Adaptive Finite-time Control Research Articles

Distributed adaptive finite-time fault-tolerant cooperative control of heterogeneous multi-agent systems with saturation and disturbances

In this paper, the issue of distributed adaptive finite-time fault-tolerant cooperative control (FT-FTCC) problem is investigated for multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with unknown parameter uncertainties, actuator faults, input saturation and external disturbances. Starting from the dynamic models of the UAVs and UGVs, an unified control model is presented. Then, a sliding-mode estimator is presented to estimate the position of the leader for the followers which only uses the information from neighbours. Next, a distributed adaptive FT-FTCC scheme, which can also deal with the uncertainties, actuator faults, input saturation and disturbances, is proposed by utilising disturbance observers and neural networks. Based on Lyapunov function approach, the tracking errors of all followers subject to the pre-defined desired positions are uniformly ultimately bounded. Finally, simulations are given to validate the efficiency of the developed FT-FTCC scheme.

Event-triggered adaptive finite-time synchronization control for dual-motor servo systems with uncertainties and torque disturbance

Event-triggered adaptive finite-time synchronization control for dual-motor servo systems with uncertainties and torque disturbance

Fuzzy Observer-Based Finite-Time Adaptive Formation Control for Multiple QUAVs With Malicious Attacks

Fuzzy Observer-Based Finite-Time Adaptive Formation Control for Multiple QUAVs With Malicious Attacks

Distributed two-channel dynamic event-triggered adaptive finite-time fault-tolerant containment control for multi-leader UAV formations

This paper addresses the distributed adaptive finite-time containment control problem in multi-leader UAV formations with actuator failures, limited communication, and external disturbances. A two-channel dynamic event-triggered strategy based on adaptive and sliding mode control is proposed as a containment control scheme, which solves the contradiction between the need to include containment error in the continuous term of the sliding mode surface in the adaptive law and the discontinuity of the communication between neighboring subsystems (follower UAVs) by constructing intermediate variables. Unlike the traditional event triggering condition that can only be applied to asymptotically convergent systems, the dynamic triggering condition designed in this paper, based on auxiliary variables, hyperbolic tangent function, and adaptive techniques, realizes finite-time convergence during the adjustment of the system and sets a more reasonable lower limit for the triggering thresholds, thus further reducing the communication frequency and ensuring the finite-time convergence of the system. The stability of the closed-loop system can be proved by the Lyapunov theorem. Zeno behavior can be avoided. The simulation results verify the effectiveness of the developed control algorithm.

Adaptive finite-time event-triggered control for nonlinear systems with quantized input and periodic disturbances

Adaptive finite-time event-triggered control for nonlinear systems with quantized input and periodic disturbances

Finite-Time Adaptive Control for Electro-Hydraulic Braking Gear Transmission Mechanism with Unilateral Dead Zone Nonlinearity

Autonomous vehicles require more precise and reliable braking control, and electro-hydraulic braking (EHB) systems are better adapted to the development of autonomous driving. However, EHB systems inevitably suffer from unilateral dead zone nonlinearity, which adversely affects the position tracking control. Therefore, a finite-time adaptive control strategy was designed for unilateral dead zone nonlinearity. Initially, the unilateral dead zone nonlinearity was reformulated into a matched disturbance term and an unmatched disturbance term to reduce the adverse effects of disturbances, thereby enhancing system controllability. Then, the “complexity explosion” in the design of the control strategy was avoided by command filtering, and the design process of the controller was simplified. Furthermore, the finite-time control theory was employed to boost the system’s convergence speed, thereby enhancing control performance. In order to ensure the stability of the system under the dead zone disturbance, the unknown disturbance terms were estimated. The stability of the control strategy was validated through the finite-time stability theorem and the Lyapunov function. Eventually, simulations and hardware-in-the-loop (HIL) experiments validated the feasibility and availability of the finite-time adaptive control strategy.

Distributed adaptive event-triggered finite-time fault-tolerant containment control for multi-UAVs with input constraints and actuator failures

This article investigates the distributed adaptive finite-time containment control problem for multi-UAVs with input constraints, actuator failures, communication limitations, and external disturbances. First, a new smoothing function is used to smooth the asymmetric input constraint signals so that the input constraint and actuator fault control problem can be transformed into a variable gain control problem. Subsequently, a new Nussbaum function is proposed to solve the variable gain control problem. A new adaptive event-triggered strategy is designed to solve the communication limitation problem, and the trigger threshold has the characteristic of adaptive adjustment that can be dynamically decreased. In response to external disturbances, an adaptive law is designed to estimate and compensate for the boundaries of disturbances. It follows from the analysis based on Lyapunov theory that under the proposed controller, the followers will converge to the convex envelope formed by the leaders in a finite time, and Zeno-free is achieved. Simulation results are provided to verify the effectiveness of the developed adaptive event-triggered finite-time fault-tolerant containment control laws.

Finite-time adaptive control based on output feedback and auxiliary variables for time-varying parameters and disturbances

This paper presents a finite-time adaptive control scheme tailored for a diverse range of unknown discrete-time systems, with a specific emphasis on BLDC motor position control. The approach leverages an auxiliary variable within an output feedback framework, adeptly circumventing the causality problem without necessitating the use of state or disturbance observers. Through the application of finite-time convergence techniques, the control law demonstrates robust performance even in the presence of time-varying parameters and compact disturbances. Additionally, the proposed time-varying estimator, based on multi-input fuzzy emulated network (MiFREN), offers a practical solution for handling unknown dynamics and disturbances, making it well-suited for real-world applications where accurate mathematical models may be unavailable. Extensive experimental validation is conducted to evaluate the efficacy of the proposed scheme, including comparisons with existing controllers. The results highlight the superiority of the approach, particularly in terms of tracking accuracy and robustness against disturbances.

Adaptive finite time command filtered backstepping control scheme of uncertain strict-feedback nonlinear systems

This paper proposes an adaptive finite time command filtered backstepping control scheme for single‐input and single‐output (SISO) uncertain strict-feedback nonlinear systems. The problem of the explosion of complexity existing in the adaptive backstepping control design and the singularity problem are solved by using the proposed adaptive finite time control method. In addition, the compensating signals are introduced to deal with the effect of the known filtering errors caused by the command filters. By using the finite time Lyapunov stability theory, the proposed adaptive finite time control strategy guarantees that all the signals in the closed-loop system are practical finite time stable, and the tracking errors converge to an arbitrarily small neighbourhood of the origin in finite time. Simulation and experimental results of the DC-DC buck converter are given to illustrate the effectiveness of the proposed adaptive finite time control scheme.

Neural Network-based Adaptive Finite-time Control for 2-DOF Helicopter Systems with Prescribed Performance and Input Saturation

In this study, we propose an adaptive neural network (NN) control approach for a 2-DOF helicopter system characterized by finite-time prescribed performance and input saturation. Initially, the NN is utilized to estimate the system’s uncertainty. Subsequently, a novel performance function with finite-time attributes is formulated to ensure that the system’s tracking error converges to a narrow margin within a predefined time span. Furthermore, adaptive parameters are integrated to address the inherent input saturation within the system. The boundedness of the system is then demonstrated through stability analysis employing the Lyapunov function. Finally, the effectiveness of the control strategy delineated in this investigation is validated through simulations and experiments.

Finite time adaptive recoil controller design for deepwater drilling riser systems

In this paper, we propose a finite-time model reference adaptive controller to attenuate the recoil response of deepwater drilling riser systems following an emergency disconnection. Firstly, a coupled model that characterizes the recoil movements of the riser, wave-excited heave motion, and the frictional resistance due to drilling fluid discharge is developed. Secondly, an adaptive control law is presented, with a portion of the adaptive gain determined through linear matrix inequalities. Thirdly, the stability criteria and updating rules that ensure finite settling time for the recoil control system is established. Then, the effectiveness and robustness of the controller against nonlinear systematic perturbations are verified. It is worth pointing out that: (1) The proposed adaptive controller significantly attenuates the recoil responses of the riser in finite time. (2) Compared to other controllers, the finite-time adaptive controller provides faster convergence for both error states and adaptive gains. (3) Perturbation cases involving nonlinear and unmodeled dynamics are examined, demonstrating the controller’s effectiveness and robustness, which ensures the safety of the drilling riser system.

Disturbance observer-based finite-time adaptive neural control scheme of DFIG-wind turbine

This paper introduces a novel disturbance observer-based finite-time adaptive neural control approach to optimize wind power conversion in a doubly fed induction generator-based wind turbines (DFIG-WT). This control strategy offers appealing features including rapid finite-time convergence, both transient and steady-state performance enhancements, and robustness against external disturbances and inherent model uncertainties. The control strategy integrates the neural networks estimation capability with the interesting proprieties of the finite-time control method to achieve efficient wind power conversion. Closed-loop finite-time stability is conducted using the finite-time Lyapunov stability concept of nonlinear systems. The developed control strategy’s effectiveness is confirmed through numerical simulation.

Finite-time adaptive NN dynamic surface control for nonstrict nonlinear FOSs subject to input dead-zone and full-states constraints

This article focuses on a kind of nonstrict nonlinear fractional-order systems (FOSs) suffering from state constraints and dead-zone input. Meanwhile, a finite-time adaptive dynamic surface control (DSC) approach based on backstepping technology and approximation principle of radial basis function neural network (RBFNN) is developed. To overcome the problem of inherent computational complexity, a fractional-order filter is applied to approach the virtual controller and its fractional-order derivative in each step of the backstepping procedure. The barrier Lyapunov function (BLF) is employed to handle the state constraints, and finite-time stability criteria on the basis of fractional-order Lyapunov method are introduced to prove the finite-time convergence of the tracking error into a small region around the origin. It is shown that all the solutions of the closed-loop system are bounded, while the state constraints are satisfied within a predetermined finite time. Finally, two examples are provided to demonstrate the effectiveness of the presented control scheme.

Finite-time adaptive control of output constrained nonlinear systems under deception attacks

Finite-time adaptive control of output constrained nonlinear systems under deception attacks

Event-Triggered Adaptive Finite-Time Control Using a Fuzzy State Observer for Nonlinear Cyber-Physical Systems Under Deception Attacks.

This article presents a new event-triggered adaptive finite-time control strategy using a fuzzy state observer for a class of nonlinear cyber-physical systems (CPSs) under malicious deception attacks with a more general form. Compared with the traditional assumptions on the deception attacks in the existing results, a more general assumption on deception attacks is given in this article. During the design process, real system states are initially estimated by developing an improved state observer, which effectively addresses the problem of state unavailability. Then, a coordinate transformation technology, in which the estimated states of observer are considered, is presented to stabilize the studied system. By constructing the singularity-free finite time virtual controls, the singularity problem in the traditional finite time design algorithms is cleverly avoided. Furthermore, to minimize communication overhead, a final finite-time controller is established by using a relative threshold event-triggered scheme. The developed event-triggered adaptive finite-time control strategy guarantees that all signals in the closed-loop system are semi-globally bounded in finite time without Zeno behavior. Finally, the correctness of the proposed control strategy is validated through two simulation results.

Observer-Based Finite-Time Adaptive Fault-Tolerant Control for Nonlinear System with Unknown Time-Varying Delay

Observer-Based Finite-Time Adaptive Fault-Tolerant Control for Nonlinear System with Unknown Time-Varying Delay

Event-triggered finite-time fuzzy tracking control for a time-varying state constrained quadrotor system based on disturbance observer

In contrast with most existing results concerning quadrotor unmanned aerial vehicle (UAV) wherein time-triggered controllers or only symmetric state constraints are considered, this paper deals with the event-triggered finite-time trajectory tracking control problem for quadrotor UAV with asymmetric time-varying state constraints and unknown external disturbances. Firstly, the fuzzy logic system is used to approximate the nonlinear relationship of the quadrotor UAV system, and a disturbance observer is designed to compensate for composite disturbances. Secondly, the command filter and the event-triggered mechanism are introduced into the controller design, while asymmetric time-varying Lyapunov functions are constructed. Thus, the computational complexity and communication burden are reduced, and the event-triggered finite-time adaptive fuzzy controller is guaranteed to stabilize the quadrotor UAV in finite-time without violating all asymmetric time-varying state constraints. Finally, the simulation results demonstrate the validity of the proposed control strategy.

Dual-stage control method for continuous hopping on the surface of small celestial bodies

Surface movement exploration techniques are an important approach to further the understanding of small celestial bodies. Hopping movement is employed to take advantage of the weak gravitational field of small celestial bodies, facilitating long-distance mobility of the rover. The rover exhibits a strong attitude-orbit coupling characteristic during the hopping movement. Different contact attitudes contribute to the challenge of determining the rebound trajectory, rendering it difficult for the rover to maintain continuous movement towards the target position along the nominal trajectory. In this paper, a dual-stage control method for continuous surface hopping movement is developed, wherein the control is applied separately during the flight stage and the collision stage. During the flight stage, applying attitude control enables the rover to establish contact with the surface in a specific attitude, ensuring accuracy in movement direction and creating favorable conditions for the control process in the collision stage. The flywheel is controlled in the collision stage to correct the state change and energy loss due to the collision, enabling the rover to attain the desired hopping state. Considering the energy consumption of the rover, the minimum hopping velocity sequence and angular velocity sequence are designed based on the hopping angle and heading angle. The intricacies and uncertainties inherent in the surface environment of small celestial bodies pose challenges for the rover during hopping and flying. In response to the issue, a finite-time adaptive sliding-mode control law is devised. The control law facilitates the rapid adjustment of the rover to the target attitude in flight, demonstrating strong robustness. In addition, by integrating the changes in contact point velocity with the impulse contact model, the accuracy of the rover's rebound state updates is enhanced. Finally, a set of simulations is performed, and simulation results indicate that the dual-stage control method can achieve a final landing position error of less than 0.2 m for a continuously hopping. The finite-time adaptive sliding-mode control law can stabilize the rover's attitude within 10 s. Conducting 500 Monte Carlo simulations of the continuously hopping rover in three small celestial body surface simulation environments shows that the position endpoint error is within 0.3 m.

Adaptive finite-time neural control of nonstrict-feedback nonlinear systems with input dead-zone and output hysteresis

This paper explores the adaptive finite-time neural control issue for nonlinear systems with input dead zone and output hysteresis in nonstrict-feedback form. The unknown functions are estimated by employing the radial basis function neural networks (RBFNN) approach. A systematic adaptive finite-time control method is introduced using the backstepping technique and neural network approximation properties. The stability of the system is also examined by using semi-global practical finite-time stability theory. The established control approach guarantees the boundedness of all signals within the closed-loop system, enabling the system output to accurately follow the desired signal within a finite time framework while maintaining a small and bounded tracking error. Finally, simulation results are shown to demonstrate the efficacy of the suggested strategy.

Distributed finite-time adaptive consensus output-feedback control of multi-agent systems under switching topologies

The paper investigates the finite-time adaptive consensus control of nonlinear multi-agent systems (MASs) by output-feedback. During the process of control design, the fuzzy logic system (FLS) is employed to approximate nonlinear function, as well as constructing a fuzzy state observer to estimate unmeasured states. Combining the dynamic surface control (DSC) with adaptive backstepping method conquers the complexity explosion issue. Then, semi-global practical finite-time stability (SGPFS) for closed-loop system is obtained under arbitrary switching communication topologies. All the signals of the overall system are uniformly ultimately bounded (UUB). Finally, the availability of developed control approach will be demonstrated through a simulation.