Robust stability analysis of formation control in local frames under time-varying delays and actuator faults

This paper investigates the robust stability of a multiagent system moving to a desired rigid formation in presence of unknown time-varying communication delays and actuator faults. Each agent uses relative position measurements to implement the proposed control method, which does not require common coordinate references. However, the presence of time delays in the measurements, which is inherent to the communication links between agents, has a negative impact in the control system performance leading, in some cases, to instability. Furthermore, the robust stability analysis becomes more complex if failures on actuators are taken into account. In addition, delays may be subject to time variations, depending on network load, availability of communication resources, dynamic routing protocols, or other environmental conditions. To cope with these problems, a sufficient condition based on Linear Matrix Inequalities (LMI) is provided to ensure the robust asymptotic convergence of the agents to the desired formation. This condition is valid for any arbitrarily fast time-varying delays and actuator faults, given a worst-case point-to-point delay. Finally, simulation results show the performance of the proposed approach.     

Fault-tolerant adaptive control for uncertain switched systems with time-varying delay and actuator faults based on sliding mode technique

This paper utilizes the sliding mode approach to tackle the issue of adaptive control for uncertain switched systems with time-varying delay and actuator faults. Firstly, a kind of mathematical model of switched time-varying delay systems under sudden actuator faults is defined. Then, a linear sliding manifold is constructed, followed by some adequate conditions for exponential stability of the switched systems running on the sliding phase. Furthermore, an adaptive fault-tolerant controller for handling the actuator degradation is designed and the reachability of the established sliding manifold is proved. At last, a series of simulation examples are provided to demonstrate the efficiency of the proposed solution.     

Adaptive consensus control for output-constrained nonlinear multi-agent systems with actuator faults

This paper addresses the problem of leader-follower consensus fault-tolerant control for a class of nonlinear multi-agent systems with output constraints. Specifically, a new nonlinear state transformation function is proposed to deal with the asymmetric constraint on output. Moreover, by integrating backstepping and radial basis function neural network approaches, an adaptive consensus control framework is developed with a single parameter estimator, which mitigates the computation of control algorithm in comparison with conventional adaptive approximation based control techniques. Then an adaptive compensation method is proposed to eliminate the effect of actuator failure. Under the proposed control scheme, all the closed-loop signals of the systems are bounded and the consensus tracking error converges to an adjustable small neighborhood of zero. To evaluate the developed control algorithm, a group of four networked two-stage chemical reactors is used to illustrate the effectiveness of the theoretic results obtained.     

Leader-following consensus for multi-agent systems with actuator faults via adaptive event-triggered control

In this paper, the leader-following consensus problem is investigated by event-triggered control for multi-agent systems subject to time-varying actuator faults. Firstly, for a case of the leader without control input, a distributed event-triggered fault-tolerant protocol is proposed with the help of adaptive gains. Secondly, the proposed protocol is developed by an auxiliary nonlinear function to compensate the effect of the leader’s unknown bounded input. It is shown that under the both obtained protocols the tracking errors converge to an adjustable neighborhood around the origin, meanwhile the Zeno behavior is avoided. Moreover, the protocols are fully distributed in sense that any global information associated with the network is no longer utilized. Finally, numerical examples are presented to show the validity of the obtained protocols.     

New gain-scheduling control conditions for time-varying delayed LPV systems

This paper investigates the problem of stability and state-feedback control design for linear parameter-varying systems with time-varying delays. The uncertain parameters are assumed to belong to a polytope with bounded known variation rates. The new conditions are based on the Lyapunov theory and are expressed through Linear Matrix Inequalities. An alternative parameter-dependent Lyapunov-Krasovskii functional is employed and its time-derivative is handled using recent integral inequalities for quadratic functions proposed in the literature. As main results, a novel sufficient stability condition for delay-dependent systems as well as a new sufficient condition to design gain-scheduled state-feedback controllers are stated. In the new proposed methodology, the Lyapunov matrices and the system matrices are put separated making it suitable for supporting in a new way the design of the stabilization controller. An example, based on a model of a real-world problem, is provided to illustrate the effectiveness of the proposed method.     

Robust finite-time cooperative formation control of UGV-UAV with model uncertainties and actuator faults

This paper investigates the finite-time cooperative formation control problem for a heterogeneous system consisting of an unmanned ground vehicle (UGV) - the leader and an unmanned aerial vehicle (UAV) - the follower. The UAV system under consideration is subject to modeling uncertainties, external disturbance as well as actuator faults simultaneously, which is associated with aerodynamic and gyroscopic effects, payload mass, and other external forces. First, a backstepping controller is developed to stabilize the leader system to track the desired trajectory. Second, a robust nonsingular fast terminal sliding mode surface is designed for UAV and finite-time position control is achieved using terminal sliding mode technique, which ensures the formation error converges to zero in finite time in the presence of actuator faults and other uncertainties. Furthermore, by combining the radial basis function neural networks (NNs) with adaptive virtual parameter technology, a novel NN-based adaptive nonsingular fast terminal sliding formation controller (NN-ANFTSMFC) is developed. By means of the proposed adaptive control strategy, both uncertainties and actuator faults can be compensated without the prior knowledges of the uncertainty bounds and fault information. By using the proposed control schemes, larger actuator faults can be tolerated while eliminating control chattering. In order to realize fast coordinated formation, the expected position trajectory of UAV is composed of the leader position information and the desired relative distance with UGV, based on local distributed theory, in the three-dimensional space. The tracking and formation controllers are proved to be stable by the Lyapunov theory and the simulation results demonstrate the effectiveness of proposed algorithms.     

Adaptive fault-tolerant control for a class of nonlinear multi-agent systems with actuator faults

This paper considers the distributed adaptive fault-tolerant control problem for linear multi-agent systems with matched unknown nonlinear functions and actuator bias faults. By using fuzzy logic systems to approximate the unknown nonlinear function and constructing a local observer to estimate the states, an effective distributed adaptive fault-tolerant controller is developed. Furthermore, different from the traditional method to estimate the weight matrix, only the weight vector needs to be estimated by exchanging the order of weight vectors and fuzzy basis functions in the fuzzy logic systems. In contrast to the existing results, the assumption that the dimensions of input vector and output vector are equal is removed. In addition, it is proved that the proposed control protocol guarantees all signals in the closed-loop systems are bounded and all agents converge to the leader with bounded residual errors. Finally, simulation examples are given to illustrate the effectiveness of the proposed method.     

Robust actuator fault diagnosis scheme for satellite attitude control systems

In this paper, a robust actuator fault diagnosis scheme is investigated for satellite attitude control systems subject to model uncertainties, space disturbance torques and gyro drifts. A nonlinear unknown input observer is designed to detect the occurrence of any actuator fault. Subsequently, a bank of adaptive unknown input observers activated by the detection results are designed to isolate which actuator is faulty and then estimate of the fault parameter. Fault isolation is achieved based on the well known generalized observer strategy. The simulation on a closed-loop satellite control system with time-varying or constant actuator faults in the form of additive and multiplicative unknown dynamics demonstrates the effectiveness of the proposed robust fault diagnosis strategy.     

A compensator design technique for control systems with time-varying nonlinear elements

A method is advanced for the design of linear controllers for a class of nonlinear systems. The systems considered in this paper are characterized by the presence of a dominant nonlinearity located in a specified sector. The proposed approach is digital-computer oriented, and design results are presented in parameter planes and parameter space.     

Composite learning adaptive sliding mode control of fractional-order nonlinear systems with actuator faults

This paper considers the tracking control of fractional-order nonlinear systems (FONSs) in triangular form with actuator faults by means of sliding mode control (SMC) and composite learning SMC (CLSMC). In SMC design, a fractional sliding surface is introduced, and an adaptation law is designed to update the estimation of the mismatched parametric uncertainty in the actuator faults. The proposed SMC can guarantee the convergence of the tracking error where a persistent excitation (PE) condition should be satisfied. To overcome this limitation, by using the online recorded data and the instantaneous data, a prediction error of the parametric uncertainty is defined. Both the tracking error and the prediction error are utilized to generate a composite learning law. A composite learning law is designed by using the prediction error and the tracking error. The proposed CLSMC can guarantee not only the stability of system but also the accurate estimation of the parametric uncertainties in the actuator faults. In CLSMC, only an interval-excitation (IE) condition that is weaker than the PE one should be satisfied. Finally, simulation example is presented to show the control performance of the proposed methods.     

Fault-tolerant control for commercial aircraft with actuator faults and constraints

In this paper, a constrained control scheme based on model reference adaptive control is investigated for the longitudinal motion of a commercial aircraft with actuator faults and saturation nonlinearities. Actuator faults and constraints are both important factors adversely affecting the stability and performance of flight control systems. An adaptive adjustment law based on Lyapunov function is utilized to adjust the fault-tolerant control law. Both additive and multiplicative faults are considered in the designed controller to deal with the three types of actuator faults: locked in place, loss of effectiveness, and bias. Moreover, different techniques are implemented in the basic and fault-tolerant controller to anti-windup. Proofs for the stability of the two modified controllers which improve the performance of control system operating in the presence of actuator faults and saturations are proposed. Finally, a numerical example of the anti-windup fault-tolerant controller for a commercial aircraft is demonstrated. The stability and performance improvements can be accrued with the presented fault-tolerant control scheme.     

Adaptive resilient containment control for nonlower triangular multiagent systems with time-varying delay and sensor faults

This paper investigates the adaptive resilient containment control for nonlinear multiagent systems (MASs) with time-varying delay, unmodeled dynamics and sensor faults. To solve the coupling problem of unknown state delays and sensor faults in a nonlower triangular structure, we develop an effective method by using a new lemma and the Lyapunov-Krasovskii functional. Then, to reduce the negative impact of unknown sensor faults, a novel adaptive resilient containment control method is designed based on a distributed sliding-mode estimator, which can effectively improve the transient performance of the MASs. Moreover, by using a dynamic signal, the problem of unmodeled dynamics is solved. The proposed control scheme can not only drive all followers suffering from sensor faults to converge to the convex hull formed by the leaders but also relatively reduce the undesired chattering phenomenon. Finally, a comparative simulation example is given to illustrate the effectiveness of the proposed strategy.     

Reliable control for event-triggered singular Markov jump systems with partly unknown transition probabilities and actuator faults

In this paper, the problem of reliable controller design for event-triggered singular Markov jump systems with partly known transition probabilities, nonlinear perturbations and actuator faults is studied. To mitigate the burden of data transmissions over network, two event-triggered schemes with different triggering conditions are introduced. The switch law between the two event-triggered schemes is governed by a random variable with Bernoulli distribution. Taking nonlinear perturbations and actuator faults into account, the resulting closed-loop system is converted into a time-delay singular Markov jump system with partly known transition probabilities. Sufficient conditions of stochastically admissible for the resulting closed-loop system are obtained in terms of a group of linear matrix inequalities. The co-design of desirable reliable controller and weighting matrices of event-triggered schemes is presented. Finally, two numerical examples are given to show the effectiveness of the developed results.     

Dynamic learning-based fault tolerant control for robotic manipulators with actuator faults

In this paper, a learning-based active fault-tolerant control (FTC) scheme for robot manipulators with uncertainties and actuator faults is proposed. Unlike traditional FTC methods, with dynamic learning theory, both uncertainties and actuator faults can be accurately identified/learned by radial basis function networks. Based on the learned knowledge, dynamical classifiers and experience-based controllers corresponding to different fault modes are constructed. With the help of dynamical classifiers, fault detection and isolation can be obtained rapidly and accurately, and the correct experience-based controller (instead of the controller reconfigured online) corresponding to the current fault system is selected to compensate for faults, and superior control performance is achieved, even in the presence of faults. The simulation studies demonstrate the feasibility of the proposed FTC method.     

Fault diagnosis and fault-tolerant tracking control for discrete-time systems with faults and delays in actuator and measurement

In this paper, the fault diagnosis (FD) and fault-tolerant tracking control (FTTC) problem for a class of discrete-time systems with faults and delays in actuator and measurement is investigated. In the first step, a discrete delay-free transformation approach is introduced for an constructed augmented system such that the two-point-boundary-value (TPBV) problem with advanced and delayed items can be avoided. Then, the optimal fault-tolerant tracking controller (OFTTC) is proposed with respect to an equivalent reformed quadratic performance index. Moreover, by using the real-time system output rather than the residual errors, a reduced-order-observer-based fault diagnoser for the augmented system is designed to diagnose faults in actuator and measurement, and solve the physically unrealizable problem of proposed OFTTC. Finally, the effectiveness of the proposed fault diagnoser and OFTTC is illustrated by a realistic design example for industrial electric heater.     

Robust state-feedback control design for active suspension system with time-varying input delay and wheelbase preview information

This paper develops a robust state-feedback controller for active suspension system with time-varying input delay and wheelbase preview information in the presence of the parameter uncertainties. By employing system augmentation technique, a multi-objective control optimization model is first established and then this controller design is converted to a static full-state feedback controller design with robust H_∞ and generalized H₂ performance, wherein the model-dependent control gain is evaluated by transforming the related nonlinear matrix inequalities into their corresponding linear matrix inequality forms based on Lyapunov theory, and then LMI (Linear-Matrix-Inequality) technique is applied to solve and obtain the desired controller. A numerical simulation case is finally provided to reveal the effectiveness and advantages of the proposed controller.     

Event-based dynamic output-feedback controller design for networked control systems with sensor and actuator saturations

This paper is concerned with the problem of event-triggered dynamic output-feedback H_∞ control for networked control system with sensor and actuator saturations. The event-triggered scheme combined with sensor saturation is first introduced to judge whether the newly sampled signal should be transmitted to the dynamic output-feedback controller or not. Under this scheme, the concurrent closed-loop system is first modeled as a control system with an interval time-varying delay and nonlinear items. Through constructing the Lyapunov–Krasovskii functional and employing linear matrix inequality approach, sufficient conditions for H_∞ asymptotical stability are derived for the networked control system; furthermore, under the above stability condition, a dynamic output-feedback controller and the corresponding event-triggered parameters are co-designed through linear matrix inequality approach. Lastly, a numerical example is employed to prove the practical utility of this method.