10 results on '"Liu, Yungang"'
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2. Periodic Event-Triggered Output-Feedback Stabilization for Stochastic Systems.
- Author
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Li, Fengzhong and Liu, Yungang
- Abstract
This article is devoted to explore the periodic event-triggered stabilization for continuous-time stochastic systems, and to develop analysis tools/methods for stochastic periodic event-triggered control. Notably, without real-time monitoring of system behavior as in the scenario with continuous event evaluation, it is critical to delicately estimate and govern the execution/sampling error to achieve the desired system performance. This, under stochastic effects, would be substantially challenging, since the behavior of the stochastic system is hard to predict and is disparate between trials even with the same initial conditions. In this article, a framework of global stabilization via periodic event-triggered output-feedback is established: 1) a criterion condition based on the ISS-Lyapunov function is presented for the feasibility of the desired event-triggered stabilization; 2) both the asymptotic stabilization and exponential stabilization are achieved for the systems, with delicately specifying the periodic event-triggering mechanism; and 3) the involved analysis, without applying the well-known Lyapunov theorems, can serve as a pattern from estimating sampling and execution errors to assess the closed-loop stability for stochastic periodic event-triggered control. Moreover, based on the established framework, we contribute the stabilizing controller design via periodic event-triggered output-feedback for a class of stochastic nonlinear systems. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
3. An Enlarged Framework of Event-Triggered Control for Stochastic Systems.
- Author
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Li, Fengzhong and Liu, Yungang
- Subjects
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STOCHASTIC systems , *LYAPUNOV functions , *SAMPLING errors , *EXPONENTIAL stability , *STABILITY criterion - Abstract
This article aims to enlarge the applicability of event-triggered control for stochastic systems, and is particularly concerned with event-triggered stabilization for stochastic systems with control-dependent diffusion term. Roughly treating stochastic noises as unfavorable factors for system stability, the related works are based on Lyapunov-type conditions for ISS property with respect to sampling error as those in the nonstochastic context. The conditions imply the existence of a twice-differentiable Lyapunov function with negative-definite infinitesimal under continuous-time control, and indeed exclude many familiar stochastic systems with control-dependent diffusion term which are continuously stabilizable while no such Lyapunov function exists. As the main contribution of this article, an enlarged framework of event-triggered stabilization is established for stochastic systems with control-dependent diffusion term, starting from the system stability under continuous-time control, rather than from Lyapunov-type conditions for ISS property. Specifically, with moment exponential stability assumed under continuous-time control, elementary event-triggering mechanisms are proposed with an enforced minimum inter-execution interval, under which the event-triggered controller can render the system exponentially stable both in the sense of expectation and in the almost sure sense. Particularly, a distinctive analysis of closed-loop stability is performed via delicate comparison between the solutions under the event-triggered, and continuous-time controls. Within the framework, inclusive Lyapunov-type conditions incorporating the underlying positive effects of stochastic noises are presented for event-triggered exponential stabilization of the stochastic systems, where the candidate Lyapunov function involved is weakened to be nondifferentiable at the origin and, even, to allow non-negative infinitesimal under continuous-time control. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
4. Adaptive stabilization based on passive and swapping identifiers for a class of uncertain linearized Ginzburg–Landau equations.
- Author
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Li, Jian and Liu, Yungang
- Subjects
- *
EQUATIONS , *CLOSED loop systems , *BOUND states , *UNCERTAIN systems , *DISTRIBUTED parameter systems , *ADAPTIVE fuzzy control - Abstract
This paper is devoted to the stabilization for a class of uncertain linearized Ginzburg–Landau equations (GLEs). The distinguishing feature of such system is the presence of serious uncertainties which enlarge the scope of the systems whereas challenge the control problem. Therefore, certain dynamic compensation mechanisms are required to overcome the uncertainties of system. Motivated by the related literature, the original complex-valued GLEs are transformed into a class of real-valued coupled parabolic systems with serious uncertainties and distinctive characteristics. For this, two classes of identifiers respectively based on passive and swapping identifiers are first introduced to design parameter dynamic compensators. Then, by combining infinite-dimensional backstepping method with the dynamic compensators, two adaptive state-feedback controllers are constructed which guarantee all the closed-loop system states are bounded while the original system states converge to zero. A numerical example is provided to validate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
5. Adaptive Control of Uncertain Coupled Reaction–Diffusion Dynamics With Equidiffusivity in the Actuation Path of an ODE System.
- Author
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Li, Jian and Liu, Yungang
- Subjects
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ADAPTIVE control systems , *PARABOLIC differential equations , *ORDINARY differential equations , *KERNEL functions , *CLOSED loop systems , *DISTRIBUTED parameter systems , *STATE feedback (Feedback control systems) - Abstract
This article is devoted to the stabilization via adaptive feedback for a class of uncertain coupled reaction–diffusion dynamics in the actuation path of an ordinary differential equation (ODE) system. The system under investigation, a class of coupled parabolic partial differential equation (PDE)–ODE systems, is more representative since the dynamics in actuation path (i.e., the PDE subsystem) are coupled rather than uncoupled parabolic equations and hence includes those in the related literature as special cases. Moreover, serious parametric uncertainties are present in both PDE and ODE subsystems, which bring obstacles to the traditional methods on this issue. To solve the control problem, an infinite-dimensional backstepping transformation with time-varying matrix-valued kernel functions is adopted to change the original system into a new one. Then, an adaptive state-feedback controller is designed for the new system, which guarantees that all the closed-loop system states are bounded while regulating the original system states to zero. Finally, a simulation example is provided to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
6. Control Design With Prescribed Performance for Nonlinear Systems With Unknown Control Directions and Nonparametric Uncertainties.
- Author
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Li, Fengzhong and Liu, Yungang
- Subjects
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NONLINEAR systems , *NONPARAMETRIC statistics , *STOCHASTIC convergence , *DIFFERENTIAL equations , *CLOSED loop systems - Abstract
This paper considers the control design with prescribed performance for uncertain nonlinear systems. Different from the existing literature, the systems under investigation possess unknown control directions and nonparametric uncertainties. Even so, the control objective to be achieved is still refined, not only to ensure the basic performance on stabilization, but also to guarantee certain prescribed performance required in real applications. Motivated by the funnel control method, a time-varying stabilizing scheme is developed for the systems, to effectively handle the serious uncertainties and to successfully guarantee the states to converge to zero with a prescribed rate. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
7. Global stabilization via time-varying output-feedback for stochastic nonlinear systems with unknown growth rate.
- Author
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Li, Fengzhong and Liu, Yungang
- Subjects
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FEEDBACK control system stability , *TIME-varying systems , *GROWTH rate , *STABILITY of nonlinear systems , *STOCHASTIC systems - Abstract
This paper considers the global stabilization via time-varying output-feedback for a class of stochastic nonlinear systems. Different from the related existing literature, the systems possess serious uncertainties/unknowns which are reflected in the uncertain control coefficient and the unknown growth rate of the unmeasured states dependent growth. To deal with these serious uncertainties/unknowns, a time-varying framework, rather than an adaptive one, is proposed in this paper since the latter has not been successfully employed in the topic. Detailedly, due to the absence of precise information on the control coefficient, time-varying K-filters are introduced to construct the unmeasured system states. By a delicate time-scaling transformation, a time-scaled entire system is derived, and from which, the design scheme of a time-varying output-feedback controller is developed by backstepping method and time-varying technique. It is shown that all signals of the resulting closed-loop system converge to zero a.s., and furthermore, when serious time-variations exist as well, it suffices to find a fast enough time-varying gain for the control design scheme. A simulation example is given to show the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
- View/download PDF
8. Global stability and stabilization of more general stochastic nonlinear systems.
- Author
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Li, Fengzhong and Liu, Yungang
- Subjects
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STABILITY theory , *STOCHASTIC systems , *NONLINEAR systems , *LIPSCHITZ spaces , *GENERALIZATION , *UNIQUENESS (Mathematics) - Abstract
Abstract: This paper considers the global stability and stabilization of more general stochastic nonlinear systems. Due to the absence of the conventional assumptions (e.g., Lipschitz condition), the stochastic nonlinear systems under investigation may have more than one weak solution. However, the most associated results are only applicable to the stochastic systems having a unique strong solution, and therefore, it is meaningful to refine and extend the relevant concepts and methods to the more general case. In this paper, the concepts of stochastic stability in the more general sense are first introduced to cover the stochastic nonlinear systems having more than one weak solution. Then, the generalized stochastic Barbashin–Krasovskii theorem and LaSalle theorem are established, which present the criterions of stochastic stability for more general stochastic nonlinear systems. As one of the main contributions in this paper, we rigorously prove the generalized stochastic Barbashin–Krasovskii theorem. Moreover, based on the generalized theorems, the output-feedback and state-feedback stabilization are accomplished respectively for two classes of high-order stochastic nonlinear systems under rather weaker assumptions comparing to the existing literature. [Copyright &y& Elsevier]
- Published
- 2014
- Full Text
- View/download PDF
9. Adaptive stabilization for an uncertain reaction–diffusion equation with dynamic boundary condition at control end.
- Author
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Li, Jian, Wu, Zhaojing, and Liu, Yungang
- Subjects
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REACTION-diffusion equations , *SYSTEM dynamics , *CLOSED loop systems , *ADAPTIVE control systems , *PROBLEM solving , *ADAPTIVE fuzzy control , *STATE feedback (Feedback control systems) - Abstract
This paper is devoted to the stabilization of a class of uncertain reaction–diffusion equations with dynamic boundary condition. Remarkably, the dynamics of boundary condition at control end are considered while unknown parameters are contained in both the intra-domain and the dynamic boundary. This greatly relaxes the restrictions on boundary dynamics and system uncertainties of the related literature where dynamic boundary condition is neglected or considered but unknown parameters are only contained in the dynamic boundary or even completely excluded from the whole system. To solve the control problem, a novel control framework is established by infinite-dimensional backstepping method combining with adaptive compensation technique based on passive identifier. Then, an adaptive state-feedback controller is explicitly constructed which guarantees that all the states of the resulting closed-loop system are bounded while those of the original system converge to zero. A simulation example is provided to validate the effectiveness of the proposed theoretical results. • The restrictions of the existing literature imposed on boundary dynamics and system uncertainties are greatly relaxed since a dynamic boundary condition at control end is considered while unknown parameters are allowed in both the intra-domain and the dynamic boundary in the paper. • A novel passive identifier is designed, combining which with the infinite-dimensional backstepping method, a novel control framework is established that can compensate both the boundary dynamics and system uncertainties, and in turn to stabilize the system under investigation. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
10. Stabilization involving condition-based adaptive control of an uncertain wave equation for the vibration of a flexible string.
- Author
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Li, Jian, Wu, Zhaojing, Wen, Changyun, and Liu, Yungang
- Subjects
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WAVE equation , *UNCERTAIN systems , *CLOSED loop systems , *ADAPTIVE control systems , *PROBLEM solving - Abstract
This paper investigates the stabilization of an uncertain wave equation which describes the vibration dynamics of a flexible string. All the system parameters are unknown while the disturbance with unknown bound and period is allowed which lead to more serious uncertainties than the related literature, and hence result into the incapability of the traditional schemes. To solve the control problem, a novel condition-based adaptive control framework is developed in the paper. Specifically, as preparation for the adaptive control design, a state-feedback controller is first designed under the assumption that all the system parameters are known. Then, an adaptive controller, together with two continuous adaptive laws and a condition-based updating mechanism for the online tuning of the controller parameters, is proposed for the original uncertain system. Finally, it is proven that the updating of controller parameters under the proposed condition-based updating mechanism stops at a finite time instant, then the proposed controller guarantees the stability of the resulting closed-loop system. The proposed theoretical results are validated by a simulation example. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
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