Design of disturbance observer based on adaptive‐neural control for large‐scale time‐delay systems in the presence of actuator fault and unknown dead zone

This work addresses the event‐triggered finite‐time control problem for a class of uncertain switched nonlinear systems with arbitrary switchings, whose powers are positive odd rational numbers. The key difference from the results of similar problems is that the systems considered in this article are more general, which contains a special case when the powers are equal to 1, and the powers have switching signals. It is well known that such nonlinear systems have challenges because of the uncontrollability in the linearization process and the backstepping technique that successfully developed for low‐order systems fail to work. To tackle this issue, combining the backstepping method, event‐triggered strategy with adding one power integrator technique, an event‐triggered control scheme is developed to make the controlled systems be globally finite‐time stable. Besides, the Zeno‐free behavior is proved to verify the feasibility of the proposed event‐triggered mechanism. Finally, simulation results are given to validate the effectiveness of the developed control strategy.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Event‐triggered finite‐time control for a class of switched nonlinear systems

Yang

Kang

2022

“…Liang et al 35 designed reduced‐order observers for stochastic nonlinear multi‐agent systems. It should be pointed out that the observer‐based control is one of effective and convenient methods to estimate state variables, which only need the input and output signals of systems 12,28,34,36–39 . For example, the authors 12 studied slide mode control issue for MJSs and constructed state observer to estimate unavailable state variables, in which the Markov mode information was involved in the observer.…”

Section: Introductionmentioning

confidence: 99%

Observer‐based adaptive neural networks control for Markovian jump nonlinear systems with partial mode information and input saturation

Cao

Nie

2021

The observer‐based adaptive neural networks control problem is studied in this article for nonlinear Markovian jump systems (MJSs) with partial mode information and input saturation. The existing adaptive control scheme for MJSs works only when the Markov mode of system is completely known. For this reason, the concept of partial mode information of Markov chain is embedded into the framework of adaptive backstepping method and then a mode detector is set to emit the mode. To achieve the control objective, only the emitted mode is used to design the state observer and adaptive control scheme. Besides, an auxiliary signal is introduced in MJSs to compensate the effect of input saturation and this signal appears in controller as the input of neural networks instead of a separate term, which makes the form of proposed controller simpler than that in the literature. Finally, a numerical example and a practical example are provided to demonstrate the feasibility of our control scheme.

“…A parameter adaptive law was designed to compensate the unknown yet invariable actuator efficient factor for a strict‐feedback uncertain nonlinear fractional‐order system 21 and successfully extended to a flexible Euler–Bernoulli (E‐B) beam in the three‐dimensional space 22 . An adaptive neural compensation scheme was reported to ensure the reliability for a class of large‐scale time delay nonlinear systems under possible additive fault 23 . Finite number of unknown actuator failures, including constant loss of effectiveness of actuator fault and time‐varying stuck type actuator fault, were considered in Reference 24 for the fractional‐order systems by resorting to an actuator redundancy framework and adaptive method.…”

Section: Introductionmentioning

confidence: 99%

Stabilization control of a flexible marine riser with failed and bounded actuator and time‐varying boundary constraints

Han

Liu

2021

In this article, we investigate the stabilization control problem of a flexible marine riser system with a failed and bounded control action and time‐varying boundary constraints. The considered system is modeled as a distributed parameter system dominated by a partial differential equation. The involved problems are extended to some more general conditions. The saturation and failures of the actuator make the input and output of the actuator a nonlinear relationship, which leads to the normally designed control input invalid. By applying the Nussbaum gain technique, we report a synthetical control method to tackle the input nonlinearity. A piecewise barrier Lyapunov function (BLF) is introduced to reduce the boundary displacement in an asymmetric open set. Compared with the traditional BLFs, the initial boundary displacement is not forced to retain within the given region by integrating a shifting function into the BLF design. In addition, the adaptive method is combined with the hyperbolic tangent function to provide a smooth control solution to the unknown parameters from nonlinear input and external perturbation. Relying on a Lyapunov‐based analysis and a numerical simulation, it is proven that the actuated riser system is uniformly bounded and the boundary displacement always keeps in the limited set even subject to actuator failures and limitations.