Event-basedH2/H∞controllers for networked control systems

Orihuela, Luis; Millán, Pablo; Vivas, Carlos; Rubio, Francisco

doi:10.1080/00207179.2014.929745

Cited by 16 publications

(16 citation statements)

References 29 publications

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“…For example, if = 0 and ε = 0, the ETS (2) is reduced to the classic periodic sampling scheme, that is, k s+1 = k s + 1, [22,25,27,28]; if ∈ (0, 1) and ε = 0, the ETS (2) can be simplified as the so-called relative ETS, that is,…”

Section: Remarkmentioning

confidence: 99%

“…The state 1, 2, 3, 4) are the cart's position, the cart's velocity, the pendulum bob's angle and the pendulum bob's angular velocity, respectively. In the sequel, for fair comparison, take the same sampling period h = 0.12s with zero communication delay, the same state feedback gain matrix K = 2 12 378 210 , and the same initial state x (0) = 0.98 0 0.2 0 T as in [28] and [24]. Under the above parameters, the comparison results on the average transmission periods (ATPs) generated by our method and the latest results obtained in [28] and [24] are listed in Table 1.…”

Section: Proofmentioning

confidence: 99%

“…In the sequel, for fair comparison, take the same sampling period h = 0.12s with zero communication delay, the same state feedback gain matrix K = 2 12 378 210 , and the same initial state x (0) = 0.98 0 0.2 0 T as in [28] and [24]. Under the above parameters, the comparison results on the average transmission periods (ATPs) generated by our method and the latest results obtained in [28] and [24] are listed in Table 1. It can be seen from Table 1 that the method proposed in this article can provide a larger ATP than that given in [28] and [24].…”

Section: Proofmentioning

confidence: 99%

“…Unfortunately, very few results related to ultimate boundness of the systems's state in eventtriggered discrete-time NCSs have been available in the literature so far. Even though the ultimately bounded stability in eventtriggered feedback control system has been discussed in [22,27,28], the co-design for feedback gain matrix and ETS cannot be realized in [22], and in [27,28], only discrete-time linear NCSs rather than discrete-time nonlinear NCSs is considered. Hence, it is significant and necessity to study the event-triggered controller design for discrete-time nonlinear NCSs with taking ultimate boundness of system's trajectory into account; and (iii) a large class of nonlinear systems can be approximated by Takagi-Sugeno (T-S) fuzzy models on any compact set to arbitrary accurary by using the fuzzy modeling approach [39], the available theory concerning the stability analysis and control synthesis of T-S fuzzy systems is fairly mature.…”

Section: Introductionmentioning

confidence: 99%

“…Since the pioneering work [1] on event-based control, several different ETSs have been proposed for different system models. To name a few, an absolute ETS for linear NCSs, see, for example, [21,27,28,56]; a relative ETS for linear NCSs, see, for example, [6,7,9,10,14,15,24,31,33,53]; a relative ETS for nonlinear NCSs, see, for example, [17,32,44].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Event-triggered controller design of nonlinear discrete-time networked control systems in T-S fuzzy model

Yue

Chen

et al. 2015

Applied Soft Computing

115

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Section: Remarkmentioning

confidence: 99%

Section: Proofmentioning

confidence: 99%

Section: Proofmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Event-triggered controller design of nonlinear discrete-time networked control systems in T-S fuzzy model

Yue

Chen

et al. 2015

Applied Soft Computing

115

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Mixed Event‐Triggered Mechanism Modeling and Controlling for Networked Control Systems with Time‐Varying Delays and Uncertainties

Liu

2018

Asian Journal of Control

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This paper is concerned with modeling and controlling under the mixed event‐triggered mechanism (ETM) for networked control systems (NCSs) with time‐varying delays and uncertainties. Firstly, an event‐triggered threshold is set by using both state and state‐independent informations in the mixed ETM. Then the event‐triggered NCSs with network‐induced time‐varying delays which exist in both sensor‐to‐controller and controller‐to‐actuator channels are modeled as a general time‐delay system. Based on the piecewise differentiable characteristic of the time‐varying delay and by using the approach of free weighting matrix and reciprocally convex, a less conservative criterion to be globally uniformly ultimately bounded (GUUB) stability and a controller design method are derived. Furthermore, an algorithm is proposed to obtain the desired mixed ETM and state‐feedback controller which can render the network load and control performance to reach an expected level. Compared with the relative and absolute ETMs, the proposed mechanism can effectively improve the transmission efficiency during the whole working time. Finally, a numerical example is given to show the effectiveness of the proposed approach.

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Adaptive event‐triggered control for nonlinear discrete‐time systems

Yue

Yin

et al. 2016

Intl J Robust & Nonlinear

108

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This paper focuses on the analysis and the design of event-triggering scheme for discrete-time systems. Both static event-triggering scheme (SETS) and adaptive event-triggering scheme (AETS) are presented for discrete-time nonlinear and linear systems. What makes AETS different from SETS is that an auxiliary dynamic variable satisfying a certain difference equation is incorporated into the event-triggering condition. The sufficient conditions of asymptotic stability of the closed-loop event-triggered control systems under both two triggering schemes are given. Especially, for the linear systems case, the minimum time between two consecutive control updates is discussed. Also, the quantitative relation among the system parameters, the preselected triggering parameters in AETS, and a quadratic performance index are established. Finally, the effectiveness and respective advantage of the proposed event-triggering schemes are illustrated on a practical example. 4105Similar ETC scheme can be found in [7]. A self-triggered scheme is given in [8] for continuoustime linear systems with disturbance, while guaranteeing the finite-gain L2 stability of the resulting self-triggered feedback control systems. In [9], a distributed relative-difference ETC scheme for distributed networked control systems with data dropout and transmission delays is proposed for linear and nonlinear subsystems. A decentralized relative-difference event-triggering mechanism is proposed for continuous-time linear systems in [10], where the closed-loop stability and L 1 performance and the bounds on the minimum time between two subsequent events generated by each node are also studied. More recently, a relative-difference discrete event-triggered communication scheme has been proposed in [11,12], where the term discrete refers to the fact that the approach needs the triggering condition to be checked only at discrete times, which is completely different from the preceding works where the implementation of the designed ETC schemes requires a continuous supervision of the system state to detect whether it violates the triggering condition. Also, an H 1 performance analysis and control synthesis of networked continuous-time linear systems with transmission delays are established in terms of linear matrix inequalities, which successfully solves the open problem in the previous published papers. Up to now, there are several interesting extensions to the research presented in [11], including event-triggered quantized control design problem for networked linear systems [13-15], event-based H 1 filter design problem for networked systems [16][17][18], L 2 -gain analysis of event-triggered networked linear systems [19], a co-design method of the ETC scheme and state feedback controller for networked T-S fuzzy systems and linear systems in [20] and [21], respectively, event-based H 2 and H 1 control design for discrete-time networked linear systems in [22] , output feedback control design for networked control systems [12,23], a decentralized state-dependent tr...

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Event-basedH₂/H_∞controllers for networked control systems

Cited by 16 publications

References 29 publications

Event-triggered controller design of nonlinear discrete-time networked control systems in T-S fuzzy model

Event-triggered controller design of nonlinear discrete-time networked control systems in T-S fuzzy model

Mixed Event‐Triggered Mechanism Modeling and Controlling for Networked Control Systems with Time‐Varying Delays and Uncertainties

Adaptive event‐triggered control for nonlinear discrete‐time systems

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