Quantized Dynamic Output Feedback H∞ Control for Discrete-time Systems with Quantizer Ranges Consideration

Che, Wei‐Wei; Yang, Guang-Hong

doi:10.1016/s1874-1029(08)60030-0

Cited by 17 publications

(19 citation statements)

References 17 publications

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“…According to (5) and (6) , we can infer that we will chose the latest packet instead if the packet has been lost at this time. α ∈ [0, 1] is a known constant.…”

Section: Problem Statementmentioning

confidence: 99%

“…And, comparing with the traditional system, networked control systems have the absolute advantage such as low process cost, reliability, sharing of information resources, flexibility and extensible easily. However, because of the characteristics of the network control systems itself, some new problems appear and need to be solved, such as time delays [1], packet dropouts occur [2], [3] and quantization error due to the limited bandwidth [4], [5]. For network control systems, signal quantization is essential.…”

Section: Introductionmentioning

confidence: 99%

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Quantized H<inf>∞</inf> control for networked control systems with random packet losses

Pei-pei

Che

2015

The 27th Chinese Control and Decision Conference (2015 CCDC)

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This paper is concerned with the quantized H ∞ state feedback control problem for discrete-time systems subject to limited communication capacity, which includes state quantization and random sensor packet losses. By introducing a random packet-loss model, an quantized state feedback controller is designed to ensure the exponentially mean-square stable of the closed-loop system and to guarantee an optimal H ∞ disturbance attenuation level. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method.

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“…According to (5) and (6) , we can infer that we will chose the latest packet instead if the packet has been lost at this time. α ∈ [0, 1] is a known constant.…”

Section: Problem Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantized H<inf>∞</inf> control for networked control systems with random packet losses

Pei-pei

Che

2015

The 27th Chinese Control and Decision Conference (2015 CCDC)

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“…Since the quantized measurements are transmitted over the communication networks with limited bandwidth, the data packet dropouts and networked-induced delays are inevitable in the communication channels. Therefore, the static output feedback control law can be described preferably by (5) In NCSs, by substituting (4) into (1), we can obtain the closed-loop system as follows:…”

Section: Problem Formulationsmentioning

confidence: 99%

“…Then quantization errors have adverse effects on the NCSs performance. All of these bring some new challenges in the NCSs analysis and controller design [4][5][6]. Quantizers are divided into linear quantizer, logarithmic quantizer, dynamical quantizer and nonlinearity quantizer.…”

mentioning

confidence: 99%

Quantized control for networked control systems with communication delay and packet dropouts

Jiang¹

2014

The 26th Chinese Control and Decision Conference (2014 CCDC)

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In the past few decades, the study of NCSs has been of great interest since networked control modeling has come to play an important role in modern engineering applications. NCSs are systems where sensors, actuators, estimation units and control units are interconnected by communica -tion networks. In NCSs, data transmission through communication channels can reduce the costs of the wring and maintenance, simplify the installation, etc. However, some new problems occur because all signals are transmitted through a network, such as communication delays and packet dropouts caused by data transmission limitations or errors always happen. Communication delays and packet dropouts deteriorate the performance and may destabilize the systems[1-3]. Another important aspect, which is well known in the signal processing area, is signal quantization. In NCSs, because of the limited transmission capacity, the data should be quantized before they are transmitted to the next nodes. Then quantization errors have adverse effects on the NCSs performance. All of these bring some new challenges in the NCSs analysis and controller design [4][5][6]. Quantizers are divided into linear quantizer, logarithmic quantizer, dynamical quantizer and nonlinearity quantizer. The characteristic of linear quantizer is fixed sector bound. In [7] that the optimal quantizer is a logarithmic in discrete time single-input-single-output system (SISO). In [8] and [9], the authors proposed the idea of sector-bounded nonlinearities. In [10], the authors dealt with the problem of feedback control for networked systems with discrete and distributed delays subject to quantization and packet dropout, and a compensation scheme was proposed to deal with the effect of random packet dropout through communication network. In [11], a unified control law This work is supported by Grant No.L2012414 of College Research Project of Liaoning Province, China.model is proposed to take the network-induced delay, random packet dropout and measurement quantization into consideration simultaneously. Then, a less conservative stability condition is derived, which depends on packet dropout probability, the lower and upper bounds of the delay and quantization density. To the best of the authors' knowledge, the quantized ∞ H feedback stabilization for NCSs with simultaneous consideration of the random communication delay, packet dropout and measurement quantization has not been fully investigated. In contrast with the above previous works, in this paper, based on Logarithmic quantization, the discrete-time NCSs model is described under the concerns of the synthesis effect of quantized signal, random communication delays and packet dropouts. By choosing appropriate Lyapunov functional, a sufficient condition for the existence of quantized ω , are the state vector , control input vector, measured output vector, controlled output, and disturbance Abstract: This paper is concerned with the problem of quantized ∞ H control for discrete-time networked control systems (NCSs) with random c...

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“…Mathematically, it can be considered as an operator, which is defined by a function round (·) that rounds towards the nearest integer. In the control strategies to be developed below, quantised measurements of the following form [19, 26] are used

q_{τ} false(g false) : = τ q ()(, \frac{g}{τ}) : = τ round ()(, \frac{g}{τ}), τ > 0

where g ∈ R p is the variable to be quantised, τ denotes the quantising level (the quantisation sensitivity), q τ (·) is the uniform quantiser with respect to τ .…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

Fault‐tolerant control via sliding‐mode output feedback for uncertain linear systems with quantisation

Hao

Yang

2013

IET Control Theory & Applications

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Quantized Dynamic Output Feedback H∞ Control for Discrete-time Systems with Quantizer Ranges Consideration

Cited by 17 publications

References 17 publications

Quantized H<inf>∞</inf> control for networked control systems with random packet losses

Quantized H<inf>∞</inf> control for networked control systems with random packet losses

Quantized control for networked control systems with communication delay and packet dropouts

Fault‐tolerant control via sliding‐mode output feedback for uncertain linear systems with quantisation

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Quantized Dynamic Output Feedback H∞ Control for Discrete-time Systems with Quantizer Ranges Consideration

Cited by 17 publications

References 17 publications

Quantized H<inf>&#x221E;</inf> control for networked control systems with random packet losses

Quantized H<inf>&#x221E;</inf> control for networked control systems with random packet losses

Quantized control for networked control systems with communication delay and packet dropouts

Fault‐tolerant control via sliding‐mode output feedback for uncertain linear systems with quantisation

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Quantized H<inf>∞</inf> control for networked control systems with random packet losses

Quantized H<inf>∞</inf> control for networked control systems with random packet losses