In this paper, a neural network (NN) controller is designed to suppress the vibration of flexible robotic manipulator system with input deadzone. The NN aims approximate unknown dynamics and eliminate effects deadzone in actuators. order describe more accurately, model constructed based on lumping spring-mass method. Full state feedback control proposed first output high-gain observer then devised make scheme practical. effect approximated by radial basis function (RBFNN) another RBFNN. able...

This paper investigates adaptive neural control methods for robotic manipulators, subject to uncertain plant dynamics and constraints on the joint position. The barrier Lyapunov function is employed guarantee that are not violated, in which Moore-Penrose pseudo-inverse term used design. To handle unmodeled dynamics, network (NN) adopted approximate dynamics. NN based full-state feedback robots proposed when all states of closed loop known. Subsequently, only robot measurable practice; output...

In this paper, a study of control for an uncertain 2-degree freedom (DOF) helicopter system is given. The 2-DOF subject to input deadzone and output constraints. order cope with uncertainties deadzone, the neural network technique introduced because its capability in approximation. update weights network, adaptive method utilized improve adaptability. Furthermore, integral barrier Lyapunov function (IBLF) adopt design guarantee condition constraints boundedness corresponding tracking errors....

In this article, quadrotor unmanned aerial vehicles (QUAVs) are organized as a two-layer structure, where the first layer is leader QUAVs and second follower QUAVs. only can receive desired tracking information of position attitude. Although followers cannot obtain given directly, they corresponding from leaders other through communication network based on graph theory. terms case, distributed formation-containment (FC) control method proposed to handle related flight problems. We aim...

In this study, the authors focus on reinforcement learning control of a single‐link flexible manipulator and attempt to suppress vibration due its flexibility lightweight structure. The assumed mode method Lagrange's equation are adopted in modelling enhance satisfaction precision. Two radial basis function neural networks (NNs) employed designed algorithm, actor NN for generating policy critic evaluating cost‐to‐go. Rigorous stability system has been proven via Lyapunov's direct method....

In this article, the optimal control problem for robotic manipulators (RMs) with prescribed constraints is addressed. Considering environmental conditions and requirements of practical applications, are imposed on system states to guarantee performance normal operation system. Accordingly, an error transformation function adopted cope generate equivalent unconstrained convenience intelligent design. order improve learning ability optimize performance, critic (CL) introduced design...

In this paper, a finite-time, active fault-tolerant control (AFTC) scheme is proposed for class of autonomous surface vehicles (ASVs) with component faults. The designed AFTC framework based on an integrated design fault detection (FD), estimation (FE), and controller reconfiguration. First, nominal the Barrier Lyapunov function presented, which guarantees that tracking error converges to predefined performance constraints within settling time. Then, performance-based monitoring low...

A neural learning-based finite-time control policy is presented for a robotic manipulator with unknown backlash-like hysteresis and system uncertainties. Adaptive networks are adopted to deal dynamics. In order eliminate the effect of hysteresis, robust adaptive term designed in backstepping design process. network-based controller by introducing fractional term, which guarantees convergence both terms, this type improves accuracy certain extent. With Lyapunov stability theory, proposed...

This study focuses on vibration control design of a flexible single‐link manipulator (FSLM) system and discusses its application an experimental platform. A spatiotemporal mathematic model is presented to formulate dynamical behaviour the FSLM system, only boundary controller mounted hub designed drive link for tracking given angular position reduce elastic deflection simultaneously. Under scheme, states are ensured converge exponentially equilibrium position. Moreover, numerical simulations...

This paper investigates the tracking control problem for unmanned underwater vehicles (UUVs) systems with sensor faults, input saturation, and external disturbance caused by waves ocean currents. An active fault-tolerant scheme is proposed. First, developed method only requires inertia matrix of UUV, without other dynamic information, can handle both additive multiplicative faults. Subsequently, an adaptive controller designed to achieve asymptotic UUV employing robust integral sign error...

In this brief, we focus on the tracking control problem of unmanned marine vessel (UMV) system with uncertainty and external disturbance. order to resist adverse effect each other between UMV states, a time-synchronized method is proposed handle coupling problem, which can guarantee that all states achieve convergence at same time. design, estimator designed problems Furthermore, stability analysis given prove feasibility control. Finally, simulations practical model are conducted illustrate...

Abstract The article introduces an innovative adaptive fixed‐time control strategy designed for a robot system grappling with challenges like actuator saturation and model uncertainty. Two strategies are explored: model‐based neural networks control. In instances of uncertainty, leveraged to contend the unknown dynamics system. These undergo training approximate elusive parameters. Through this network approach, we establish laws grounded in convergence, ensuring that tracking errors...

In this paper, we focus on the reinforcement learning control of a single-link flexible manipulator and attempt to suppress vibration due its flexibility lightweight structure. The assumed mode method (AMM) Lagrange's equation are adopted in modeling enhance satisfaction precision. Two radial basis function neural networks (RBFNNs) employed designed algorithm, actor network (NN) for generating policy critic NN evaluating cost-function. Rigorous stability system has been proven via Lyapunov's...

In this paper, an adaptive neural control method with coupled input constraint for a two degrees of freedom(DOF) uncertain robotic system is studied. A transformation matrix proposed to handle the problem. The constrained problem transformed into uncoupled incorporation network techniques aimed at addressing uncertainty 2-DOF robot system. An analysis based on Lyapunov stability theory given illustrate constraint. addition, simulations are conducted further prove feasibility and...

A simple adaptive control scheme using neural networks is applied to DC drives through simulation and real-time experimental studies. The primary objective of the paper demonstrate effectiveness this for different operating conditions. consists two parts. One a estimator which used estimate dynamics drive system under control. other controller generate signal so that pre-defined output regulated desired value. Simulation results are presented scheme.