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To improve the autonomy of maritime search and rescue (SAR) operation, this paper concentrates on the formation control problem for autonomous surface vehicles (ASVs) with the limited communication resource. A novel parallel search guidance, considering the maneuvering characteristics of ASVs, is developed to guide the formation to execute the automatic SAR operation. That can guarantee that the corresponding guidance law is highly efficient, self-driving and suitable for the large-scale formation. Combined with the guidance principle, a formation control algorithm is proposed by fuse of the event-triggered control and neural networks (NNs). In the proposed scheme, the gain uncertainty of actuators is effectively compensated requiring no prior information around the model structure. Unlike the existing results, the proposed event-triggered mechanism can activate synchronously both the controller and the NNs weight estimator. Considerable effort has been made to guarantee the semi-global uniform ultimate bounded (SGUUB) stability. Finally, two examples are illustrated to verify the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

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 investigates the adaptive fuzzy event-triggered control for the underactuated surface vessels (USVs), considering constraints of the International Regulations for Preventing Collisions at Sea (COLREGs) and the actuator failures. The proposed scheme can be divided into the guidance module and the control module. An improved logic virtual ship guidance principle, considering the ship-to-ship collision avoidance, is developed to generate the real-time reference signal for USVs. The main characteristic of the guidance principle is to ensure USVs sailing in the path following mode and collision avoidance mode. Especially for the collision avoidance mode, the collision avoidance guidance is targetedly designed for three sailing situations (the head-on situation, the overtaking situation, and the crossing situation), which is consistent with the COLREGs. Furthermore, an adaptive fuzzy event-triggered law is designed to control the USVs to converge to the desired path. The model unknown terms and the basic fault of the actuator are identified by the fuzzy logic system, and the fuzzy logic state observer is designed to estimate the unmeasured states of the USVs. Unlike the existing results, the communication burden from the controller to the actuators is reduced for the merits of the input event-triggered rule. Through the Lyapunov theory, it is proved that all the signals of the closed-loop control system are the semiglobal uniform ultimate bounded. Finally, the simulated examples are provided to illustrate the validity of the proposed control approach. [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]

This paper presents a gain scheduling approach for achieving the consensus tracking of multi-agent systems with actuator saturation. We first construct a series of nesting ellipsoid invariant sets associated with consensus errors. When the consensus errors stay between the two ellipsoid invariant sets, the feedback gains keep constant, but when the consensus errors enter into the smaller ellipsoid invariant set, the feedback gains abruptly become larger. By combining this gain scheduling technique and the parametric Lyapunov equations, we, respectively, design state and output feedback gain scheduling protocols. Their main advantage, in comparison with the fixed case, is that the convergence rate of consensus tracking can be enhanced by scheduling the gain parameters. Numerical simulations verify the effectiveness of theoretical analysis. [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]

Summary: This paper investigates simultaneous estimations of states, system fault, and sensor fault for a class of Markovian jump systems, resorting to the design of a robust observer, in which both the external disturbance and actuator degradation are taken into consideration. The loss‐of‐effectiveness, stuck, and outage fault cases are involved, and the considered Markovian jump system is assumed to possess generally uncertain transition rates, which can generalize the traditional bounded uncertain transition rates and partially unknown transition rates. In particular, an augmented system whose states cover the original states, system fault, and sensor fault is constructed. Then, a novel adaptive observer is presented with time‐varying gain matrices and parameter accommodation being injected to deal with the disturbance and actuator degradation. Finally, a practical example is shown to demonstrate the high efficiency of the proposed method as well as its advantages over some existing results. [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]

Adaptive tracking control of a class of MIMO nonlinear system preceded by unknown hysteresis is investigated. Based on dynamic surface control, an adaptive robust control law is developed and compensators are designed to mitigate the influences of both the unknown bounded external uncertainties and the unknown Prandtl–Islinskii hysteresis. By adopting the low-pass filters, the explosion of complexity caused by tedious computation of the time derivatives of the virtual control laws is overcome. With the proposed control scheme, the closed-loop system is proved to be semi-globally ultimately bounded by the Lyapunov stability theory, and the output of the controlled system can track the desired trajectories with an arbitrarily small error. Finally, numerical simulations are given to verify the effectiveness of the proposed approach. [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]

Polymer micro/nano-actuators are attracting tremendous interest due to their potential applications in micro/nano-mechanical systems and lab-on-a-chip systems. To achieve this, thin films of stimuli-responsive polymers are required to be patterned at the micro/nanometer scale, and also to possess highly ordered orientation in the responsive component. We demonstrate here that nanoscale patterning and uniaxial alignment of liquid crystalline mesogens can be simultaneously achieved by nanoimprint lithography performed in the liquid crystalline mesophase. Photoactive azobenzene mesogens were aligned parallel to the nanogratings imprinted in the films. The degree of alignment depended on the extent of nanoconfinement. The nanogratings expanded in the direction perpendicular to the film upon exposure to uniform UV irradiation, because of trans-to-cis isomerization. In addition, the reversible deformation amplitude strongly depended on the degree of alignment of the photoactive azobenzene mesogens. [ABSTRACT FROM AUTHOR]

This study considers the control problem for a class of non‐linear singularly perturbed systems (SPSs) subject to actuator saturation. A sufficient condition for the existence of state‐feedback controllers to achieve a prescribed stability bound is proposed and the corresponding basin of attraction is estimated. Then a convex optimisation problem is formulated, by which an optimal controller can be obtained to achieve a prescribed stability bound and simultaneously maximise the estimate of the basin of attraction of the SPSs for any allowable singular perturbation parameter. Furthermore, a stability condition is established, which improves the existing stability bound analysis methods for a class of non‐linear SPSs. Finally, examples are given to show the advantages and effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

This paper investigates a parameterized path-guided following/maneuvering control problem of an autonomous surface vehicle (ASV) subject to actuator faults via a noncooperative game strategy. Unlike the existing path maneuvering control methods, the noncooperative game of this paper includes two sub-games. On one hand, the path update is considered to be against the effort of kinematic control. On the other hand, the kinetic control is considered to be against the total disturbances consisting of actuator faults and external disturbances. A robust adaptive fault-tolerant path maneuvering controller is designed based on a noncooperative game approach. Specifically, we design a kinematic control law using an improved dynamic surface control approach to achieve the geometric objective. An improved neural predictor is constructed, in which a concurrent learning-based adaptation is designed to identify unknown fault coefficients. A path update law and a kinetic control law are calculated to cover noncooperative games by using an adaptive dynamic programming approach. Theoretical analysis shows that the closed-loop system is input-to-state stable, and the proposed method can meet the geometric objective, the dynamic objective, and the fault-tolerant objective. Finally, simulation results demonstrate the efficacy of the proposed robust adaptive fault-tolerant control method for path maneuvering. • A noncooperative game-based variable tuning law is proposed for path update. • A fault-tolerant control method is developed using a noncooperative game strategy. • An improved neural predictor is designed for identifying fault coefficients. [ABSTRACT FROM AUTHOR]

In this paper, the formation control of the underactuated surface vehicles (USVs) is studied in the presence of the condition of actuator fault and limited communication resources. Considering the performance characteristics of the underactuated surface vehicle (USV), a robust adaptive synchronized event-triggered formation control method is proposed under the usage of the event-triggered control (ETC) and robust neural damping technique. In consideration of the constant energy expenditure of the law of adaptation, the formulated control method is set in the mechanism of triggering by both the controller and the gain related adaptive law, which could cause the communication to reduce more much power consumption. The robust adaptive rule is fault compensated in the way of combining robust neural damping and dynamic surface control (DSC) techniques. Since the fault amendment strategy compresses inconclusive bias fault parameters and model uncertainty parameters, system stability can be enhanced under the premise of reducing the influence of adaptive parameters. A huge volume of work has taken place to ensure semi-global uniform ultimate bounded (SGUUB) stability. To conclude, the effectiveness of the algorithm is verified by two arithmetic examples. • An expanded square parallel search guidance law is proposed using the DVS principle. • A synchronized event-triggered control algorithm is developed for USVs. • The improved fault compensation strategy is designed to stabilize the fault effect. • The ETC algorithm can effectively reduce the burden of communication resources. [ABSTRACT FROM AUTHOR]

To achieve the autonomous cable-laying operation under the varying depth, this note investigates the path-following problem of underactuated cable-laying vehicles with constraints of the unknown actuator gain. A double-stage logical (DSL) guidance principle is developed to realize the practical laying path programming for the cable-laying vehicle. In the guidance law, the catenary model is incorporated to derive the towing distance, i.e., the horizontal projection distance between the cable landing point and the vehicle's gravity center. That can guarantee the cable-laying operation is solidly implemented in the condition of the varying depth. As for the control part, the composite neural event-triggered control algorithm is proposed by fusing the zero-order holder (ZOH) to stabilize the track error between the target position and the actual one. The event-triggered mechanism is employed to effectively reduce the occupancy of the communication channel between sensors and controllers. Moreover, for the merits of robust neural damping and composite learning techniques, the gain uncertainty of actuators can be compensated by updating two adaptive laws online. The stability analysis of the closed-loop system is rigorously performed via Lyapunov criterion and simulation results are provided to verify the performance of the proposed scheme. • A novel cable-laying scheme is proposed for underactuated vehicle with varying depth. • The catenary model is incorporated to derive a more accurate virtual reference. • Only two adaptive parameters need to be updated to compensate the gain uncertainty. • The ZOH-based event-triggered mechanism can effectively reduce transmission burden. [ABSTRACT FROM AUTHOR]

This paper presents a novel event-triggered cooperative dynamic positioning control algorithm for multiple marine surface ships in the presence of actuator faults. In this algorithm, the undirected interaction topology is employed to construct the communication networks among marine surface ships, and the assumption that the information of leader can be available to all followers is relaxed successfully. To avoid the unnecessary information transmission among ships, the event-triggered mechanism is incorporated in control design. And the strict positive lower bound on interevent interval is proved, which indicates no accumulation of triggering instants, e.g., Zeno behavior is eliminated. Only two adaptive parameters are designed to estimate the actuator fault parameters online, they are updated when the event-triggered condition is violated and held otherwise. Considerable effort is made to guarantee the semi-global uniform ultimate bounded (SGUUB) stability by the extension of Lyapunov approach. Finally, numerical simulations are provided to verify the effectiveness and feasibility of the proposed algorithm. • A distributed control strategy is proposed with fault compensation mechanism. • The undirected interaction topology is used to construct the communication networks. • The lower bound on interevent interval is proved, i.e., Zeno behavior is avoided. • The gain uncertainty and actuator faults are compensated by event-based adaptive law. [ABSTRACT FROM AUTHOR]

This paper investigates a performance-guaranteed formation tracking problem of autonomous surface vehicles (ASVs) under uncertain environments. Especially, model uncertainties, external disturbances and actuator faults exist simultaneously. Based on graph theory and adaptive techniques, a novel two-layer robust adaptive fault-tolerant formation scheme is developed. In kinematic layer, a transformation is made to get a performance unconstrained problem and an adaptive control strategy is incorporated to stabilize transformed errors. In kinetic layer, two types of robust adaptive fault-tolerant formation controllers, i.e. the fault-based one and the fault-unknown one, are designed for different fault scenarios. These controllers share the same structure of single-parameter updating laws to adjust adaptive parameters. It is shown that: 1) using the proposed formation scheme with either designed fault-tolerant controller, desired formation configurations of ASVs are achieved if the interaction topology is connected and control parameters satisfy given conditions; 2) prescribed formation tracking performance can be ensured and all error signals are guaranteed to be uniformly ultimately bounded; 3) a trade-off between two designed controllers exists, that is although the assumption for fault-unknown controller is weaker, larger control parameters are required to behave like fault-based one. Simulations and comparisons are provided to illustrate the effectiveness of theoretical results. • A novel formation scheme is designed with an adaptive strategy in kinematic layer. • Two adaptive fault-tolerant formation controllers are designed in proposed scheme. • A general structure of single-parameter adaptive laws is given for both controllers. • Parameter selection is analyzed and a trade-off between two controllers is observed. [ABSTRACT FROM AUTHOR]

This note focus on the waypoints-based path-following control for the unmanned sail-assisted vehicles (USAV), aiming to release the constraints of the actuator failures and gain uncertainties. The proposed scheme is formulated as two components, i.e., the composite guidance part and the control part. By utilizing the sign self-selection algorithm, the composite Logic Virtual Ship (LVS) guidance law is developed in the scheme to program the real-time heading angle for the USAV. The main superiorities of this design are to ensure the USAV navigating efficiently and choose the corresponding sailing mode: upwind mode, downwind mode or crosswind mode. Furthermore, to improve the effectiveness of the closed-loop control system, an event-triggered robust neural control algorithm is targetly designed for the rudder actuator and the sail actuator by fusing the robust neural damping technique and the input event-triggered mechanism. In this algorithm, the unknown terms of the system are tackled requiring no information of the system model and the external disturbances. The transmission burden from the controller to the actuator is reduced. And the unknown actuator failures and the gain uncertainties are compensated through four adaptive updated parameters. Based on the Lyapunov analysis, sufficient effort has been made to guarantee that all the signals of the closed-loop control system are the semi-global uniform ultimate bounded (SGUUB). Finally, the simulated results demonstrate the validity of the proposed control strategy. • An event-triggered robust neural algorithm is proposed for the unmanned sail-assisted vehicles. • The composited LVS guidance law could generate a real-time reference for the upwind, crosswind and downwind conditions. • The energy consumption and transmission burden of the actuators are largely reduced by the input event-triggered mechanism. • The form of the control law becomes concise by employing robust neural damping techniques. [ABSTRACT FROM AUTHOR]

This paper presents a novel robust neural event-triggered control algorithm to achieve the dynamic positioning operation of marine surface ships in the presence of actuator faults. In the algorithm, the model uncertainty and the "explosion of complexity" are addressed by fusion of the robust neural damping and dynamic surface control techniques. The gain related adaptive law is constructed to compensate the gain uncertainties and the unknown actuator faults, which improved the stability of the ship dynamic loop system. Furthermore, the event-triggered mechanism is introduced to reduce the communication load between the controller and actuator. For merits of the aforementioned design, the proposed algorithm is with the advantages of concise form and easy to be implemented in practical ocean engineering. Based on the Lyapunov theory, rigorous analysis is proved to guarantee the semi-global uniform ultimate boundedness (SGUUB) of the closed-loop system. Finally, numerical simulations are conducted to demonstrate the validity and feasibility of the proposed algorithm. • This paper proposes a neural event-triggered control scheme for dynamic positioning ships with actuator faults.. • The robust neural damping technique is employed to address the model uncertainty. • The "explosion of complexity" is avoided by the DSC filters. • The gain uncertainty is compensated by constructing the related adaptive parameters. [ABSTRACT FROM AUTHOR]