The dynamic surface control (DSC) technique was developed recently by Swaroop et al. This simplified the backstepping design for of nonlinear systems in strict-feedback form overcoming problem "explosion complexity." It later extended to adaptive with linearly parameterized uncertainty. In this paper, incorporating into a neural network based framework, we have class arbitrary Our development is able eliminate complexity" inherent existing method. addition, stability analysis given which...

A robust adaptive tracking control approach is presented for a class of strict-feedback single-input-single-output nonlinear systems. By employing radial-basis-function neural networks to account system uncertainties, the proposed scheme developed by combining ¿dynamic surface control¿ and ¿minimal learning parameter¿ techniques. The key features algorithm are that, first, problem ¿explosion complexity¿ inherent in conventional backstepping method avoided, second, number parameters updated...

Autonomous surface vehicles (ASVs) are marine vessels capable of performing various operations without a crew in variety cluttered and hostile water/ocean environments. For complex missions, there increasing needs for deploying fleet ASVs instead single one to complete difficult tasks. Cooperative with offer great advantages enhanced capability efficacy. Despite application potentials, coordinated motion control pose challenges due the multiplicity ASVs, complexity intravehicle interactions...

In this brief, we consider the formation control problem of underactuated autonomous surface vehicles (ASVs) moving in a leader-follower formation, presence uncertainties and ocean disturbances. A robust adaptive controller is developed by employing neural network dynamic technique. The stability design proven via Lyapunov analysis where semiglobal uniform ultimate boundedness closed-loop signals guaranteed. advantages proposed are that: first, method only uses measurements line-of-sight...

This brief is concerned with the distributed maneuvering of multiple autonomous surface vehicles guided by a virtual leader moving along parameterized path. In guidance loop, law developed incorporating constant bearing strategy into path-maneuvering design such that prescribed formation pattern can be reached. To optimize signal under velocity constraint as well minimize control torque during transient phase, an optimization-based command governor employed to generate optimal for vehicle...

In this paper, a cooperative time-varying formation maneuvering problem with connectivity preservation and collision avoidance is investigated for fleet of autonomous surface vehicles (ASVs) position-heading measurements. Each vehicle subject to unknown kinetics induced by internal model uncertainty external disturbances. At first, nonlinear state observer used recover the unmeasured linear velocity yaw rate as well Then, observer-based control laws are designed based on artificial potential...

In this paper, a neurodynamics-based output feedback scheme is proposed for distributed containment maneuvering of marine vessels guided by multiple parameterized paths without using velocity measurements. Each vessel subject to internal model uncertainties and external disturbances induced wind, waves, ocean currents. order recover unmeasured information as well identify unknown dynamics, an echo state network (ESN) based observer recorded input-output data each vessel. Based on the...

This paper presents a novel extended state observer (ESO)-based line-of-sight guidance law for path following of underactuated marine surface vehicles in the presence time-varying sideslip angle. A reduced-order ESO is employed to identify vehicle angle caused by constant ocean disturbances when curved or disturbances. guarantees that can be timely and exactly estimated, thus contributes desired with higher accuracy regardless external induced wind, waves, currents. The input-to-state...

This paper addresses the leader–follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive controllers are proposed based on state information neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring accurate model each agent. result further extended to output feedback case where a neighborhood observer relative Then, distributed observer-based derived...

This paper presents an adaptive output-feedback neural network (NN) control scheme for a class of stochastic nonlinear time-varying delay systems with unknown directions. To make the controller design feasible, coefficients are grouped together and original system is transformed into new using linear state transformation technique. Then, Nussbaum function technique incorporated backstepping recursive to solve problem Furthermore, under assumption that delays exist in output, only one NN...

In this paper, a leader-following consensus scheme is presented for networked uncertain nonlinear strict-feedback systems with unknown control directions under directed graphs, which can achieve predefined synchronization error bounds. Fuzzy logic are employed to approximate system uncertainties. A specific Nussbaum-type function introduced solve the problem of directions. Using dynamic surface technique, distributed controllers developed guarantee that outputs all followers synchronize...

This paper presents a predictor-based neural dynamic surface control (PNDSC) design method for class of uncertain nonlinear systems in strict-feedback form. In contrast to existing NDSC approaches where the tracking errors are commonly used update network weights, predictor is proposed every subsystem, and prediction employed adaptation laws. The scheme enables smooth fast identification system dynamics without incurring high-frequency oscillations, which unavoidable using classical methods....

The containment maneuvering of marine surface vehicles has two objectives. first one is to force the follow a convex hull spanned by multiple parameterized paths. second meet requirement desired dynamic behavior along paths during containment. A modular design approach presented. At first, an estimator module using recurrent neural network proposed estimate unknown kinetics induced model uncertainty, unmodeled dynamics, and environmental disturbances. Next, controller developed based on...

This paper is concerned with the target tracking of underactuated autonomous surface vehicles unknown dynamics and limited control torques. The velocity unknown, only measurements line-of-sight range angle are obtained. First, a kinematic law designed based on an extended state observer, which utilized to estimate uncertain due velocities. Next, estimation model single-hidden-layer neural network developed approximate follower induced by parameters, unmodeled dynamics, environmental...

Autonomous marine vehicles (AMVs), including autonomous surface and underwater vehicles, are versatile means to explore, exploit, monitor, protect resources environments. Motion control is a fundamental enabling technique for state-of-the-art AMV development. Especially, guidance critical component in motion control. In recent years, line-of-sight (LOS) guidance, as an efficient method, has attracted tremendous interest from both theoretical practical perspectives. this paper, overview of...

This article addresses the distributed path maneuvering of underactuated unmanned surface vehicles (USVs) with collision avoidance and connectivity preservation. The USVs are guided by multiple virtual leaders moving along parameterized paths only a fraction have access to leaders. An observer-based finite-time control method is proposed achieve containment formation. Specifically, extended state observer employed recover unmeasured linear/angular velocities estimate total disturbances...

This article addresses the problem of distributed path following multiple under-actuated autonomous surface vehicles (ASVs) with completely unknown kinetic models. An integrated guidance and learning control architecture is proposed for achieving a time-varying formation. Specifically, robust law at kinematic level developed based on consensus approach, path-following mechanism, an extended state observer. At level, model-free data-driven neural predictors via integral concurrent designed...

An adaptive output feedback control is studied for uncertain nonlinear single-input-single-output systems with partial unmeasured states. In the scheme, a reduced-order observer (ROO) designed to estimate those By employing radial basis function neural networks and incorporating ROO into new backstepping design, an controller constructively developed. A prominent advantage its ability balance action between state feedback. addition, scheme can be still implemented when all states are not...

Abstract In this paper, by incorporating the dynamic surface control technique into a neural network‐based adaptive design framework, we have developed backstepping‐based for class of nonlinear systems in pure‐feedback form with arbitrary uncertainty. The circular problem which may exist is overcome. addition, our development able to eliminate ‘explosion complexity’ inherent existing methods. A stability analysis given, shows that law can guarantee semi‐global uniformly ultimate boundedness...

This paper addresses the cooperative path following problem of ring-networked under-actuated autonomous surface vehicles on a closed curve. A guidance law is proposed at kinematic level such that symmetric formation pattern achieved. Specifically, individual laws surge speed and angular rate are developed by using backstepping technique line-of-sight method. Then, coordination design to update variables under topology. The equilibrium point closed-loop system has been proven be globally...