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This paper presents an adaptive neural fault-tolerant control algorithm for the path-following activity of the underactuated surface vehicle (USV) using the novel output-based triggering approach. In the algorithm, the event-triggered mechanism is designed utilizing the attitude states from the kinematics aspect of USV. Both the control inputs and the related calculation thread are implemented only at the trigger instants. Furthermore, neural networks (NNs) are employed to remodel the model uncertainties, and the adaptive observer is developed to estimate and compensate for the effect of the unknown actuator faults. With the direct Lyapunov theorem, the semi-global uniformly ultimately bounded (SGUUB) stability can be guaranteed for the closed-loop system in aspects of both the trigger instant and the continuous interval. The comparison experiment has been illustrated to verify the effectiveness of the proposed algorithm, which can effectively improve the information transmission performance and the fault-tolerant capability. [ABSTRACT FROM AUTHOR]

In this article, an asynchronous output-feedback controller is proposed for a class of Markovian jump systems (MJSs) with generally bounded transition rates (TRs). Specifically, two cases have been considered, one of which assumes the TR being completely unknown, while the other specifies the TR range. In particular, the designed asynchronous output-feedback controller is independent of the system modes, implying a sustainable controlling behavior against unavailable system modes. It is worth noting that the mode-dependent controller can be treated as a special case of the independent one. Furthermore, the existing conditions of such a controller are acquired in terms of linear matrix inequalities. Finally a practical example, concerning a single-machine infinite-bus power system, is given to confirm the feasibility of the proposed controller. [ABSTRACT FROM AUTHOR]

This article presents a novel composite neural learning fault-tolerant algorithm to implement the path-following activity of underactuated vehicles with event-triggered input. With the input event-triggered mechanism, the dominant superiority is to reduce the communication burden in the channel from the controller to actuators. In the proposed scheme, the system uncertainties are dealt with in the fusion of the neural networks (NNs) and the dynamic surface control (DSC) method. The serial-parallel estimation model (SPEM) is constructed to estimate the error dynamics, where the derived prediction error could improve the compensation effect of the NNs. As for the gain uncertainties and the unknown actuator faults, four adaptive parameters are designed to stabilize the related perturbation and not be affected by the triggering instants. Based on the direct Lyapunov theorem, considerable efforts have been made to guarantee the semiglobal uniformly ultimately bounded (SGUUB) stability of the closed-loop system. Finally, comparison and practical experiments are illustrated to verify the superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

For leader-following multiagent systems with input saturation, the existing protocols use a low gain feedback approach to achieve semi-global consensus. The main drawback of this approach is the ineffective utilization of the actuator potential, resulting in bad performance. To improve the transient performance of the consensus tracking, this paper proposes a gain scheduled approach for multiagent systems subject to the saturator saturations. A novel kind of scheduler-based protocols are proposed, which consists of state feedback controllers with time-varying gain and parameter schedulers. The role of the controllers is to achieve the consensus tracking, while the schedulers can accelerate this consensus progress by enlarging the gain parameter. To remove the dependence of the schedulers on global information, a minimum-value-based consensus algorithm is put forward, with idea of driving all values of agents throughout the network to their minimum value. Its implementation is guaranteed by the network-topology connectivity. Finally, our approach is further extended to the case where the leader’s control input is nonzero, time-varying, and bounded. The discontinuous protocol and its continuous approximation counterpart are designed, yielding the exact- and quasi-consensus tracking, respectively. Simulation results verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

This study deals with the protocol design for achieving robust global consensus tracking of multi‐agent systems. Agent dynamics are described as general linear systems with actuator saturation and input additive uncertainties and disturbances. Via developing a scheduled low‐and‐high gain design technique, the state feedback protocol is proposed, under which global consensus tracking and disturbance rejection for such systems can be achieved under the mild assumptions on agent dynamics and network topology. This result is further extended to the case of the reduced‐order observer‐based protocol design, with the help of the special coordinate basis approach. Finally, the advantages of the proposed protocols are illustrated by a numerical simulation. [ABSTRACT FROM AUTHOR]

This study addresses the networked control problem for event‐triggered systems with quantisation effect and actuator fault. A new type of finite‐level dynamic logarithmic quantiser is proposed here. Firstly, when the actuator is subjected to deterministic fault and time delay occurs in the network between the sensor and the controller, stability analysis and stabilisation of the system are accomplished. Secondly, suppose the actuator is subjected to stochastic fault and there is packet dropout in the network between the sensor and the controller, the asymptotic stability of the system is analysed, and a mean‐square feedback controller is designed. Finally, simulation studies are made to verify the effectiveness of the presented method. [ABSTRACT FROM AUTHOR]

This paper addresses the robust consensus reliable control problem against actuator faults for linear parameter-varying multiagent systems. First, the actuator faults are modeled via a polytopic uncertainty method. Second, a distributed observer is designed for the single agent by sharing the communication network sensors to estimate the state information. Then by these estimated information, a robust consensus reliable control protocol against actuator faults is obtained and desired disturbance rejection performance can be guaranteed by this proposed protocol. Third, the nonconvexity conditions of the consensus control protocol can be translated into an linear matrix inequality optimization problem via simple matrix calculation. Finally, the effectiveness of the proposed reliable controller scheme is illustrated by two examples. [ABSTRACT FROM AUTHOR]

This paper deals with the optimum dynamic positioning control problem for marine ships in the presence of actuator gain uncertainties and unknown environmental disturbances. The proposed approach is formulated as two modules, i.e., the guidance part and the control part. By utilizing the improved extremum seeking algorithm, the optimum-seeking guidance is developed in this note to generate the reasonable heading guidance for dynamic positioning ships. The main purpose of this design is to ensure the closed-loop system running efficiently and environment-friendly in practice. Combined with the proposed guidance principle, a robust neural control algorithm is developed based on the dynamic surface control, neural networks, and the robust neural damping technique. In this algorithm, the strong couplings of state variables and the gain uncertainty of actuators are tackled, and the system uncertainties are compensated requiring less (or no) information of the hydrodynamic structure, the actuator model and the external disturbances. Considerable effort is made to guarantee the semiglobal uniform ultimate bounded stability by employing the Lyapunov theory. The advantages of the proposed control scheme could be summarized as two points. First, the control approach is with the properties of optimization and energy-saving, which is meaningful for applying the theoretical algorithm. Second, the pitch ratio of thrusters is selected as the control inputs of interest, which is measurable in the practical plant. These characteristics would facilitate the implementation of the algorithm in engineering. Two examples are provided to verify the performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this study, the authors mainly focus on the event‐triggered control design problem of networked control systems (NCSs) with dynamic quantisation and fault. The research contents are divided into two parts. The first part assumes that quantised measurements of the state are available, asymptotic stability analysis and feedback controller design of the event‐triggered NCSs with constant sensor fault and actuator fault are accomplished. The second part assumes that quantised measurements of the input are available, stochastic actuator fault, which is modelled by the Bernoulli distributed white sequence is considered in this situation, and a robust feedback controller is designed. At the end, numerical examples are given to illustrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

This study addresses the finite‐frequency robust feedback controller design problem against actuator faults for linear parameter‐varying systems. First, a general model of actuator faults is presented. Then, sufficient conditions for the existence of the state‐feedback controller are obtained by using generalised Kalman–Yakubovich–Popov lemma and projection lemma, which guarantee that the closed‐loop system satisfies robustness performance in a finite‐frequency domain and is stable for both faults free and actuator faults. In addition, by introducing a state feedback gain, the non‐convexity conditions of the output‐feedback gain are derived. An iterative linear matrix inequality algorithm is proposed in this study to get the solution. The performances of the proposed reliable controller schemes are illustrated by two examples. [ABSTRACT FROM AUTHOR]