Adaptive sliding mode control for stochastic Markovian jumping systems with actuator degradation

Chen, Bei; Niu, Yugang; Zou, Yuanyuan

doi:10.1016/j.automatica.2013.02.014

Cited by 194 publications

(109 citation statements)

References 22 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. Among various descriptions of nonlinearities, the so-called randomly occurring nonlinearities (RONs) [26] cater for those randomly changeable nonlinearities in terms of their types and/or intensities governed by stochastic variables.…”

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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“…In realistic control system, the actuator degradation is usually inevitable. Inspired by [27,32], the actuator degradation is described as…”

Section: Problem Formulationmentioning

confidence: 99%

“…It is more difficult to be dealt with because the actuator degradation is dependent on control input, instead of viewed as an independent disturbance. In the past decades, various reliable control methodologies have been proposed to address the control problem of different systems with actuator fault, see [23][24][25][26][27][28] and the references therein. Recently, [29] addresses a fault detection problem of switched systems with servo inputs and sensor stuck faults.…”

Section: Introductionmentioning

confidence: 99%

Output feedback control for a class of nonlinear systems with actuator degradation and sensor noise

et al. 2016

ISA Transactions

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a b s t r a c tThis paper investigates the output feedback control problem of a class of nonlinear systems with sensor noise and actuator degradation. Firstly, by using the descriptor observer approach, the origin system is transformed into a descriptor system. On the basis of the descriptor system, a novel Proportional Derivative (PD) observer is developed to asymptotically estimate sensor noise and system state simultaneously. Then, by designing an adaptive law to estimate the effectiveness of actuator, an adaptive observer-based controller is constructed to ensure that system state can be regulated to the origin asymptotically. Finally, the design scheme is applied to address a flexible joint robot link problem.

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“…Among this work, T-S fuzzy systems and Markovian jump systems are two representative classes of dynamical systems. Over the past decades, many meaningful results have been published on the sliding mode control of either T-S fuzzy systems [10,11,12,13] or Markovian jump systems [14,15,16,17,18,19,20]. However, relatively little attention has been focused on research into sliding mode control for composite systems comprising the two classes of systems, namely Markovian jump T-S fuzzy systems [21,22], despite their wide application [23,24,25,26].…”

Section: Introductionmentioning

confidence: 99%

Integral sliding mode control for Markovian jump T–S fuzzy descriptor systems based on the super‐twisting algorithm

Zhang

Yan

et al. 2017

IET Control Theory & Applications

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This paper investigates integral sliding mode control problems for Markovian jump T-S fuzzy descriptor systems via the super-twisting algorithm. A new integral sliding surface which is continuous is constructed and an integral sliding mode control scheme based on a variable gain super-twisting algorithm is presented to guarantee the well-posedness of the state trajectories between two consecutive switchings. The stability of the sliding motion is analyzed by considering the descriptor redundancy and the properties of fuzzy membership functions. It is shown that the proposed variable gain super-twisting algorithm is an extension of the classical single-input case to the multi-input case. Finally, a bio-economic system is numerically simulated to verify the merits of the method proposed.

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Adaptive sliding mode control for stochastic Markovian jumping systems with actuator degradation

Cited by 194 publications

References 22 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

Output feedback control for a class of nonlinear systems with actuator degradation and sensor noise

Integral sliding mode control for Markovian jump T–S fuzzy descriptor systems based on the super‐twisting algorithm

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