Author
Chong Lin
Other affiliations: University of Hong Kong, National University of Singapore, Nanyang Technological University
Bio: Chong Lin is an academic researcher from Qingdao University. The author has contributed to research in topics: Backstepping & Nonlinear system. The author has an hindex of 65, co-authored 255 publications receiving 13313 citations. Previous affiliations of Chong Lin include University of Hong Kong & National University of Singapore.
Papers published on a yearly basis
Papers
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TL;DR: The present results may improve the existing ones due to a method to estimate the upper bound of the derivative of Lyapunov functional without ignoring some useful terms and the introduction of additional terms into the proposed Lyap unov functional, which take into account the range of delay.
899 citations
TL;DR: A novel method is proposed in this note for stability analysis of systems with a time-varying delay by considering the additional useful terms when estimating the upper bound of the derivative of Lyapunov functionals and introducing the new free-weighting matrices.
Abstract: A novel method is proposed in this note for stability analysis of systems with a time-varying delay. Appropriate Lyapunov functional and augmented Lyapunov functional are introduced to establish some improved delay-dependent stability criteria. Less conservative results are obtained by considering the additional useful terms (which are ignored in previous methods) when estimating the upper bound of the derivative of Lyapunov functionals and introducing the new free-weighting matrices. The resulting criteria are extended to the stability analysis for uncertain systems with time-varying structured uncertainties and polytopic-type uncertainties. Numerical examples are given to demonstrate the effectiveness and the benefits of the proposed method
737 citations
TL;DR: This paper focuses on adaptive fuzzy tracking control for a class of uncertain single-input /single-output nonlinear strict-feedback systems and a novel direct adaptive fuzzy Tracking controller is constructed via backstepping.
603 citations
TL;DR: The proposed adaptive fuzzy tracking controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value.
Abstract: This paper is concerned with the problem of adaptive fuzzy tracking control for a class of pure-feedback stochastic nonlinear systems with input saturation. To overcome the design difficulty from nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is first introduced to approximate the saturation function; then, an adaptive fuzzy tracking controller based on the mean-value theorem is constructed by using backstepping technique. The proposed adaptive fuzzy controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.
386 citations
TL;DR: A new finite-time stability criterion is proposed and a novel adaptive neural output-feedback control strategy is raised by backstepping technique, and under the presented control scheme, the finite- time quantized feedback control problem is coped with without limiting assumption for nonlinear functions.
Abstract: This paper addresses the finite-time tracking issue for nonlinear quantized systems with unmeasurable states. Compared with the existing researches, the finite-time quantized feedback control is considered for the first time. By proposing a new finite-time stability criterion and designing a state observer, a novel adaptive neural output-feedback control strategy is raised by backstepping technique. Under the presented control scheme, the finite-time quantized feedback control problem is coped with without limiting assumption for nonlinear functions.
366 citations
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01 Jan 2015
3,828 citations
TL;DR: This paper suggests the lower bound lemma for such a combination, which achieves performance behavior identical to approaches based on the integral inequality lemma but with much less decision variables, comparable to thosebased on the Jensen inequalityLemma.
2,248 citations
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TL;DR: This paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies which are adaptive, distributed, asynchronous, and verifiably correct.
Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.
2,198 citations