparisons with some well-known control techniques are performed to show the usefulness, smoothness, and robustness of the proposed APD-NFTSMC strategy. [ABSTRACT FROM AUTHOR]

The tracking control problem of non‐holonomic mobile robot systems has been extensively investigated in the past decades, however, most of the existing control strategies were developed specifically for the fixed‐point tracking. This technical note focuses on the region tracking control for a non‐holonomic mobile robot system with parameter uncertainties in the robot dynamics. With the system decomposition and adaptive control method, some restrictions imposed on the angular and linear velocities of the non‐holonomic mobile robot in recent literature are removed, enabling to track dynamic trajectories with any values of the angular and line velocities. The proposed adaptive control scheme can simultaneously solve both the regulation and region tracking problems of a non‐holonomic mobile robot with one passive wheel and two actuated wheels. By utilizing the designed control laws, the mobile robot system is able to globally reach inside a moving region specified by potential functions whose path can be a circular curve, a straight line, or sinusoidal curve, by using a single adaptive controller. Since the dynamic region can be specified arbitrarily small, the fixed‐point tracking can be regarded as a special case of region tracking studied in this paper. Compared with the traditional fixed‐point tracking, region tracking has more flexibility and better robustness. Numerical results are presented to show the effectiveness of the designed strategy. [ABSTRACT FROM AUTHOR]

This study utilizes the Takagi–Sugeno fuzzy model to represent a subset of nonlinear systems and presents an innovative adaptive approach for optimal dynamic terminal sliding mode control (TSMC). The systems under consideration encompass bounded uncertainties in parameters and actuators, as well as susceptibility to external disturbances. Performance evaluation entails the design of an adaptive terminal sliding surface through a two-step process. Initially, a state feedback gain and controller are developed using Linear Matrix Inequality (LMI) techniques, grounded on H 2 -performance and partial eigenstructure assignment. Dynamic sliding gain is subsequently attained via convex optimization, leveraging the derived state feedback gain and the designed terminal sliding mode (TSM) controller. This approach diverges from conventional methods by incorporating control effort and estimating actuator uncertainty bounds, while also addressing sliding surface and TSM controller design intricacies. The TSM controller is redefined into a strict feedback form, rendering it suitable for addressing output-tracking challenges in nonlinear systems. Comparative simulations validate the effectiveness of the proposed TSM controller, emphasizing its practical applicability. [ABSTRACT FROM AUTHOR]

In this paper, the adaptive finite-time fault-tolerant control (FTC) problem is investigated for uncertain nonlinear strict-feedback systems. The strict-feedback nonlinear system considered in this paper contains unknown nonlinear dynamics and actuator faults (both lock-in-place and loss of effectiveness). In this control process, adaptive laws are used to approximate unknown nonlinear functions. By using the sliding mode control technique and combining it with the adaptive backstepping control design, an adaptive terminal sliding mode FTC scheme is proposed. It is proved that the closed-loop system is finite-time stable and that the system output can track a given reference signal. Simulation results further show the efficacy of the designed control approach. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive dynamic surface sliding mode control technique to address the issue of system parameter changes in permanent magnet synchronous motor (PMSM) position servo systems. The proposed method involves adopting a linear parameter varying (LPV) observer-based parameter identification algorithm and adaptive control technique. Initially, a mathematical model of the PMSM is established, and the system parameters are divided into nominal and perturbation values. This allows for the reconstruction of the system model into a state space equation that incorporates the unknown perturbation parameters. To accurately estimate these unknown parameters, an LPV observer is designed based on the reconstructed model. Additionally, an adaptive dynamic surface sliding mode control technique is explored to achieve the desired tracking performance. Meanwhile, an exponential reaching law is introduced to expedite the dynamic behavior of the system and mitigate chattering. Finally, a suitable Lyapunov function is selected to ensure the overall stability of the system. The simulation results demonstrate the effectiveness of the parameter identification and control algorithm in achieving good identification and tracking control ability for PMSM systems. [ABSTRACT FROM AUTHOR]

Aiming at the sensitivity problems of uncertain factors such as parameter variation, external disturbance and friction for the permanent magnet synchronous motor control system of electric vehicle, a fractional order complementary non-singular terminal sliding mode control method based on neural network is proposed. The mathematical model of permanent magnet synchronous motor with uncertain factors was established. The sliding mode controller was designed by combining the generalized sliding mode surface and the complementary sliding mode surface, which shortened the arrival time from the state trajectory to sliding mode surface. The fractional calculus operator with filtering characteristics was used to improve the position tracking accuracy and reduce the chattering. As for the variety of uncertain disturbances, the neural network was used to estimate the system total uncertainty and compensate online to further improve the dynamic response ability and anti-interference ability. Finally, the simulation results verify the effectiveness and feasibility of the proposed method, which can provide theoretical and technical support for improving the control accuracy of permanent magnet synchronous motor and the development of electric vehicles. [ABSTRACT FROM AUTHOR]

To handle the disturbances and uncertainties issue in the control of the stabilized platform toolface angle, a composite control approach based on a backstepping sliding mode control (BSMC) method with a nonlinear disturbance observer (NDO) is proposed. First, a nonlinear mathematical model of the stabilized platform is established, and the NDO is employed to observe and compensate for the external disturbance. Then, the BSMC control approach based on the nonlinear mathematical model is designed to improve the robustness of the stabilized platform control system. The asymptotic stability of the designed controller and NDO convergence are mathematically verified using the Lyapunov theory. Furthermore, to address the dead zone torque caused by mechanical friction on the stabilized platform, which could lead to instability in the toolface angle, a novel dead zone torque estimation algorithm is presented. Finally, in comparison with other advanced control methods, simulation results show the superiority and robustness of the proposed scheme under complex disturbances from the downhole environment. And drilling simulation experiment results are provided to validate the robustness and adaptivity of the proposed method. [ABSTRACT FROM AUTHOR]

Robot manipulators as an indispensable part of automatic operation are becoming increasingly important in intelligent manufacturing systems, such as grinding and assembly. Although control methods of robot manipulators have been extensively studied, high-precision robots still face new challenges from uncertainties caused by changes in the environment and enhancement of interference. As a consequence, the neural network-based observer is utilized to reduce the influence of uncertainties and external disturbances. In this work, a new kind of nonlinear disturbance observer is designed which could well function with observed states. To improve the control efficiency and response characteristic, a kind of new integral sliding manifold is devised and the control input is generated via backstepping techniques. The stability is proved with Lyapunov theory, and the experimental results are given to demonstrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

The widespread use of wheeled mobile robots (WMRs) in many fields has created new challenges. A critical issue is wheel slip, which, if not accurately determined and controlled, causes instability and deviation from the robot's path. In this paper, an intelligent approach for estimating the longitudinal and lateral slip of wheels is proposed that can effectively compensate for the negative effects of slippage. The proposed algorithm relies on three regression networks to estimate the longitudinal slip ratio of the right and left wheels and sideslip angle on terrains with different friction coefficients. The datasets collected during tests on different surfaces with various maneuvers are used to train the artificial neural networks (ANNs). A developed dynamic model of a WMR considering wheel slip and modified traction force is presented. The adaptive robust controller, based on sliding mode control (SMC), is introduced to deal with the problems related to slipping, unknown uncertainties, and disturbances. The simulation results demonstrate that the presented controller has better performance than SMC in handling external disturbances and uncertainties, which leads to reduction in tracking error and faster convergence to zero. The proposed controller with an intelligent slip estimator, has been applied to a four-wheel mobile robot to demonstrate its effectiveness and feasibility. The high accuracy of slip estimation in the mentioned intelligent algorithm has resulted in the presented method being on average 26% more effective in reducing the tracking error than the control method without slip compensation in each test for circular trajectory. • Developing a dynamic model of WMR using modified traction force. • Proposing slip estimator based on an intelligent learning for both longitudinal and lateral slip. • Eliminating the time delay in slip estimation and compensating for its effect in the same time step by predicting the slip amount. • Improved robot performance in trajectory tracking on slippery surfaces. [ABSTRACT FROM AUTHOR]

To improve the transient response, accuracy and robustness of trajectory tracking control for cable-driven continuum robots (CDCRs), a recursive integral terminal sliding mode control combined with an adaptive disturbance observer (ADO-RITSMC) is proposed. The recursive integral terminal sliding mode control (RITSMC) guarantees fast transient response and high tracking accuracy with a fast zero convergence of the tracking error without chattering. To attenuate the effect of uncertain dynamics, an adaptive disturbance observer (ADO) is constructed to derive uncertain dynamics. Particularly, an improved grey wolf optimizer (IGWO) is merged into the ADO to enhance the estimating accuracy of uncertain dynamic factors. Simulation and experiment results demonstrate the superiority of the ADO-RITSMC in enabling fast transient response, high accuracy and strong robustness of trajectory tracking control. • The RITSMC achieves a fast zero convergence and high-precision trajectory tracking control without chattering. • Assigning a starting value for the integral term of the RISMC function to improve the transient response of the controller. • An ADO is designed to estimate uncertain dynamic factors and compensate for the control input. • An improved grey wolf optimizer (IGWO) is introduced into ADO for more accurate estimation of uncertain dynamic factors. [ABSTRACT FROM AUTHOR]

This article presents an observer-based adaptive sliding mode controller for a fully-actuated hexacopter unmanned aerial vehicle, designed for trajectory tracking in a perturbed environment while carrying a cable-suspended payload. Based on the unavailability of a payload swing sensor, an extended high-gain observer is designed to provide full-state and disturbance estimation including payload motion. Such disturbances are compensated into the control loop to dampen the oscillations, thus improving the flight performance of the hexacopter driven by the adaptive control, providing robustness against bounded perturbations and chattering reduction. The stability analysis of the observer-based controller is guaranteed through Lyapunov theory. Simulations using a multibody emulator demonstrate time reduction in payload dampening while controlling the aircraft trajectory, compared to a feedback regulation-based adaptive controller. • An observer-based adaptive control is designed for UAV payload swing reduction. • The observer provides swing estimation without using additional sensor. • The control scheme provides robustness to disturbances and finite-time convergence. • The closed-loop stability of the observer-based control is proven by Lyapunov theory. • Simulations show the performance of the proposal for UAV tracking and swing damping. [ABSTRACT FROM AUTHOR]

This article introduces a new fault-tolerant control method based on type-2 fuzzy systems with PID fast terminal sliding mode control. By integrating the advantages of proportional-integral-derivative (PID) control with fast terminal sliding mode (FTSM) control, a novel proportional-integral-derivative fast terminal sliding mode (PID-FTSM) is developed to accelerate convergence and decrease steady-state error. To provide outstanding fault tolerant control performance and approximation of system uncertainties, a type-2 fuzzy logical switching approach law eliminates the chattering phenomenon and reduce the need of prior knowledge without affecting the system's robustness. The overall stability of the system is verified using the Lyapunov function. Finally, several experiments demonstrate that the suggested technique outperforms alternatives. [ABSTRACT FROM AUTHOR]

This work introduces a novel adaptive fixed-time control strategy for nonlinear systems subject to external disturbances. The focus pertains to the introduction of the fixed-time terminal sliding mode control (FxSMC) technique. The proposed scheme exhibits rapid convergence, chatter-free and smooth control inputs, and stability within a fixed time. The utilization of an adaptive methodology in combination with the FxSMC yields the proposed strategy. This approach is employed to address the dynamic system in the presence of external disturbances. The results obtained from the Lyapunov analysis will provide insights into the stability of the closed-loop system in a fixed time. In the end, the simulation results are presented in order to assess and demonstrate the effectiveness of the methodology. [ABSTRACT FROM AUTHOR]

This paper is concerned with the predefined-time exact sliding mode control issue of a class of high-order uncertain nonlinear systems with disturbances. The proposed control scheme is composed of a predefined-time exact disturbance observer and a two-stage predefined-time exact sliding mode controller. The disturbance observer can estimate the system disturbances accurately within an arbitrary predefined observation time, and the time can be set as the handover time between two control stages. The classic sliding mode controller guarantees bounded system states in the first control stage. Then, a predefined-time sliding mode controller is designed based on time-varying tuning function, regulating the system states to exact zero within a final predefined settling time in the second stage. It is shown that the control input signal is always chattering-free with respect to time. The effectiveness and superiority of the proposed control scheme is demonstrated with simulation examples. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This article proposes a novel fixed‐time integral sliding mode controller for admittance control to enhance physical human‐robot collaboration. The proposed method combines the benefits of compliance to external forces of admittance control and high robustness to uncertainties of integral sliding mode control (ISMC), such that the system can collaborate with a human partner in an uncertain environment effectively. First, a fixed‐time sliding surface is applied in the ISMC to make the tracking error of the system converge within a fixed time regardless of the initial condition. Then, a fixed‐time backstepping controller (BSP) is integrated into the ISMC as the nominal controller to realize global fixed‐time convergence. Furthermore, to overcome the singularity problem, a nonsingular fixed‐time sliding surface is designed and integrated into the controller, which is useful for practical application. Finally, the proposed controller is validated for a two‐link robot manipulator with uncertainties and external human forces. The results show that the proposed controller is superior in the sense of both tracking error and convergence time, and at the same time, can comply with human motion in a shared workspace. [ABSTRACT FROM AUTHOR]

This paper presents an integrated guidance and control design for the homing missiles with the radome error compensation to address the guidance problems caused by radome. Firstly, a mathematics model of the integrated guidance and control system with the compensation for the radome error is built by integrating the missile dynamics and the engagement kinematics between the missile and ground target on the longitudinal motion. Secondly, the model is transformed into a normal form by nonlinear coordinate transformation because the system is a time-varying system with mismatched uncertainties. Thirdly, an adaptive control law of the system is designed by adopting the sliding mode control theory, and the stability of the closed-loop system is also conducted. Finally, the simulation proves that the proposed integrated guidance and control scheme can effectively compensate for the radome error and ensure the hit-to-kill attack to the target. [ABSTRACT FROM AUTHOR]

In this article, we address the disturbance rejection problem for linear plants with delayed measured output. The output delay is allowed to be time‐varying and of arbitrary duration. The disturbances that may represent actuator faults are generated by an exogenous dynamic system and can be matched or unmatched. A predictor–based observer is designed via the PDE–backstepping (Partial Differential Equation–backstepping) method so that an estimate of the current state vector, as well as that of unmeasured disturbance, can be obtained. These estimates are used in to regulate the output and reject the disturbance by output feedback sliding mode control. In addition, a solution for finite‐time disturbance rejection (rather than exponential only) is also introduced when the sensor delay is constant. Numerical examples illustrate the performance and robustness of the both proposed predictor‐feedback control systems. [ABSTRACT FROM AUTHOR]

In this work, an integral-type terminal sliding mode (TSM) controller with an asymptotic disturbance observer is developed. The proposed controller can be applied to a class of uncertain integrator systems with unknown external disturbances. In addition, the chattering phenomenon and the singularity problem in traditional TSM control and the influence of unknown external disturbances on the system are taken into consideration. For unknown external disturbances in practical applications, a disturbance observer with asymptotic estimation performance is constructed. Thus, the control strategy is developed to ensure chattering-free and eliminate the singularity problem. By comparing with the traditional TSM control, we expect to synthesize a more efficient chattering-free sliding mode controller. The integral-type TSM transforms the discontinuous sign function into the continuous smooth function. Furthermore, the proposed control algorithm can accurately compensate for the external unknown disturbance and exhibits better robustness. Finally, the simulation results demonstrate the effectiveness of the controller and the stability of the whole closed-loop system is strictly proved. [ABSTRACT FROM AUTHOR]

In order to describe and solve chaotic yawing in straight-line navigation, taking large tanker Davis Sea as an example, the yawing model and corresponding high-gain adaptive controller is established. Chaotic yawing is proved to exist. Mathematical analysis indicates the error of the controlled system is globally ultimately bounded. Simulation results show the proposed control law is effective and robust to model perturbation. Compared with sliding mode control, the accuracy of proposed method is 69.9% better and the control energy consumption is 32.6% smaller. [ABSTRACT FROM AUTHOR]

This document provides brief biographical information about three individuals involved in the field of mathematics and systems science. The first individual is a professor at the ISS Academy of Mathematics and Systems Science, CAS, with research interests in system modeling, adaptive control, stochastic systems, and multi-agent systems. The second individual is a professor at Beijing Institute of Technology, specializing in adaptive control, quantized control, multi-agent systems control, and their applications to aircraft control systems. The third individual is a Ph.D. student at the Academy of Mathematics and Systems Science, with research interests in quantized control, adaptive control, and sparse identification. [Extracted from the article]

To enhance the anti-inertia disturbance ability of permanent magnet synchronous motor (PMSM) speed system, an adaptive sliding mode control with inertia identification is proposed. A novel sliding mode control (NSMC) based on a new reaching law coupled with model reference adaptive system (MRAS) inertia identification is realized the adaptive control, named MRAS+NSMC. In the NSMC construct process, an integral sliding mode surface and a variable speed reaching law are introduced to avoid speed differentiation and improve dynamics, respectively. And the new reaching law imported a successive sigmoid(s) to replace the traditional sign(s) to suppress chattering phenomena. For the problem that the performance deteriorated by rotational inertia variation caused by load changes, the inertia is estimated in real time according to the MRAS theory, and the identification value is updated to the NSMC controller to realize adaptive MRAS+NSMC speed control. Experimental results show that the proposed adaptive MRAS+NSMC control has a faster speed response, and the speed response time is reduced from 85 to 49 ms compared with conventional SMC control. In addition, it has strong robustness to inertia disturbances and high speed tracking accuracy. Compared with conventional SMC, the speed tracking accuracy of proposed MRAS+NSMC is increased from 12% to 4%. This makes the proposed MRAS+NSMC control has great potential practical significance for speed control of PMSM. [ABSTRACT FROM AUTHOR]

This paper develops a Fuzzy Adaptive Backstepping Control (FABC) and a Fuzzy Adaptive Backstepping Sliding Mode Control (FABSMC) for Single-Input Single-Output (SISO) nonlinear-systems with unmeasured states. The proposed adaptive schemes are fully compared. Thus, the Fuzzy Type-2 (FT2) concept and the High-Order Integral-Chain Differentiator (HOICD) are used as two universal approximators. Indeed, the first one is employed to approximate the nonlinear system model's and the second one to estimate the unknown states. Special attention is paid for the used approximators robustness under unmodeled dynamics, parameter variations and process noise. It should be noted that the asymptotic stability of both the fuzzy adaptive controls and the observer convergence for each scheme have been proved. In addition, the employed schemes have been simulated on a two-tank coupled nonlinear system. Thus, from simulation results, we can prove that the proposed methods guarantee that all signals for closed loop systems are both regular and bounded. Specifically, it can be shown that the performances of the proposed Fuzzy Interval Type-2 (FIT2) schemes are significantly improved compared with Fuzzy Type-1 (FT1) schemes in presence of external disturbances. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper focuses on the speed control of a permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and external disturbances. Conventional sliding mode control (CSMC) can only converge asymptotically in the infinite domain and will cause unacceptable sliding mode chattering. To improve the performance of the PMSM speed loop in terms of response speed, tracking accuracy, and robustness, a hybrid control strategy for a fixed-time-convergent sliding mode controller (FSMC) with a fixed-time-convergent sliding mode observer (FSMO) is proposed for PMSM speed regulation using the fixed-time control theory. Firstly, the FSMC is proposed to improve the convergence speed and robustness of the speed loop, which can converge to the origin within a fixed time independent of the initial conditions. Then, the FSMO is used as a compensator to further enhance the robustness of the speed loop and attenuate sliding mode chattering. Finally, simulation and experimental results show that the proposed method can effectively improve the dynamic performance and robustness of the PMSM speed control system. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of attitude stabilization of a quadrotor unmanned aerial vehicle (UAV) in the presence of parametric uncertainty, modeling uncertainty, control input saturation and external disturbance. A fuzzy logic system (FLS) is used to approximate unknown nonlinear function, which consists of parametric uncertainty and modeling uncertainty of quadrotor system. To compensate for control input saturation, a second-order auxiliary system is constructed to reduce the amplitude of the designed control signal. Furthermore, two adaptive fuzzy sliding mode control techniques are proposed to achieve attitude tracking of a quadrotor, where two disturbance rejection strategies are developed. The stability of closed-loop system is proved by Lyapunov theory. The defined tracking error is guaranteed to converge to a neighborhood of zero and the transient bound of real tracking error is derived. The simulation is carried out to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

An adaptive finite-time composite control (AFTCC) scheme is designed for the pitch angle trajectory tracking control of Underwater Glider (UG) with actuator physical constraints, uncertain dynamics and external disturbances. Firstly, a novel nonsingular fast terminal sliding mode control (NFTSMC) law is designed that can avoid singular problems, significantly reduce chattering, and achieve finite-time convergence of the system states. Secondly, a novel fixed-time extended state observer (FxTESO) is established to estimate the pitch angular velocity and lumped disturbances within a fixed time. Furthermore, a novel adaptive fixed-time saturation compensation system (AFxTSCS) is proposed to mitigate the effect caused by actuator saturation, and it can adjust the parameter adaptively when the actuator is in saturation or out of saturation. Finally, the AFTCC scheme, which is based on the NFTSMC framework and combines FxTESO and AFxTSCS, is designed to achieve the pitch angle trajectory tracking of UG, and the finite-time convergence of the whole closed-loop system is proved by the Lyapunov stability theory, and the simulations verify the availability and superiority of the proposed AFTCC scheme. • A simplified underwater glider model is established. • A novel FxTESO is constructed to estimate lumped disturbances. • A novel AFxTSCS is designed to mitigate the effect caused by actuator saturation. • An AFTCC scheme is designed to track the pitch angle of underwater glider. [ABSTRACT FROM AUTHOR]