$H_{\infty}$ Control for Networked Predictive Control Systems Based on the Switched Lyapunov Function Method

Wang, Rui; Liu, Shuai; Wang, Wei; Rees, D.; Zhao, Yun‐Bo

doi:10.1109/tie.2009.2038341

Cited by 112 publications

(39 citation statements)

References 25 publications

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“…Average dwell time method was given as an effective tool for finding such switching signal that a common Lyapunov function was not necessary for the overall system still to be stable even though there existed unstable subsystems. Furthermore, an improved predictive control design strategy, combined with the switched Lyapunov function technique, was proposed in [53], where the controller gain varied with the random delay to make the corresponding closed-loop system asymptotically stable with an H ∞ -norm bound. Besides, a new predictive control scheme based on multirate Kalman Filtering was presented in [54] to compensate for the random delays and packet losses in the feedback channel of NCSs.…”

Section: Predictive Controlmentioning

confidence: 99%

Modeling of Random Delays in Networked Control Systems

Chen

Jiang

et al. 2013

Journal of Control Science and Engineering

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In networked control systems (NCSs), the presence of communication networks in control loops causes many imperfections such as random delays, packet losses, multipacket transmission, and packet disordering. In fact, random delays are usually the most important problems and challenges in NCSs because, to some extent, other problems are often caused by random delays. In order to compensate for random delays which may lead to performance degradation and instability of NCSs, it is necessary to establish the mathematical model of random delays before compensation. In this paper, four major delay models are surveyed including constant delay model, mutually independent stochastic delay model, Markov chain model, and hidden Markov model. In each delay model, some promising compensation methods of delays are also addressed.

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Section: Predictive Controlmentioning

confidence: 99%

Modeling of Random Delays in Networked Control Systems

Chen

Jiang

et al. 2013

Journal of Control Science and Engineering

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“…It should be mentioned that, compared with modifying the system mechanical structure, the adopted control approach yields much more flexibility for the mobile robot. Certainly, we are also aware of adaptive scheme to update the upper bound, but the control algorithm with adaptive scheme Backstepping-based Robust Control for WMR with A Boundary in Prior for the Uncertain Rolling Resistance 349 may make the regulation process more elastic and cause further time-delay usually [4,5]. To overcome this drawback, a powerful robust control approach is determine to employ to deal with the uncertain problem of the unavoidable rolling resistance.…”

Section: Introductionmentioning

confidence: 99%

Backstepping-based Robust Control for WMR with A Boundary in Prior for the Uncertain Rolling Resistance

Yue

Wang²,

Yang³

2014

INT J COMPUT COMMUN

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In this study, we focus on the trajectory tracking control problem of a wheeled mobile robot (WMR) in an uncertain dynamic environment. Concerning the fact that the upper boundary may be usually achieved in prior according to the physical properties of the terrain, this crucial message is utilized to construct the controllers. Firstly, a dynamic model for WMR including the rolling resistance is presented, whose state variables are longitudinal and rotational velocities, as well as the rotational angle of the mobile platform. Secondly, with the aid of backstepping technique, the robust controllers based on the upper boundary are proposed and the globally asymptotic stability of the closed-loop system is proven by the Lyapunov theory in the following. Lastly, a saturation function is applied to replace the signum function, by which the inherent chattering can be suppressed greatly. Numerical simulation results demonstrate that the proposed controllers with upper bound in prior possess robustness characteristics which yields potentially valuable applications for the mobile robot, especially in the unstructured environment.

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“…Recently, ∞ optimal control techniques have been found to be an effective solution to treat robust stabilization and tracking problems, in presence of external disturbances and system uncertainties [19][20][21][22][23][24]. In an ∞ control technique, the main design goal is to force the gain from unmodelled dynamics, external disturbances, and approximation errors to be equal or less than a prescribed disturbance attenuation level ( ∞ attenuation constraint) [19].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive -Based Formation Control for Multirobot Systems

2013

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We describe a decentralized formation problem for multiple robots, where an ∞ formation controller is proposed. e network of dynamic agents with external disturbances and uncertainties are discussed in formation problems. We �rst describe how to design social potential �elds to obtain a formation with the shape of a polygon. en, we provide a formal proof of the asymptotic stability of the system, based on the de�nition of a proper Lyapunov function and ∞ technique. e advantages of the proposed controller can be listed as robustness to input nonlinearity, external disturbances, and model uncertainties, while applicability on a group of any autonomous systems with -degrees of freedom. Finally, simulation results are demonstrated for a multiagent formation problem of a group of six robots, illustrating the effective attenuation of approximation error and external disturbances, even in the case of agent failure or leader tracking.

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$H_{\infty}$ Control for Networked Predictive Control Systems Based on the Switched Lyapunov Function Method

Cited by 112 publications

References 25 publications

Modeling of Random Delays in Networked Control Systems

Modeling of Random Delays in Networked Control Systems

Backstepping-based Robust Control for WMR with A Boundary in Prior for the Uncertain Rolling Resistance

An Adaptive -Based Formation Control for Multirobot Systems

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