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This article investigates the policy iteration (PI) method for the discounted optimal control (DOC) problem of continuous‐time linear systems. We show the properties and convergence of the PI method. The theory analysis shows that the convergence of PI can be ensured without requiring the initial admissible control gain. The convergence rate of the PI method is provided. An iteration‐termination criterion is established for detecting the stability of the closed‐loop system under the control gain obtained by executing PI. Two kinds of data‐driven implementations are constructed without using prior information of the system dynamics. A simulation example is presented to validated the properties of the PI method. [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]

This note focuses on the leader–follower formation control problem of underactuated surface vehicles (USVs) with the unknown environmental disturbance. Especially, due to the ocean environmental disturbance, the vehicle's desired-heading angle is altered violently. To address the constraint, a reduced-order extended state observer (ESO) is introduced. The sideslip angle of the vehicle is estimated online to amend the reference heading angle by virtue of the proposed observer. Furthermore, a novel adaptive formation control algorithm is presented to stabilize the dynamic error system. For the merits of the radial basis function neural networks (RBF NNs) and the minimal learning parameter (MLP) techniques, only two adaptive parameters require to be updated online to compensate for the perturbation from the model uncertainty and the environmental disturbance. Based on the proposed controller, it is illustrated that the desired formation pattern can be maintained without the effect of the sideslip angle. Meanwhile, all signals in the closed-loop system are proved to be with the semi-global uniformly ultimately bounded (SGUUB) stability. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed algorithm. [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 paper investigates the leader–follower formation problem of underactuated surface vessels. Velocities of both leader and follower vessels are unavailable. Model uncertainties and ocean disturbances are also considered. By incorporating adaptive control, neural networks (NNs), the high-gain observer (HGO) and the minimal learning parameter (MLP) algorithm in the backstepping procedure, a novel adaptive output-feedback formation control scheme is developed. We show that formation errors can be guaranteed to be semiglobally uniformly ultimately bounded (SGUUB) with the proposed controller. Compared with existing methods, the formation can be achieved only with position and yaw angle of both leader and follower. Meanwhile, the developed scheme can enhance the robustness of the closed-loop system with less computational effort, where only two online parameters need to be tuned. Simulation and comparison results are provided to illustrate the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

Abstract In this work, a novel optimized robust control algorithm, based on the mirror-mapping method, is proposed for a class of industrial unstable process with time delay. The optimizing criterion is to minimize the sensitivity function to enhance its robustness. The controllers are designed based on the Padé approximated mirror-mapping process with a stable form, other than the original unstable system. The developed algorithm could release the internal stability constraints to the unstable plant. By using the graphical stability criterion, a systematic methodology is derived to obtain the exact stabilizing region, where the sole design parameter is related to the stability degree of the closed-loop system. The proposed algorithm is with characteristics of concise and efficient design. Three experiments has been employed to illustrate that the control effects can achieve the satisfied performance in aspects of disturbance rejection and robustness. Highlights • A novel optimized robust algorithm is proposed with more efficient performance. • The algorithm could release the internal stability constraints to unstable plant. • The exact stabilizing region is identified by the graphical stability criterion. [ABSTRACT FROM AUTHOR]

In this note, a novel adaptive constrained control algorithm is proposed for dynamic positioning vessels in the presence of input amplitude and rate saturations. In the scheme, both kinematics and kinetics loops are augmented by the auxiliary system to deal with the saturation impact. Meanwhile, for merits of the command filters and minimal leering parameter technique, the cumbersome analytic derivatives of the virtual control law need not be required in the control design, and only two adaptive parameters are updated online to stabilise the effect of the model uncertainty and the external disturbance for each subsystem. Using the Lyapunov theory, the semi‐global uniformly ultimately bounded is proved for the closed‐loop system. The effectiveness and robustness of the proposed algorithm are demonstrated by the numerical example in the presence of the simulated marine disturbance. [ABSTRACT FROM AUTHOR]

Summary: In this paper, an effective method is proposed to get the stabilizing regions of fractional‐order PIλDμ controllers for an arbitrarily given fractional‐order system with time delay. For each known proportional gain (kp), integral gain (ki), or derivative gain (kd) in the PIλDμ controllers, the stabilizing region with respect to the other two control gains is derived respectively. The boundaries of the stabilizing regions are firstly obtained based on singular frequencies. Then, the main results are presented to directly determine the stabilizing region from an analytical viewpoint. The results avoid the time‐consuming stability test since the stabilizing region is usually determined by manually choosing lots of test points from all the divided regions by the resultant boundaries. Besides, the stabilizing (ki, kd) regions of the PIλDμ controllers for λ + μ = 2 can be determined and the linear programming characteristic of the stabilizing (ki, kd) region for the case λ + μ = 2 is obtained. Furthermore, the robust stabilizing region is analyzed. The results in this paper provide the basis for both the tuning of the PIλDμ controller in practice and the design of the PIλDμ controller satisfying different performance criteria. Numerical examples and an application example are presented to check the validity of the proposed method. [ABSTRACT FROM AUTHOR]

A two‐degree‐of‐freedom consensus scheme is investigated for fractional‐order multi‐agent systems with time delay. The two‐degree‐of‐freedom protocol including the individual controllers and the coupling controllers can realise the global tasks and improve consensus performance. Based on such a protocol, a closed‐loop multi‐input multi‐output framework in frequency domain is established. Then the multi‐agent system is decoupled into several subsystems with respect to the eigenvalues of the Laplacian matrix. For each subsystem, the robust stabilising region of the individual controller satisfying H∞ index is obtained on the basis of the improved D‐partition method. The controller parameters chosen in the region can provide robustness for the individual agent. The parameters of the coupling controller that ensure fast consensus are determined by first deriving the stabilising region and then searching for the fastest consensus speed in the obtained region. The two‐degree‐of‐freedom structure can trade off the consensus performance and disturbance rejection and is applicable to arbitrary‐order multi‐agent systems with time delay including the fractional‐order system and the integer‐order system. The two‐degree‐of‐freedom consensus controller satisfying other performance criteria can also be designed based on the resultant stabilising region. The simulation results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A systematical design method of optimal control for non-minimum phase integrating processes with time delay using disturbance observer-based (DOB) control scheme is presented. All stabilising controllers and the filter of DOBs for integrating plants are developed. Then the optimal set-point tracking controller and the optimal filter of DOB are systematically derived by minimising the H2 norm performance specifications. The proposed design method has three main advantages. First, the design procedure is systematical and simple. Specified weight functions are chosen for step inputs and inputs similar to steps. The designed set-point tracking controller and the filter of DOB are given in analytical forms. Second, the designed set-point tracking controller and the filter of the DOB are optimal. They are derived from minimising the performance indexes of set-point tracking and input load disturbance rejection (ILDR). Finally, the set-point tracking performance specification and ILDR specification can be quantitatively achieved by conveniently tuning the adjustable parameters. Numerical simulations are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper studies the leader-follower formation control of underactuated surface vehicles with model uncertainties and environmental disturbances. A parameter estimation and upper bound estimation based sliding mode control scheme is proposed to solve the problem of the unknown plant parameters and environmental disturbances. For each of these leader-follower formation systems, the dynamic equations of position and attitude are analyzed using coordinate transformation with the aid of the backstepping technique. All the variables are guaranteed to be uniformly ultimately bounded stable in the closed-loop system, which is proven by the distribution design Lyapunov function synthesis. The main advantages of this approach are that: first, parameter estimation based sliding mode control can enhance the robustness of the closed-loop system in presence of model uncertainties and environmental disturbances; second, a continuous function is developed to replace the signum function in the design of sliding mode scheme, which devotes to reduce the chattering of the control system. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this note, the authors study the tracking problem for uncertain nonlinear time-delay systems with unknown non-smooth hysteresis described by the generalised Prandtl–Ishlinskii (P-I) model. A minimal learning parameters (MLP)-based adaptive neural algorithm is developed by fusion of the Lyapunov–Krasovskii functional, dynamic surface control technique and MLP approach without constructing a hysteresis inverse. Unlike the existing results, the main innovation can be summarised as that the proposed algorithm requires less knowledge of the plant and independent of the P-I hysteresis operator, i.e. the hysteresis effect is unknown for the control design. Thus, the outstanding advantage of the corresponding scheme is that the control law is with a concise form and easy to implement in practice due to less computational burden. The proposed controller guarantees that the tracking error converges to a small neighbourhood of zero and all states of the closed-loop system are stabilised. A simulation example demonstrates the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this note, a general scheme is proposed for the high order unstable delay process with one or more positive poles, using the mirror mapping technique. The Nyquist criteria is employed to establish a systematic methodology to tune the parameter. The stabilizing parameter region could guarantee the prespecified robustness specification. In the scheme, a control law is designed based on the all-pole Padé approximated model. The unstable process was first mapped into a minimum-phase system, and the actual control is obtained by the closed-loop gain shaping algorithm (CGSA). The advantages are that one has a concise design procedure and can achieve good performance such as disturbance rejection and robustness. Finally, three highly cited examples are used to illustrate the effectiveness of the proposed method. [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]

This paper focuses on the real time intelligent navigation scheme for unmanned surface vehicle (USV) subject to collision avoidance regulations. The proposed approach is formulated as two segments: the real time guidance principle with COLREGS-compliant collision avoidance mechanism and the finite-time adaptive event-triggered control algorithm. The pointed improvement for the artificial potential field (APF) can guarantee USV possess the excellent avoidance function in accordance with COLREGS regulations. Especially, when the obstacle makes dangerous actions, the emergency obstacle avoidance operation (EOAO) is implemented according to the real time position of obstacles. Based on the proposed guidance principle, a finite-time robust neural control algorithm is developed by fusion of the finite-time stability theory and event-triggered mechanism. The intermittent computing and communication can effectively reduce the energy and resource consumption of the control system. Moreover, the finite-time adaptive controller design contributes to smaller computation load and facilitates the implementation of the algorithm in ocean engineering. The semi global finite-time uniformly boundedness (SGFTUB) of the closed-loop system is guaranteed through the Lyapunov theory. Finally, the numerical simulation and comparison experiment are illustrated to verify the guidance and control performance of the proposed algorithm. • This paper proposes a novel real-time intelligent navigation strategy subject to collision avoidance regulations is proposed. • Pointed improvement for APF can guarantee USV possess the excellent avoidance function with COLREGS regulations. • When other vehicle failed to make collision avoidance action, the EOAO mechanism will be implemented that uses relative position. • Finite-time adaptive controller contributes to smaller computation load. [ABSTRACT FROM AUTHOR]

This paper studies a time-varying formation control problem of a swarm of autonomous surface vehicles (ASVs) with prescribed constraints. Every ASV suffers from unavailable velocities, saturated inputs, internal uncertainties, and external disturbances. A distributed finite-time performance-prescribed time-varying formation control method is proposed for ASVs. Specifically, an adaptive fuzzy state observer (AFSO) is firstly proposed to recover the unavailable velocity by using saturated inputs and estimated disturbances from the fuzzy logic system. Secondly, a tunnel prescribed performance (TPP) function is designed to limit tracking errors with a concise form and smaller overshoot. At the kinematic level, with TPP-based error transformation, a C 1 finite-time time-varying guidance law is proposed by using the smooth switch functions and recovered velocities. Next, a finite-time command filter based on Levant differentiator is presented to smooth the guidance signals. At the kinetic level, a C 1 finite-time saturated control law is developed with the estimated velocities and disturbances. Then, it proves that tracking errors of the proposed closed-loop system converge into a small neighborhood around the equilibrium within finite time while evolving under TPP constraints regardless of saturated inputs. Finally, comparison results are provided to demonstrate the effectiveness of the proposed distributed finite-time performance-prescribed time-varying formation control method. • Distributed finite-time performance-prescribed formation control method is proposed for ASVs. • The TPP with a concise form is developed to achieve smaller overshoot in a positive manner. • An adaptive fuzzy state observer is designed to recover unavailable velocities. [ABSTRACT FROM AUTHOR]

This paper is concerned with a coordinated search and rescue problem of heterogeneous ocean vehicle cluster composed of autonomous surface vehicles (ASVs) and autonomous underwater vehicles (AUVs) subject to model uncertainties and ocean disturbances. Firstly, a three dimensions (3D) cross domain kinematic controller with auto-stop function at the rescue points is designed for the coordinated ASV-AUV system by using a line-of-sight guidance law. Secondly, an event-triggered based communication mechanism is constructed to ensure that the ASV-AUV system can broadcast information at its trigger moments except to the auto-stop points. Finally, an adaptive motion control law based on a low-frequency learning fuzzy predictor is designed, which is able to filter out the high-frequency components of uncertainties and disturbances. The stability of the closed-loop system is proven by employing input-to-state stability and cascade stability analysis. Simulation results and numerical analysis show the effectiveness of the proposed 3D heterogeneous cross domain coordinated path following controller with auto-stop function for marine search and rescue. • In contrast to the existing coordinated path following controllers which applicable to a two-dimensional or three-dimensional coordinated control in the same domain, a three-dimensional cross domain coordinated controller with auto-stop function applicable to sea surface and underwater scenarios are constructed. • In contrast to the existing communication that cannot stop during the whole control period, a predictor-based event-triggered communication mechanism is proposed such that the narrow network band could be effectively alleviated, and the communication will be suspended at the rescue points. • In contrast to the existing predictor design methods, a low-frequency learning fuzzy predictors are presented not only to filter out high-frequency components of non-linearities uncertainties and unmodeled random external disturbances, but also to achieve fast adaptation. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of finite-time trajectory tracking for fully actuated autonomous surface vehicles without the velocity measurements, in the presence of uncertain parameters and complex environmental disturbances. Firstly, a generalized nonlinear finite-time extended state observer is proposed to recover the velocities and synthetic disturbances simultaneously. The generalized structure can further enhance the estimation accuracy and the observation errors are proved to be finite-time uniformly ultimately bounded stable. Then, a two-loop control law is developed by using virtual velocity command and fast non-singular integral terminal sliding controller. The observer is integrated with the controller to overcome the problem of unavailable surge, sway, yaw velocities and to rapidly reject disturbances, thereby contributing to fast and accurate trajectory tracking of the vehicle. Theoretical analysis for finite-time stability of the closed-loop system is rigorously derived through the Lyapunov's stability theory. Finally, comparative simulation results are given to illustrate the effectiveness and superiority of the proposed control approach. • A GNFTESO is proposed to observe the velocities and external disturbances accurately. • The GNFTESO can estimate the unavailable information in body-fixed frame using the position-heading measurements of the inertial frame. • Tracking errors of the ASV are forced to enter a small neighborhood of the origin in a finite time. • High accuracy, faster convergence, and continuous structure are remarkable features. [ABSTRACT FROM AUTHOR]

Considering navigation scenarios in elaborate waters, the high-precision waypoints-based path-following problem of underactuated surface vessel (USV) is investigated by combining the iterative learning control (ILC) and the artificial potential field (APF) in this note. A potential-based dynamic virtual ship (DVS) guidance, considering the challenge of preventing collisions with irregular barriers, is designed with the path following module and the collision avoidance module. A virtual potential field is constructed in the guidance strategy to provide the desired heading signal In particular, the desired heading signal will force that to navigate to one secure location, where the USV approaches the barrier. On the basis of guidance, the iterative control algorithm is selected to design the controller of the system due to the advantages of high accuracy. The dynamic surface control (DSC) and the robust neural damping techniques are utilized to constraint the intrinsic problem of "explosion of complexity" in ILC. The merits of the method involve concise form and controllable precision. Through the Lyapunov criterion, the corresponding closed-loop system is with the semi-global uniformly ultimately bounded (SGUUB) stability. The simulation results are illustrated to verify the effectiveness of the proposed algorithm. • The improved iterative learning control algorithm is proposed for USV. • A potential-based guidance is designed to prevent collisions with irregular barriers. • The proposed algorithm is with merits of concise form and controllable precision. • The closed-loop system is semi-global uniformly ultimately bounded. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive event-triggered control algorithm for sail-assisted unmanned surface vehicle (USV) under nonlinear modified logic virtual ship (LVS) guidance, which addresses the issues of communication load and input saturation constraint. In guidance module, the reference signal generated by LVS guidance is further processed by nonlinear modification rules. That can effectively remove the abrupt phenomenon of actuators. In the control module, a robust adaptive control technique for sail-assisted USV is proposed by fusing adaptive compensation technology and hybrid threshold event-triggered. Unnecessary transmission is reduced between controller and actuator by constructing hybrid threshold event-triggered mechanism. Different from most existing event-triggered mechanism with fixed threshold parameters, threshold parameters in hybrid threshold event-triggered are dynamically adjusted according to the demands of the controller. Furthermore, the compensation effect of sail on the dynamic mechanism is considered. Adaptive parameters of rudder and propeller are constructed to improve the robustness of the closed-loop system. Finally, the theoretical stability of the proposed method is proved by Lyapunov stability theorem, and the control performance is evaluated by simulation platform, which verifies that the scheme has reliable tracking accuracy under time-varying disturbances. • The nonlinear modified LVS principle is proposed to improve sail acting performance. • The hybrid threshold parameter setting can obtain satisfactory resource efficiency. • It can be effectively released the coupling effect of sail force on power mechanism. • The triggered state variables are semi-globally uniform ultimate bounded stable. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic event-triggered control algorithm for the unmanned sailboat robot (USR) to carry out the waypoints-based path-following mission. The proposed scheme consists of the guidance module and control one. For the guidance module, the improved logic virtual ship (LVS) guidance law is proposed to plan the reference route for the USR considering the marine environment with time-varying wind direction. The navigation zones for USR are divided into crosswind zone and non-crosswind zone. It is beneficial for the sailboats to achieve tracking and gybe in different navigation zones. As for the control part, the dynamic event-triggered control is proposed by setting tuning threshold parameter. It is advantageous to decrease the resource waste and channel occupancy. Compared with the existing event-triggered control with static threshold parameter, the proposed algorithm is with the better performance in data transmission. The closed-loop control system has been proved to be with the semi-global uniform ultimate bounded (SGUUB) stability. Finally, the simulation experiment illustrates the superiorities of the proposed algorithm. • An improved logic virtual ship (LVS) principle is developed considering the time-varying ocean environment. • A dynamic event-triggered mechanism is designed for USR by using the minimum threshold setting. • The more accurate control effect can be achieved by asynchronous triggered of sail angle and rudder angle. [ABSTRACT FROM AUTHOR]

A crucial and challenging issue in path following control of the autonomous surface vehicle (ASV) is input constraint and communication burden. In this paper, an intervened logic virtual ship (ILVS) guidance is developed to generate the reference signal, and further to tackle the input saturation constraint by employing the dynamic feedback evaluation rule. The main superiority of this design is to intervene the logic virtual ship (LVS) guidance principle to avoid the persistent large stabilization error. Associated with ILVS guidance framework, a robust adaptive neural event-triggered algorithm is proposed for the ASV by fusing the adaptive technique and the multiport event-triggered approach. The constrains of the model nonlinear term and the uncertain actuators gain are released by constructing online learning parameters. Furthermore, the channel resource from the sensor to the controller (SC) as well as the controller to the actuator (CA) is reduced for merits of the multiport event-triggered approach. The feedback error signals and the control inputs will be updated while the triggered condition is occurred. That also can eliminate the low frequency disturbance, caused by marine environment, to improve the robustness of the closed-loop system. Through the Lyapunov stability criterion, all state variables in the triggered point and triggered interval are achieved semi-global uniform ultimate bounded (SGUUB) stability. Finally, the control performance of the proposed method is evaluated on simulation platform, showing the satisfied tracking accuracy with the low transmission load. • The robust adaptive neural event-triggered control algorithm is proposed for the autonomous surface vehicle (ASV). • The developed intervened logic virtual ship (ILVS) guidance can generate the reference signal, and further to tackle the input saturation constraint. • The computing resource from the sensor to the controller, the transmission load from the controller to the actuator are reduced simultaneously. • All the state variables in the triggered point and triggered interval are achieved semi-global uniform ultimate bounded (SGUUB) stability. [ABSTRACT FROM AUTHOR]

This paper investigates an improved event-triggered robust adaptive control algorithm for the marine surface vehicle with the fault compensating mechanism. A dynamic event-triggered mechanism is designed with a concise form to reduce the updating frequencies of the system state. Different from the exiting results, the proposed algorithm can ensure that both the controller and the state transmitter are activated synchronously only at the triggering instants. That can ameliorate the communication obstruction in both the channels of sensor-to-controller and controller-to-actuator. To improve the fault-tolerant capability of the theoretical algorithm, gain-related adaptive parameters are derived to compensate for gain uncertainties and possible actuator faults. In addition, a compensating term via the robust neural damping technique is introduced to stabilize the unpredictable perturbation from the model uncertainties and the external disturbance. Through the Lyapunov criterion, the corresponding closed-loop system is with the semi-global uniformly ultimately bounded (SGUUB) stability. The simulation results are illustrated to verify the effectiveness of the algorithm. • An event-triggered robust adaptive fault-tolerant control algorithm is proposed for marine vehicles. • A concise dynamic event-triggered condition is designed to guarantee an effective tradeoff. • The communication burden can be largely reduced in both the channels of the sensor-to-controller and the controller-to-actuator. [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 investigates a novel robust adaptive fault-tolerant control algorithm for the path-following activity of the unmanned surface vehicle (USV) via the multiplied event-triggered mechanism. An improved multiplied event-triggered condition is designed by employing the estimate model with a concise form. Thus, the burden-some problem is released, especially for the channel from sensors to the controller. Besides, two discrete adaptive parameters are constructed to stabilize the perturbation caused by the gain constraint and actuator faults. The model uncertainties and the practical disturbance are compensated by utilizing neural networks (NNs) approximation, in which the weight updating is reduced with the robust neural damping technique. With the direct Lyapunov theorem, the semi-global uniformly ultimately bounded (SGUUB) stability can be guaranteed for the closed-loop system. Finally, both the simulation and the physical vehicle-based experiments are illustrated to verify the effectiveness of the algorithm. • A robust fault-tolerant control algorithm is proposed for unmanned surface vehicle. • The adaptive parameters are updated online to compensate for unknown actuator faults. • An improved multiplied event-triggered condition is designed with a concise form. • It can evade the unnecessary information transmission of the onboard control network. [ABSTRACT FROM AUTHOR]

This note investigates an event-triggered robust adaptive control for path following of the unmanned robot sailboat (URS) by employing the proportional integral sliding mode manifold and the robust neural damping technique in presence of marine practice. The dominant assignment of this note can be summarized into three points: (1) The double-layer virtual guidance is developed to generate the reference signal for three navigation conditions (i.e., the upwind sailing, the downwind sailing and the crosswind sailing). That can enhance the navigating automatism of the URS while the tacking and the gybing. (2) The system uncertainties are approximated by the radial basis function neural networks (RBF-NNs). To further simplify the controller form, the robust neural damping technique has been introduced to evade the updated information of the neural weights. Furthermore, the input saturation of the closed-loop control system is tackled by constructing the auxiliary variable in the control design. (3) The communication burden in the channel from the controller to the actuator can be reduced for merits of the event-triggered rule. Besides, the system chattering, caused by the marine disturbances has also been reduced through the proportional integral sliding mode manifold and gain-related adaptive law. The tracking errors of the closed-loop control system will converge to a compact set, and all the signals satisfy the semi-global uniformly ultimately bounded (SGUUB) stability. Finally, the effectiveness and the robustness of the proposed algorithm have been demonstrated via the numerical simulations under the simulated marine environment. • An event-triggered robust adaptive control is proposed for unmanned robot sailboat. • The corresponding guidance is designed for upwind, crosswind and downwind conditions. • The input saturation is tackled by the auxiliary variable in the control design. • The proposed algorithm is with lower communication burden and no chattering action. [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]

This paper investigates the practical finite time control problem with uncertain parameters, external disturbances, and input saturation for quad-copter unmanned aerial vehicle systems. Firstly, an adaptive robust controller based on backstepping with fast terminal sliding mode control is designed for the major control loops. Secondly, only four adaptation laws are used to estimate the quad-copter uncertain parameters while a projector algorithm is used to guarantee the estimation within a prescribed range. Thirdly, an adaptive switching gain is developed to compensate the lumped disturbances. Finally, a compensator term is introduced in control design to reduce the adverse effect caused by the input saturation. The proposed control scheme can attenuate chattering phenomenon and guarantee that all states of the closed-loop system are practical finite time stable. The validity of the proposed flight control system is confirmed by using several flight scenarios under various conditions and a comparison study with other works is made showing the effectiveness, robustness, adaptiveness, and energy efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]