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...

In this paper, an adaptive fuzzy backstepping dynamic surface control (DSC) approach is developed for a class of multiple-input-multiple-output nonlinear systems with immeasurable states. Using fuzzy-logic to approximate the unknown functions, state observer designed estimate By combining adaptive-backstepping technique and DSC technique, output-feedback backstepping-control developed. The proposed method not only overcomes problem "explosion complexity" inherent in backstepping-design...

In this paper, an adaptive fuzzy backstepping output-feedback tracking control approach is proposed for a class of multi-input and multi-output (MIMO) stochastic nonlinear systems. The MIMO systems under study are assumed to possess unstructured uncertainties, unknown dead-zones, directions. By using linear state transformation, the coefficients slopes characteristic dead-zones lumped together, original system transformed new on which design becomes feasible. Fuzzy logic used approximate...

In this paper, a composite adaptive fuzzy output-feedback control approach is proposed for class of single-input and single-output strict-feedback nonlinear systems with unmeasured states input saturation. Fuzzy logic are utilized to approximate the unknown functions, state observer designed estimate states. By utilizing observer, serial-parallel estimation model established. Based on backstepping dynamic surface technique prediction error between system model, new controller parameters laws...

In this paper, an adaptive fuzzy decentralized output feedback control design is presented for a class of interconnected nonlinear pure-feedback systems. The considered systems contain unknown uncertainties and the states are not necessary to be measured directly. Fuzzy logic employed approximate functions, then state observer designed estimations immeasurable variables obtained. Based on backstepping dynamic surface technique, scheme developed. It proved that all resulting closed-loop...

In this paper, a hybrid fuzzy adaptive output feedback control design approach is proposed for class of multiinput and multioutput strict-feedback nonlinear systems with unknown time-varying delays, unmeasured states, input saturation. First, logic are employed to approximate functions in the system. Next, smooth function used saturation an state observer constructed solve problem states. Based on designed observer, serial-parallel estimation model established. By applying dynamic surface...

This paper is concerned with the event-triggered finite-time control problem for networked switched linear systems by using an asynchronous switching scheme. Not only of boundedness, but also input-output stability considered in this paper. Compared existing results systems, a new type condition proposed. Sufficient conditions are established to guarantee event-based closed-loop both bounded and stable. A set stabilizing controllers designed under It revealed that triggered thresholds...

A novel nonlinear sliding mode control approach dealing with the formation of under-actuated ships is presented in this paper. To avoid singularity problem, state space system partitioned into two regions, one region bounded for terminal and its complement singular that. And a linear auxiliary controller designed trajectories starting from region. With application finite-time stability theory, distributed individual ship to achieve given pattern within finite time. Finally, simulation...

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...

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Robust adaptive-fuzzy-tracking control of a class uncertain multi-input/multi-output nonlinear systems with coupled interconnections is considered in this paper. Takagi–Sugeno (T–S) fuzzy are used to approximate the unknown system functions. A novel adaptive-control scheme developed on basis so-called "dynamic-surface control" and "minimal-learning parameters" techniques. The proposed has...

Autonomous underwater vehicles (AUVs) are submersible controlled by onboard computers. AUV formation is a cooperative control which focuses on controlling multiple AUVs to move in group while executing tasks. In contrast single AUV, multi-AUV represents higher efficiency and better stability for many applications, such as oil gas industries, hydrographic surveys, military missions, etc. To achieve formation, there several key factors, including performance, control, communication capability....

In this paper, an adaptive fuzzy robust output feedback control problem is considered for a class of single-input and single-output nonlinear systems in strict-feedback form. The possess the unstructured uncertainties, unknown dead zone, dynamics they do not assume states being available controller design. design, logic are first used to approximate by utilizing information bounds dead-zone slopes treating time-varying inputs coefficients as system uncertainty, state observer designed...

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 article investigates an adaptive reinforcement learning (RL) optimal control design problem for a class of nonstrict-feedback discrete-time systems. Based on the neural network (NN) approximating ability and RL technique, backstepping controller minimal parameter (MLP) are developed by establishing novel strategic utility function introducing external terms. It is proved that proposed controllers can guarantee all signals in closed-loop systems semiglobal uniformly ultimately bounded...

This article focuses on the containment control problem for nonlinear multiagent systems (MASs) with unknown disturbance and prescribed performance in presence of dead-zone output. The fuzzy-logic (FLSs) are used to approximate function, a observer is estimate external disturbances. Meanwhile, new distributed scheme developed by utilizing adaptive compensation technique without assumption boundary value disturbance. Furthermore, Nussbaum function utilized cope coefficient, which caused...

In this paper, an adaptive neural network (NN) control problem is investigated for discrete-time nonlinear systems with input saturation. Radial-basis-function (RBF) NNs, including critic NNs and action are employed to approximate the utility functions system uncertainties, respectively. previous works, a gradient descent scheme applied update weight vectors, which may lead local optimal problem. To circumvent problem, multigradient recursive (MGR) reinforcement learning proposed, utilizes...

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...

This article investigates the model-free fault-tolerant containment control problem for multiagent systems (MASs) with time-varying actuator faults. Depending on relative state information of neighbors, a distributed method based reinforcement learning (RL) is adopted to achieve objective without prior knowledge system dynamics. First, agent itself and its error established. Then, optimal transformed into an regulation system. Furthermore, RL-based policy iteration employed deal...

This paper proposes a novel fault tolerant control strategy for dynamic positioning of unmanned marine vehicles using the quantized feedback sliding mode technique. Due to complex ocean environment, are modeled as Takagi-Sugeno fuzzy system with unknown membership functions. When functions not available, traditional technique becomes infeasible. To tackle this difficulty, based on switching mechanism is designed compensate thruster faults effects. In addition, phenomenon time-varying delay...

This article proposes an adaptive neural-network command-filtered tracking control scheme of nonlinear systems with multiple actuator constraints. An equivalent transformation method is introduced to address the impediment from nonlinearity. By utilizing command filter method, explosion complexity problem addressed. With help approximation, backstepping strategy via technique and design algorithm proposed. Based on this scheme, boundedness all variables guaranteed output error fluctuates...

In some crucial consensus tracking missions, the sign of error is not allowed to change during process. The existing control schemes are unable satisfy this requirement. To solve issue, work improves conventional prescribed performance (PPC) approach and applies it cooperative unmanned aircraft vehicle (UAV) systems. Moreover, flight controller design incorporates human decision-making. This hybrid active interaction implies that humans UAVs can execute complex variable missions as a...

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This article develops continuous and periodic event-triggered sliding-mode control (SMC) algorithms for path following of underactuated surface vehicles (USVs). Based on the SMC technology, a path-following law is designed. The upper bounds quasi-sliding modes USVs are established first time. Subsequently, both mechanisms considered added into proposed scheme. It demonstrated that with appropriate selecting parameters, use hyperbolic tangent functions does not affect boundary layer mode...