In this paper, adaptive impedance control is developed for an n-link robotic manipulator with input saturation by employing neural networks. Both uncertainties and are considered in the tracking design. order to approximate system uncertainties, we introduce a radial basis function network controller, handled designing auxiliary system. By using Lyapunov's method, design controllers. state output feedbacks constructed. To verify proposed control, extensive simulations conducted.

In this paper, we consider the trajectory tracking of a marine surface vessel in presence output constraints and uncertainties. An asymmetric barrier Lyapunov function is employed to cope with constraints. To handle system uncertainties, apply adaptive neural networks approximate unknown model parameters vessel. Both full state feedback control are proposed paper. The law designed by using Moore-Penrose pseudoinverse case that all states known, high-gain observer. Under method controller...

In this paper, we present adaptive neural network tracking control of a robotic manipulator with input deadzone and output constraint. A barrier Lyapunov function is employed to deal the constraints. Adaptive networks are used approximate unknown model manipulator. Both full state feedback considered in paper. For control, high gain observer estimate unmeasurable states. With proposed constraints not violated, all signals closed loop system semi-globally uniformly bounded. The performance...

The work presented here is concerned with the robust flight control problem for longitudinal dynamics of a generic airbreathing hypersonic vehicles (AHVs) under mismatched disturbances via nonlinear-disturbance-observer-based (NDOBC) method. Compared other method AHV, proposed obtains not only promising robustness and disturbance rejection performance but also property nominal recovery. merits are validated by simulation studies.

The research of this paper works out the attitude and position control flapping wing micro aerial vehicle (FWMAV). Neural network with full state output feedback are designed to deal uncertainties in complex nonlinear FWMAV dynamic system enhance robustness. Meanwhile, we design disturbance observers which exerted into via feedforward loops counteract bad influence disturbances. Then, a Lyapunov function is proposed prove closed-loop stability semi-global uniform ultimate boundedness all...

Adaptive neural networks (NNs) are employed for control design to suppress vibrations of a flexible robotic manipulator. To improve the accuracy in describing elastic deflection manipulator, system is modeled via lumped spring-mass approach. Full-state feedback as well output proposed separately. Aiming at achieving objective, uniform ultimate boundedness closed-loop ensured. Numerical simulations model carried out verify performance NN control. Finally, experiments given further validate...

This paper addresses a flexible micro aerial vehicle (MAV) under spatiotemporally varying disturbances, which is composed of rigid body and two wings. Based on Hamilton's principle, distributed parameter system coupling in bending twisting, modeled. Two iterative learning control (ILC) schemes are designed to suppress the vibrations reject disturbances regulate displacement track prescribed constant trajectory. At basis composite energy function, boundedness convergence proved for...

In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking based on action-dependent heuristic dynamic programming (ADHDP). The action is generated by the combination of sliding mode (SMC) and ADHDP controller to track desired velocity altitude. particular, observes differences between actual velocity/altitude velocity/altitude, then provides accordingly. does not rely accurate mathematical model...

In this paper, we study the fixed-time event-triggered consensus problem of uncertain nonlinear multiagent systems. Two controllers are proposed. contrast to finite-time results, convergence time results is independent initial conditions. Furthermore, continuous communications can be avoided both in update and triggering condition monitoring. It proved that there no Zeno behavior under control strategies. The availability algorithms verified by numerical simulations.

In this paper, we investigate fuzzy neural network (FNN) control using impedance learning for coordinated multiple constrained robots carrying a common object in the presence of unknown robotic dynamics and environment with which robot comes into contact. First, an FNN algorithm is developed to identify plant model. Second, introduced regulate input order improve environment-robot interaction, can track desired trajectory generated by learning. Third, light condition requiring move finite...

This brief addresses the fixed-time event/self-triggered leader-follower consensus problems for networked multi-agent systems subject to nonlinear dynamics. First, we present an event-triggered control strategy achieve consensus, and a new measurement error is designed avoid Zeno behavior. Then, two self-triggered strategies are presented continuous triggering condition monitoring. Moreover, under proposed strategies, strictly positive minimal interval of each follower given exclude Compared...

In this paper, the n-dimensional discretized model of two-link flexible manipulator is developed by assumed mode method (AMM). Subsequently, based on dynamic model, both full-state feedback control and output are investigated to achieve trajectory tracking vibration suppression. order guarantee stability strictly, uniform ultimate boundedness (UUB) closed-loop system realized Lyapunov's stability. Furthermore, through appropriately choosing parameters, states will converge zero within a...

A variable length crane system under the external disturbances and constraints is studied in two-dimensional space. The dynamical analysis of cable considers length, tension, speed, coupled vibrations longitudinal-transverse directions. Considering output constraint problems, boundary control algorithms with signal barriers are designed acted on to reduce flexible cable, ensure stability theory. Effectiveness performance proposed schemes depicted via several simulation examples.

In this paper, an event-triggered near optimal control structure is developed for nonlinear continuous-time systems with constraints. Due to the saturating actuators, a nonquadratic cost function introduced and Hamilton-Jacobi-Bellman (HJB) equation constrained formulated. order solve HJB equation, actor-critic framework presented. The critic network used approximate action estimate law. addition, in proposed method, signal transmitted aperiodic manner reduce computational transmission cost....

A data-driven adaptive tracking control approach is proposed for a class of continuous-time nonlinear systems using recent developed goal representation heuristic dynamic programming (GrHDP) architecture. The major focus this paper on designing multivariable scheme, including the filter-based action network (FAN) architecture, and stability analysis in fashion. In design, FAN used to observe system function, then generates corresponding together with reference signals. will provide an...

This paper presents the design of a novel adaptive event-triggered control method based on heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In proposed method, law is only updated when condition violated. Compared periodic updates in traditional (ADP) control, can reduce computation and transmission cost. An actor-critic framework used to learn optimal value function. Furthermore, model network designed estimate state vector. The...

In this article, the problem of asynchronous fault detection (FD) observer design is discussed for 2-D Markov jump systems (MJSs) expressed by a Roesser model. general, FD cannot work synchronously with system, that is, mode varies system in line some conditional transitional probabilities. For dealing difficult point, hidden model (HMM) employed. Then, combining H∞ attenuation index and H_ increscent index, multiobjective solution to formed. terms linear matrix inequality technology,...

This article proposes a hybrid policy-based reinforcement learning (HPRL) adaptive energy management to realize the optimal operation for island group system with transmission-constrained environment. An hub (IEH) model that can cascade utilization is proposed. Compared traditional model, IEH satisfy special demand of island, meanwhile, ensure supply island. Moreover, an islands (EMIG) based on formulated which comprehensively considers inverse distribution and resources, as well limited...

This paper investigates the path following problem of underactuated unmanned surface vehicle systems suffering unknown disturbances. A fixed-time predictor is proposed to approximate sideslip caused by disturbances, which prediction error can converge zero in a fixed time. By selecting appropriate controller parameters, upper bound settling time identified. And it's independent initial conditions, compared with finite-time predictor. In addition, line-of-sight (LOS) guidance law and heading...

Nowadays, the control technology of robotic manipulator with flexible joints (RMFJ) is not mature enough. The flexible-joint dynamic system possesses many uncertainties, which brings a great challenge to controller design. This paper motivated by this problem. In order deal and enhance robustness, full-state feedback neural network (NN) proposed. Moreover, output constraints RMFJ are achieved, improve security robot. Through Lyapunov stability analysis, we identify that proposed can...

The modern power system is evolving towards a new generation of smart grid, with significant benefits from the latest computer-based communication network technologies. Furthermore, as incremental deployment phase measurements units (PMUs) and use Smart Meters, there will be substantial increase real-time measurements. Under this trend, event-triggered control (ETC) play an important role in reducing computation cost. In paper, novel ETC architecture design for load frequency (LFC)...