In this technical note, the problem of event-trigger based adaptive control for a class uncertain nonlinear systems is considered. The nonlinearities system are not required to be globally Lipschitz. Since contains unknown parameters, it difficult task check assumption input-to-state stability (ISS) with respect measurement errors, which in most existing literature. To solve problem, we design both controller and triggering event at same time such that ISS no longer needed. addition...

In this paper, we investigate the problem of output feedback control for a class uncertain nonlinear systems with event-triggered input. The considered system contains not only unknown parameters, but also general functions that are required to be globally Lipschitz, in contrast most existing results area. Besides providing two different strategies without input-to-state stable assumption respect measurement errors, propose new way encode and decode signals further decrease communication...

Unknown failures and time delays of actuators which may degrade system performance seem inevitable in practical systems. However, the available results to compensate for unknown delay based on adaptive approaches are very limited. In this paper, we address such a problem by considering controlling class second-order systems with actuator input delays. Firstly, controlled is transformed into triangular structure model. Meanwhile, dynamics output signal. Then, an controller developed using...

In this paper, the event-triggered control problem is investigated using backstepping techniques for nonlinear systems with dead-zone input. The external disturbance and unknown parameters are also considered in controller’s design. It well known that errors input signal measurements inevitable. control, such will directly affect whether updated. This measurement error can be seen form of interference to threshold. Therefore, unlike traditional existence threshold proposed controller not...

Abstract It is well known that unknown modeling errors cannot be avoided in practice. Such unmeasured uncertainties are usually denoted as nonlinear functions exist every channel of the system equation. This paper aims to develop an output feedback adaptive control scheme by constructing state estimation filters address such errors. In controller design, these caused will accumulated last step for compensation. Unknown parameters existing upper bound and estimated synchronously based on...

This paper addresses the problem of quantized feedback control nonlinear Markov jump systems (MJSs). The plant is represented by a class fuzzy MJSs with time-varying delay based on Takagi-Sugeno model. signal utilized for purpose and sector bound approach exploited to deal quantization errors. By constructing Lyapunov function which depends both mode information basis functions, reciprocally convex used derive criterion able ensure stochastic stability predefined l2-l∞ performance resulting...

Hysteresis exists in a wide range of physical actuators. Furthermore, such actuators may be subject to failures or faults which are often uncertain time, value and pattern during system operation. However, the available results based on adaptive approaches compensate for unknown hysteretic very limited. The work this note is aimed at addressing problem by considering controlling class strict feedback systems. A scheme designing smooth control proposed purpose. It shown that designed...

In this technical note, a robust adaptive control scheme is proposed based on backstepping techniques for class of nonlinear systems with unknown parameters. A modeling error may also exist in every state equation or channel and it bounded by known function which allowed to depend all system states. It shown that the can ensure signals closed-loop bounded, if strength errors sufficiently weak. Transient performance established. Thus stabilizing classical strict-feedback forms small...

In this article, a decentralized adaptive control scheme is proposed based on backstepping techniques for class of uncertain interconnected systems with unknown modeling errors and interactions. Unlike existing results, the functions bounding interactions are not required to meet triangular condition. Namely, such allowed depend all states system. It shown that can ensure signals in closed-loop system bounded. Simulation studies verify effectiveness scheme.

In this paper, a new robust adaptive control scheme is proposed for class of nonlinear systems with external disturbance and output modeling error. The error considered here allowed to depend on all states. Thus, traditional backstepping techniques cannot be used in the controller design due such an unknown existing coordinate changes. This problem has been solved by developed scheme. By establishing upper bound function depending system states, linear inequality relationship between state...

In this paper, we propose a robust tracking control scheme for class of uncertain strict-feedback nonlinear systems. these systems, the signal is quantized by sector-bounded quantizers including well-known hysteresis quantizer and logarithmic quantizer. Compared with existing results in input-quantized control, proposed can systems non-global Lipschitz nonlinearities unmatched uncertainties caused model external disturbances. It shown that designed controller ensures global boundedness all...

Summary This paper addresses the problem of dissipativity‐based asynchronous control for a class discrete‐time Markov jump systems. A unified framework to design controller systems with mixed time delays is proposed, which fairly general and can be reduced synchronous or mode‐independent controller. Based on stochastic Lyapunov function approach, fully utilizes available information system mode controller, sufficient condition established ensure stability strictly ( , ) dissipative...

In this paper, a neural network-based adaptive iterative learning control scheme is developed to solve the trajectory tracking problem for rigid robot manipulators with arbitrary initial errors. Time-varying boundary layers are used relax zero error condition which must be observed in traditional design, and networks constructed approximate uncertainties robotic systems, whose optimal weights estimated by using partial saturation difference method. For bounded state errors, of will...

A prescribed performance neuro-adaptive control scheme is proposed for a single-link flexible-joint robotic manipulator with unknown deadzone and actuator faults. new smooth inverse model constructed to offset the adverse effect caused by input in of manipulators. The law developed coordinating backstepping technique ensure transient/steady-state performance, while adaptive neural networks are employed uncertainty approximation. tracking error always restricted within bound during process,...

In this paper, an event-triggered adaptive control scheme is proposed for the gun system of a tank subject to not only external disturbances but also uncertain modeling errors and unknown parameters. Compared with existing results, upper bound function unknown. Therefore, traditional method cannot be applied directly handle effect caused by errors. To solve problem, smooth $sg(\cdot)$ introduced estimate errors, such that their effects on stability are successfully compensated. The...

In this paper, a novel neural network-based error-track iterative learning control scheme is proposed to tackle trajectory tracking problem for tank gun systems. Firstly, the system modeling systems introduced as preparation of controller design. Then, reference error constructed deal with nonzero initial control. The adaptive designed by using Lyapunov approach. Adaptive network adopted approximate nonlinear uncertainties, robust technique being used compensate approximation and external...

Summary An adaptive compensation control scheme is proposed by using backstepping techniques for a class of uncertain nonlinear systems preceded m hysteretic actuators, which exhibit unknown backlash nonlinearity and possibly experience failures. estimated smooth inverse the actuator utilized in controller design to compensate effects It shown that designed controllers can ensure all signals closed‐loop system bounded any failure pattern actuators tracking performance also maintained....

In this paper, to reduce the communication burden between controller and actuator, we propose an event-triggered control design scheme for spacecraft attitude stabilization problem. The main idea is that triggering event simultaneously such can effectively compensate measurement errors caused by event-triggering mechanism. Two different kinds of events, i.e. fixed threshold strategy relative strategy, are considered according practical situations. Through Lyapunov analysis, it shown proposed...

In this paper, an error-tracking iterative learning control scheme is proposed for a class of nonlinearly parametric time-delay systems with initial state errors. The controller developed by Lyapunov approach. With desired error trajectory constructed according to the given method, robust and are synthetically applied compensate uncertainties. While closed-loop system operates, as iteration number increases, can make perfectly follow its over entire time interval, which, precisely track...