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Summary: Adaptive output‐feedback control is investigated for a class of uncertain damped wave equations. The remarkable features of the system in question are as follows: (i) Unknown damping is allowed at the boundary; (ii) The boundary measurement is corrupted by an unknown harmonic disturbance. These features make the control problem essentially different from those in the related literature. To solve the problem, a novel adaptive output‐feedback control scheme is established for the system. Specifically, an ingenious observer is first introduced to reconstruct the unmeasured system state in the space domain. Based on this, a certain compensation mechanism is designed for the unknown damping coefficient and output disturbance by adaptive technique based on projection operator. Then, an output‐feedback controller is successfully designed by the backstepping method for ODEs, which guarantees that all states of the resulting closed‐loop system are bounded, and the original system state ultimately converges to an arbitrarily prescribed small neighborhood of the origin. Finally, a simulation example is provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is devoted to the boundary stabilisation via event-triggered output-feedback for a class of 2 × 2 hyperbolic systems. Different from the closely related works, the system parameters are spatially varying and only one boundary measurement is available for feedback, which brings essential difficulties to the analysis and synthesis of event-triggered control. To solve the problem, by using the time-varying strategy and the infinite-dimensional backstepping technique, a novel event-triggered output-feedback controller is designed for the systems. Particularly, a time-varying event-triggering mechanism, with an extra decaying signal introduced into the threshold, is determined. It is rigorously shown that the designed event-triggered controller can guarantee that all the states of the resulting closed-loop system exponentially converge to zero in the sense of L 2 norm while no Zeno phenomenon occurs. Two simulation examples are given to illustrate the effectiveness of the established boundary control strategy. [ABSTRACT FROM AUTHOR]

To date, most schemes of adaptive stabilization are confined to convergence, and cannot specify the convergence rate. As such, the possibility of excessively slow convergence could not be ruled out, which undermines the application scope of adaptive schemes. Such imperfection is mainly due to the limited capability of compensation/learning mechanisms which lack the ingredients affording specific convergence rate. For stronger applicability, more comprehensive compensation/learning mechanisms need to be exploited, inevitably aggravating control synthesis and analysis. This paper aims to enhance adaptive control in terms of convergence rate, and particularly, seeks exponential regulation via adaptive output feedback for stochastic nonlinear systems allowing large uncertainties coupling to unmeasurable states and dynamic uncertainties. To this end, a refined adaptive output-feedback scheme is established in the stochastic framework, though no non-stochastic counterpart exists. Critically, a novel dynamic high gain is introduced in a universal manner, with its updating law delicately incorporating the gain-dependent time-varying information in exponential form. The dynamic gain would not only become sufficiently large to capture the large uncertainties, but also render the desired convergence with the rate online regulated to match the dynamic uncertainties. In this way, an adaptive output-feedback controller based on dynamic-gain observer is designed, which guarantees the system and observer states to almost surely converge to zero at an exponential rate. The stochastic framework complicates the validity verification of the established scheme, entailing subtle martingale-based analysis. Correspondingly, a distinctive analysis pattern is developed for the resulting closed-loop system, to attain expected stochastic convergence and boundedness. [ABSTRACT FROM AUTHOR]

This paper aims to establish a novel adaptive event-triggered scheme of global output-feedback stabilization for nonlinear systems with unmeasurable state dependent growth under the architecture with network communication among sensor, observer-based controller and actuator. To suppress the inherent system nonlinearities (reflected by the polynomial-of-output growth rate), a dynamic gain is integrated into event-triggered scheme. While reducing execution as much as possible to maintain efficiency, it is critical to ensure timely information transmission and control updating for the effectiveness of adaptive mechanism. To this end, double-side asynchronous adaptive event-triggering mechanisms, instead of a one-side or (double-side) synchronous one, are delicately designed by fully exploiting the dynamic gain, upon which adaptive event-triggered output-feedback control is established to ensure the system states to converge to zero. Particularly, the time of evaluation suspension and the threshold parameter for the events on system output and observer states are not fixed but rather online adjusted with the alteration of dynamic gain, to make sure to counteract the influence of sampling/actuation error. Unlike the related results, the adaptive event-triggering mechanisms render the inter-execution times determined purely according to system behavior and without explicit upper-bound limit, which retain the desired potential in execution reducing. [ABSTRACT FROM AUTHOR]