An Integrated Design Framework of Fault-Tolerant Wireless Networked Control Systems for Industrial Automatic Control Applications

Ding, Steven X.; Zhang, Ping; Yin, Shen; Ding, E.L.

doi:10.1109/tii.2012.2214390

Cited by 128 publications

(92 citation statements)

References 33 publications

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“…So far, considerable research attention has been devoted to the theoretical research on control problems for nonlinear stochastic systems, see [1,3,5,6,9,11,20,22,24,30] and the references therein. For example, for different kinds of nonlinear stochastic systems, the H ∞ output feedback control problem has been investigated in [24], the adaptive fuzzy control problem has been proposed in [22], the neural-network-based controller design has been addressed in [23], the adaptive sliding mode controller has been designed in [4,10,17,18] and the observer-based control problems have been solved in [25], respectively.…”

Section: Introductionmentioning

confidence: 99%

Finite-horizon reliable control with randomly occurring uncertainties and nonlinearities subject to output quantization

et al. 2015

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This paper deals with the finite-horizon reliable H∞ output feedback control problem for a class of discrete time-varying systems with randomly occurring uncertainties (ROUs), randomly occurring nonlinearities (RONs) as well as measurement quantizations. Both the deterministic actuator failures and probabilistic sensor failures are considered in order to reflect the reality. The actuator failure is quantified by a deterministic variable varying in a given interval and the sensor failure is governed by an individual random variable taking value on 0, 1 . Both the nonlinearities and the uncertainties enter into the system in random ways according to Bernoulli distributed white sequences with known conditional probabilities. The main purpose of the problem addressed is to design a time-varying output feedback controller over a given finite horizon such that, in the simultaneous presence of ROUs, RONs, actuator and sensor failures as well as measurement quantizations, the closedloop system achieves a prescribed performance level in terms of the H∞-norm. Sufficient conditions are first established for the robust H∞ performance through intensive stochastic analysis, and then a recursive linear matrix inequality approach is employed to design the desired output feedback controller achieving the prescribed H∞ disturbance rejection level. A numerical example is given to demonstrate the effectiveness of the proposed design scheme.

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Section: Introductionmentioning

confidence: 99%

Finite-horizon reliable control with randomly occurring uncertainties and nonlinearities subject to output quantization

et al. 2015

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“…There is Finally choose feedback control law can be described as follows : 2 0 3 0 2 1 2 1 2 2 1 2 2 1 1 2 2 2 3 0 1 0 2 3 3 3 and will converge to zero, 3 x is also bounded [6]. …”

Section: The Design Of Nonlinera Controllermentioning

confidence: 99%

Improved Many Machine Excitation Nonlinear Robust Controller Design

Yan¹,

Ying²

2016

Proceedings of the 2016 International Conference on Economics, Social Science, Arts, Education and Management Engineering

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Abstract. Electric power systems are one of nonlinear, multidimensional, dynamic and large scale systems. Once power systems lose stability, it would result in the consequence is very serious. With excitation control for multi-machine power system nonlinear model in this article, a series of stability control problems are studied by means of the improved backstepping methods, including excitation control. The nonlinear adaptive robust controller which can stabilize the system has been designed. The concise design method and excellent design strategy make the designed corresponding control scheme own extensive adaptability, which effectively improve the maintain system power angle and voltage stability.

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“…Growing applications have been found in various areas, for example, transportation systems, power systems, remote monitoring and data acquisition systems, chemical processes, and many manufacturing plants [1,2]. NCSs provide many advantages when compared with traditional point-to-point systems, including low cost, easy maintenance, and high efficiency.…”

Section: Introductionmentioning

confidence: 99%

Stabilization of NCSs by random allocation of transmission power to sensors

Wang

Guo

Zhuang

2016

Sci. China Inf. Sci.

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This study investigates networked control systems (NCSs), whose sensors communicate with remote controllers via a wireless fading channel. The sensor can choose different power levels at which it can transmit its measurement to the controller. The transmission power is selected according to a given probability distribution. The level of transmission power determines the probability of packet loss. The objective of this study is to find an appropriate transmission power probability distribution and a system controller jointly such that NCSs can be exponentially stabilized within a given energy budget. By the average dwell time technique, sufficient conditions for almost sure stability and an optimal sensor power probability distribution maximizing the stability margin are obtained. The effectiveness of the results is demonstrated by numerical simulations.

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An Integrated Design Framework of Fault-Tolerant Wireless Networked Control Systems for Industrial Automatic Control Applications

Cited by 128 publications

References 33 publications

Finite-horizon reliable control with randomly occurring uncertainties and nonlinearities subject to output quantization

Finite-horizon reliable control with randomly occurring uncertainties and nonlinearities subject to output quantization

Improved Many Machine Excitation Nonlinear Robust Controller Design

Stabilization of NCSs by random allocation of transmission power to sensors

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