Quantized output feedback stabilization of uncertain systems with input nonlinearities via sliding mode control

Zheng, Bo‐Chao; Yang, Guang‐Hong

doi:10.1002/rnc.2883

Cited by 51 publications

(44 citation statements)

References 37 publications

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“…Since all previously described controllers were designed for discrete time and in order to cope with the finite sampling, a discrete time SMC controller is designed [23], [24], [25]. Considering an uncertain first order discrete time linear system in which the following notation is introduced, i.e.…”

Section: B Sliding Mode Controlmentioning

confidence: 99%

Model based control strategies for a class of nonlinear mechanical sub-systems

Ionescu¹,

Keyser²

2016

2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR)

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Abstract-This paper presents a comparison between various control strategies for a class of mechanical actuators common in heavy-duty industry. Typical actuator components are hydraulic or pneumatic elements with static non-linearities, which are commonly referred to as Hammerstein systems. Such static non-linearities may vary in time as a function of the load and hence classical inverse-model based control strategies may deliver sub-optimal performance. This paper investigates the ability of advanced model based control strategies to satisfy a tolerance interval for position error values, overshoot and settling time specifications. Due to the presence of static non-linearity requiring changing direction of movement, control effort is also evaluated in terms of zero crossing frequency (up-down or leftright movement). Simulation and experimental data from a lab setup suggest that sliding mode control is able to improve global performance parameters.

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Section: B Sliding Mode Controlmentioning

confidence: 99%

Model based control strategies for a class of nonlinear mechanical sub-systems

Ionescu¹,

Keyser²

2016

2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR)

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“…During the past few decades, various kinds of neural networks have been increasingly investigated due to their extensive and successful applications in different areas such as secure communication, signal processing, image processing, pattern recognition, combinatorial opti-B Guangming Zhuang zgmtsg@126.com 1 NCSs under those mentioned communication phenomena, and a large number of fruits have been reported in the literature, see, for example, [41,[43][44][45][46][47], and the references therein. To the best of the authors' knowledge, however, thus far, there are few research on the H ∞ filter for MJNNs, not to mention the case with mode-dependent time-varying delays, parameter uncertainties and limited communication capacity.…”

Section: Introductionmentioning

confidence: 99%

$$H_{\infty }$$ H ∞ Estimation for Markovian Jump Neural Networks With Quantization, Transmission Delay and Packet Dropout

Zhuang

Xia

et al. 2015

Neural Process Lett

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This paper is concerned with the problem of robust H ∞ estimation for a class of Markovian jump neural networks with norm-bounded parameter uncertainties, time-varying delay and limited communication capacity including signal transmission delay, measurement quantization and data packet dropout, which occur simultaneously in the same networked control system framework. Our objective is to design mode-dependent H ∞ filter in the network environment in order to ensure the filtering error system is not only exponentially mean-square stable, but also satisfies a prescribed H ∞ norm level for the limited communication capacity and for all admissible uncertainties. We use the delay system method to deal with signal transmission delay and data packet dropout, utilize the sector bound approach to handle measurement quantization. We also construct a comprehensive stochastic Lyapunov-Krasovskii functional to show the inherent mode-dependent state delays in the neural networks itself and the network-induced signal transmission delay. The free-weighting matrix technique and a set of strict linear matrix inequalities are employed to derive novel conditions for the desired mode-dependent H ∞ filter. A numerical example is provided to verify the effectiveness and usefulness of the obtained main results.

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“…The result by Konaka, Suzuki, and Okuma (2002) by an adaptive discrete logic-based controller. The paper by Zheng and Yang (2012) is concerned with the quantized output feedback stabilization problem for a class of uncertain systems with nonsmooth nonlinearities in the actuator device via sliding mode algorithm. In Hayakawa, Ishii, and Tsumura (2009) a direct adaptive control framework for nonlinear systems with input quantizers is developed.…”

Section: Introductionmentioning

confidence: 99%