Litcius/Paper detail

A Blow-Up Function Approach to Global Event-Triggered Prescribed Tracking Output Feedback Control of Nonlinear Systems

Pengju Ning, Changchun Hua, Kuo Li, Rui Meng

2022IEEE Transactions on Circuits and Systems I Regular Papers23 citationsDOI

Abstract

In this paper, global event-triggered adaptive prescribed tracking output feedback control is investigated for a class of nonlinear uncertain systems with unknown control direction. Different from the existing works, the design of the tracking error-dependent normalized function and prescribed boundary is based on our uniformly defined blow-up function rather than a specific function, and the asymmetric constraint requirements on tracking error can be achieved by appropriately selecting the blow-up function. By utilizing the Kalman filter ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -filter) and dynamic gain technique, a new reduce-order observer is proposed, which can make the estimated error exponentially converge to zero. In addition, by introducing a dynamic signal into the trigger condition, a novel event-triggered mechanism is proposed, which can extend the trigger time interval and completely counteract the event-triggered errors in terms of asymptotic stability by sacrificing part of the system transient performance. Furthermore, an adaptive controller is designed based on the backstepping method, which ensures the boundedness of the state of the closed-loop system, while regulating the tracking error meets the global prescribed performance requirements and approaches to zero asymptotically. Two examples are given to illustrate the effectiveness of the proposed control scheme.

Topics & Concepts

Control theory (sociology)BacksteppingTracking errorController (irrigation)Nonlinear systemExponential stabilityFunction (biology)Observer (physics)MathematicsComputer scienceFilter (signal processing)Adaptive controlControl (management)Artificial intelligenceAgronomyEvolutionary biologyPhysicsBiologyComputer visionQuantum mechanicsAdaptive Control of Nonlinear SystemsAdaptive Dynamic Programming ControlStability and Controllability of Differential Equations