Presence Of Actuator Failures Research Articles

Input–output finite-time robust stabilisation of distributed parameter cyber-physical systems with deception attacks

In this paper, we study the state estimation and input–output finite-time (IO-FT) stabilisation issues for cyber-physical distributed parameter systems (CPDPSs) designed by parabolic partial differential equations. More precisely, to reconstruct the immeasurable states of the addressed CPDPSs, a proportional-integral (PI) observer is implemented since the system states are not always readily measurable. Furthermore, the stability analysis is investigated for CPDPSs in the presence of actuator failures, deception assaults, external disturbances and linear fractional uncertainties. Further, a PI observer-based secured quantised reliable controller is designed to ensure the IO-FT stability of the resulting closed-loop system. Moreover, to reduce the burden on the communication medium, the control input data is quantised before transmission by employing logarithmic quantisers. In the meantime, the deception attacks are assumed to possess a stochastic nature which follows Bernoulli distribution. Besides, by utilising Lyapunov stability theory and integral inequality, a set of adequate conditions is obtained for achieving the required result of the undertaken system. Furthermore, the resulting stability criteria are expressed in the form of linear matrix inequalities, which can be solved using the MATLAB software. Eventually, two numerical examples with simulation results are provided to validate the efficacy of the designed controller.

Distributed integral controllability for non-square processes: A comprehensive study and numerical analysis

Distributed control systems offer significant benefits such as enhanced flexibility, improved failure tolerance, and simplified system design compared to centralized systems. While the controllability of linear square systems under decentralized structures incorporating integral action is well-explored, challenges arise when dealing with non-square processes, which are prevalent in various control and optimization scenarios. Traditionally, non-square systems are manipulated into square configurations by adjusting inputs and outputs to apply decentralized integral controllability (DIC) analysis, potentially affecting the system’s reliability and controller flexibility. To address this issue, we propose a direct application of decentralized integral controllability to non-square processes, termed DIC-NSQ. We approach this problem by representing the system through a state space description, transforming it into standard singular perturbation form, and subsequently establishing its necessary as well as sufficient conditions using singular perturbation analysis. Through numerical examples, we demonstrate that DIC-NSQ effectively maintains offset-free tracking and ensures robust performance, even in the presence of actuator failures. This contribution marks an advancement in the field of distributed control systems, particularly for applications involving non-square processes.

Distributed Adaptive Formation Control for Fractional-Order Multi-Agent Systems with Actuator Failures and Switching Topologies

In this paper, a class of distributed adaptive formation control problems are investigated for second-order nonlinear fractional-order multi-agent systems with actuator failures and switching topologies. To address these challenges, two adaptive coupling gains based on agents’ position and velocity are incorporated into the control protocol. Using the Lyapunov method along with graph theory and matrix analysis, sufficient conditions for system stability are derived in the presence of actuator failures and switching topologies. The effectiveness of the proposed control protocol is demonstrated through numerical simulations, which show its capability to maintain stable formation control under these challenging conditions.

Satellite attitude control using extended model predictive control (EMPC) under actuator failures

The space sector has become increasingly relevant, especially satellites, due to their ability to access different parts of the planet in a short space of time. The challenge of controlling the satellite’s attitude is crucial to the success of a mission. However, the actuator failure condition makes this task even more challenging since the system becomes underactuated, and the control strategies that deal with this scenario and present a satisfactory computational cost are limited unless a simplification of the system dynamics is adopted, such as considering the total angular momentum equal to zero or the diagonal moment of inertia matrix. In this work, extended model predictive control (EMPC) was used to point a satellite in the nadir direction in the presence of actuator failure. This controller uses a model of the system to optimize the control variable over a finite prediction horizon, obtaining a near-optimal solution. The control strategy was tested through a Monte Carlo simulation in two failure scenarios, the first with a failure in the reaction wheel and then also with a failure in the magnetic-torque rod. The results showed that for the first failure scenario, the time required to perform pointing and the final error were lower than for the second failure scenario. The computational load was evaluated through a closed-loop simulation using an embedded processor based on the ARM platform. The simulation shows that the model requires less memory and is more efficient in terms of execution time. The robustness analysis shows that the controller is robust to external disturbance torques and errors of up to 50% in the inertia of the model, with no significant loss in performance. We suggest that the proposed technique is capable of performing pointing with satisfactory accuracy, even with two actuator failures. In addition, this approach can yield substantial cost savings, which is more pronounced for small satellite platforms such as CubeSats.

Multi-objective integrated attitude control of large solar power satellite: A distributed incremental predictive approach

This paper addresses the multi-objective integrated attitude control problem of a large solar power satellite (SPS) in the presence of time-varying parameters, disturbances, and actuator saturation. The attitude coupling dynamic model, which could accurately describe the rotational motion of different SPS components, is firstly obtained. The gravity gradient, solar radiation pressure, microwave radiation reflection, and friction torques are investigated to evaluate their influence on attitude control accuracy. The coupling dynamic model is linearized and discretized, which provides a subsystem model for distributed controller design. A distributed incremental predictive controller is designed for each rotation channel to form a distributed system. The augmented system state is defined to solve the complex constraint problem, and the predicted value with feedback correction is introduced to deal with the disturbances. Besides, the stability of the system is analyzed by considering external disturbances and actuator failure. Comparative analysis with centralized methods under the same prediction horizon is provided, and the results demonstrate a tenfold solution performance enhancement while maintaining accuracy. Furthermore, the controller is integrated with feedback correction, which could improve control accuracy by at least one order of magnitude. The proposed controller reduces the adjusting time for attitude stabilization by 56.8 % in the presence of actuator failure. The simulation results demonstrate that the proposed controller has good robustness and fault tolerance, which provides a feasible solution for SPS multiple attitude control missions.

Fault-Tolerant Control for Carrier-Based Aircraft Automatic Landing Subject to Multiple Disturbances and Actuator Faults

This paper introduces a fault-tolerant control scheme for the automatic carrier landing of carrier-based aircraft using direct lift control. The scheme combines radial basis function neural network and active disturbance rejection control (RBF-ADRC) to overcome the impact of actuator failures and external disturbances. First, the carrier-based aircraft model, the carrier air-wake model, and the actuator fault model were established. Secondly, ADRC is designed to estimate and compensate for actuator faults and disturbances in real time. RBFNN adjusts the ADRC controller parameters based on the system state. Then, the Lyapunov function is constructed to prove the stability of the closed-loop system. The controller is applied to the direct lift control channel, auxiliary attitude channel, and approach power compensation system. The direct lift control improves the performance of fixed-wing aircraft. Finally, comparative simulations were conducted under various actuator failures. The results demonstrate the remarkable fault tolerance of the RBF-ADRC scheme, enabling precise tracking of the desired glide path by the shipboard aircraft even in the presence of actuator failures.

Neuroadaptive Fault-Tolerant Control With Unsynchronized Event Triggering for Actuation Updating and Parameter Adaptation.

Communication and computation resources are normally limited in remote/networked control systems, and thus, saving either of them could substantially contribute to cost reduction and life-span increasing as well as reliability enhancement for such systems. This article investigates the event-triggered control method to save both communication and computation resources for a class of uncertain nonlinear systems in the presence of actuator failures and full-state constraints. By introducing the triggering mechanisms for actuation updating and parameter adaptation, and with the aid of the unified constraining functions, a neuroadaptive and fault-tolerant event-triggered control scheme is developed with several salient features: 1) online computation and communication resources are substantially reduced due to the utilization of unsynchronized (uncorrelated) event-triggering pace for control updating and parameter adaptation; 2) systems with and without constraints can be addressed uniformly without involving feasibility conditions on virtual controllers; and 3) the output tracking error converges to a prescribed precision region in the presence of actuation faults and state constraints. Both theoretical analysis and numerical simulation verify the benefits and efficiency of the proposed method.

Fault-tolerant control allocation for a bio-inspired underactuated AUV in the presence of actuator failures: Design and experiments

In this paper, we present the mathematical design and implementation of a fault-tolerant control scheme for a bio-inspired underwater robot with four flexible fins. The proposed active fault-tolerant control scheme re-configures the force allocation matrix using the elimination of column method, depending on which fin actuator is faulty. The proposed method allows to decouple the 6-DOF controllable underwater vehicle using the remaining three fins. The efficacy of the proposed method is assessed experimentally for trajectory tracking of an ellipsoidal-shaped trajectory using two different controllers, namely PID control and Sliding Mode control. The obtained results show that the combination of a sliding mode controller with the proposed fault-tolerant control allocation approach ensures an efficient trajectory tracking control performance when faults occur.

Integrated vehicle control using adaptive control allocation

SummaryThe focus of this paper is an integrated, fault‐tolerant vehicle control algorithm for the overall stability of ground vehicles. The proposed scheme comprises a high‐level controller that creates a virtual control input and a low‐level adaptive control allocator that distributes the virtual control effort among redundant actuators. The proposed control framework distinguishes itself from earlier results in the literature by its ability to blend active suspension, steering and traction control channels, in the presence of uncertainties and time‐varying dynamics, without the need for fault identification. The control structure is validated in the simulation environment using a fourteen‐degree‐of‐freedom non‐linear vehicle model. The integrated controller is compared to the case of a conventional control approach where each control problem is solved separately. Our results show that, compared to the conventional approach, the proposed method ensures that the vehicle follows driver inputs with up to % higher longitudinal maneuver velocity, despite the presence of actuator failures and slippery road conditions. Furthermore, to demonstrate the benefit of integrating active suspension control to the overall control scheme, we replaced the suspension control of the proposed approach with an independent suspension control system for comparison purposes. We then showed that the integrated case provided % lower roll angle deviation, and % lower pitch angle deviation, in the presence of actuator effectiveness loss and adverse road conditions.

Prescribed-Time Performance Recovery Fault Tolerant Control of Platoon With Nominal Constraints Guarantee

The specific restrictions are breached in the case of vehicle platoon faults and result in unacceptable system performance degradation. This paper proposed a novel prescribed time performance recovery fault tolerant control method to ensure nominal platoon performance under multiple faults, including actuator faults with deferred backup actuator switching and leader-follower link faults in consideration. A novel barrier function based prescribed time sliding mode controller is devised to assure platoon consensus errors and convergence time within prescribed constraints under normal conditions at first. Under multiple faults conditions, to tackle with leader-follower link faults problem, a novel distributed recursive estimator is proposed to estimate the leader’s states and recover the previous leader-follower platooning control protocol in a prescribed time. Besides, in the presence of actuator failures, the nominal constraints violated problem under faults is put into consideration. Owing to the unavoidable deferred actuator replacement time, the previous platoon consensus error constraints are violated and cause platoon performance degradation. Under such circumstances, by exploiting one novel barrier function-based sliding mode controller with an error shifting function, the unfavorable exceeding platoon consensus errors can be recovered into the nominal constraints domains within a prescribed time. Numerical simulations and hardware-in-loop (HIL) experiments are demonstrated to validate the effectiveness and superiority of our performance recovery fault tolerant control algorithms.

Finite-time dissipative synchronization of discrete-time semi-Markovian jump complex dynamical networks with actuator faults

This paper is concerned with the problem of finite-time synchronization for a class of discrete-time semi-Markovian jumping complex dynamical networks (CDNs) with actuator faults based on reliable control. The main aim of this paper is to design a state feedback controller such that the resulting closed-loop system is finite-time synchronized under a prescribed dissipativity performance level even in the presence of actuator failures. Moreover, a stochastic nature followed by Bernoulli distribution is described in the considered networks due to the occurrence of probabilistic nature in time-varying delays. By composing a suitable Lyapunov–Krasovskii functional containing triple summation terms with the aid of Kronecker product properties, Lyapunov stability theory and free weighting matrix approach, sufficient criteria are established in terms of linear matrix inequalities that assure finite-time synchronization and meet the dissipativity performance to the addressed CDNs. The usefulness of the presented design scheme is finally verified by numerical examples.

Robust adaptive event-triggered fault-tolerant control for time-varying systems against perturbations and faulty actuators

In this paper, the robust adaptive event-triggered fault-tolerant control (FTC) problem is addressed for a time-varying continuous-time system with perturbations and general actuator failures. In order to eliminate the adverse effects of faults and perturbations on system performance, a robust fault-tolerant controller is derived via integrating direct adaptive control technique to adjust control parameters. For the sake of reducing the communication resources and actuator actions, an event-triggered control technique is presented to adjust the control inputs based on the proposed FTC strategy. To ensure the system is free from Zeno phenomenon, a bound on the inter-event execution time is established. On the basis of the event-trigger condition, the uniformly bounded stability results of the adaptive FTC system are obtained by utilizing Lyapunov stability theory in the presence of actuator failures and perturbations. The superior of the developed control strategy is substantiated by simulation results of a rocket fairing system.

Adaptive Actuator Failure Compensation on the Basis of Contraction Metrics

This letter develops an adaptive actuator failure compensation method for nonlinear systems with unmatched parametric uncertainty based on contraction metrics. The proposed method, which is constructed by benefiting from the recent achievements on contraction metrics based adaptive control techniques, ensures the closed-loop stability and asymptotic tracking of the desired trajectory in the presence of actuator failures. In particular, a sufficient convex condition is derived for constructing a valid metric, by which a quadratic program-based controller is obtained to determine the inputs of the actuators. The introduced method is more general than the common adaptive actuator failure compensation methods, as it does not require the system to have an identical relative degree for all inputs and be transformable into the parametric strick-feedback or feedback linearization form. Besides, it can be enriched with learning-based algorithms and common robust modifications. Simulation results are presented to verify the effectiveness of the proposed controller.

Event-triggered adaptive control of a class of nonlinear systems with non-parametric uncertainty in the presence of actuator failures

This paper deals with event-triggered adaptive tracking control of a class of nonlinear systems with non-parametric uncertainty and unknown control input direction, in the presence of actuator faults. The proposed event-triggered control method takes advantage of the radial basis function neural networks to approximate the non-parametric uncertainties. Moreover, this control method benefits from the Nussbaum-type function-based adaptation laws for simultaneously dealing with unknown input direction and actuator faults. Numerical simulation results confirm the efficiency of the proposed control method to confront the above mentioned limitations.

Adaptive Actuator Fault Compensation and Disturbance Rejection Scheme for Spacecraft

An adaptive actuator failure compensation scheme is proposed for attitude tracking control of spacecraft with unknown disturbances and uncertain actuator failures. A new feature of this adaptive control scheme is the adaptation of the failure pattern parameter estimates, as well as the failure signal parameter estimates, for direct adaptive actuator failure compensation. Based on an adaptive backstepping control design, the estimates of the disturbance parameters are used to solve the disturbance rejection problem. Without the requirement of additional fault detection mechanism, the switching function is designed to automatically locate and turn off the unknown faulty actuators by observing a control performance index. The asymptotic stability of the system output in the presence of actuator failures is rigidly proved through standard Lyapunov approach, while the other signals of the closed-loop system are guaranteed to be bounded. Simulation results verify the desired adaptive actuator failure compensation performance.

Adaptive actuator failure compensation for a class of nonlinear systems with full state constraints

AbstractIn this article, an adaptive compensation scheme is proposed for controlling a class of Brunovsky form systems with unknown parameters and possible actuator failures such that the full state constraints can be achieved. Compared with the previous research, the main advantage of the scheme is that by selecting a set of parameters related to the barrier Lyapunov functions, virtual control signals can be constrained within required boundaries. As a result, the full state constraints and tracking performance constraints can be achieved simultaneously even in the presence of actuator failures. It is shown that with this scheme, all the closed‐loop signals are bounded and the tracking error converges to a residue set that can be made arbitrarily small

Fuzzy finite-time stable compensation control for a building structural vibration system with actuator failures

This paper investigates finite-time stability vibration control for a building structure system in the presence of actuator failure. The dynamic compensation approach for seismic waves improves the control performance by considering such waves as an unknown nonlinear item in the system. In the control design, this item is approximated via the adaptive fuzzy control method. In addition, it is considered that actuators can fail and therefore lessen, the effectiveness of the suppression of building structure vibration. An adaptive failure compensation method is proposed to address this problem. Moreover, to rapidly suppress vibration, a finite-time active vibration controller is designed in combination with a failure compensation method. Under the proposed control strategy, the building structure system with uncertain actuator failures can be guaranteed to be stable in finite time. Finally, examples of different failure cases are presented to demonstrate the anti-seismic effectiveness of the proposed method.

Resilient fault-tolerant anti-synchronization for stochastic delayed reaction–diffusion neural networks with semi-Markov jump parameters

This paper deals with the anti-synchronization issue for stochastic delayed reaction–diffusion neural networks subject to semi-Markov jump parameters. A resilient fault-tolerant controller is utilized to ensure the anti-synchronization in the presence of actuator failures as well as gain perturbations, simultaneously. Firstly, by means of the Lyapunov functional and stochastic analysis methods, a mean-square exponential stability criterion is derived for the resulting error system. It is shown the obtained criterion improves a previously reported result. Then, based on the present analysis result and using several decoupling techniques, a strategy for designing the desired resilient fault-tolerant controller is proposed. At last, two numerical examples are given to illustrate the superiority of the present stability analysis method and the applicability of the proposed resilient fault-tolerant anti-synchronization control strategy, respectively.

Fault-Tolerant Control of Teleoperation Systems with Flexible-Link Slave Robot and Disturbance Compensation

This study addresses the control problem of a teleoperation system with the slave flexible-link in the face of time delay, dynamic uncertainties, disturbances, and actuator faults. In the presence of actuator failures or when unknown disturbances act on the master and slave manipulators, the teleoperation system will be more likely to face the performance degradation and even instability. This paper proposes a simple proportional-derivative controller in conjunction with a disturbance observer and an auxiliary controller. Advantages of the proposed control law include its simple structure and no requirement for fault detection and isolation mechanism; thus, it is appropriate for implementation. Additive appealing features are that the controller can compensate dynamic uncertainties, disturbances, and actuator failures. Using a Lyapunov function, it is demonstrated that all the signals in the closed-loop system are ensured to be ultimately bounded. Simulation results are presented to verify the effectiveness of the proposed controller.

A novel adaptive actuator failure compensation scheme based on multi-design integration for half-car active suspension system

A new actuator failure compensation scheme in the presence of actuator failures with multi-uncertainties is proposed for half-car active suspension systems based on multi-design integration. A parameterized function has been introduced to denote the multiple failures occurred in the front and rear actuators. An effective feedback controller is designed to obtain asymptotic tracking and closed-loop system stability by employing backstepping technique. Based on the desired controller, multiple adaptive control signals are designed corresponding to each possible failure case. By introducing failure indicator functions and integrating these control signals, a composite controller is constructed to handle all failure patterns, which ensures both pitch and vertical motions of car body to stabilize and track the desired signals. Finally, simulation is conducted to verify the effectiveness of the controller proposed in this study.