Event-triggered neural intelligent control for uncertain nonlinear systems with specified-time guaranteed behaviors
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ORIGINAL ARTICLE
Event-triggered neural intelligent control for uncertain nonlinear systems with specified-time guaranteed behaviors Xingling Shao1,2,4
•
Haonan Si1,3 • Wendong Zhang1,2
Received: 26 March 2020 / Accepted: 8 September 2020 Ó Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract In this paper, an event-triggered neural intelligent control for uncertain nonlinear systems with specified-time guaranteed behaviors is proposed. To cope with constrained communication resources, an event-triggered mechanism using switched thresholds is devised without involving input-to-state stability assumption, such that a better design flexibility and freedom can be provided. In addition, a minimum-learning-parameter-based state observer is developed to online estimate the unavailable states and uncertainties at the same time, which effectively eliminates the issue of learning explosion without sacrificing the identification precision. Furthermore, in pursuit of making a compromise between sampling cost and tracking performance, a modified barrier Lyapunov function based on a time-varying finite-time behavior boundary is constructed in the controller design, which can guarantee that the tracking error converges to a predetermined region within a specified time. Then by introducing the Nussbaum gain technique to handle the unknown control direction, an eventtriggered neural output feedback control strategy is synthesized within the framework of dynamic surface control. Meanwhile, with the aid of Lyapunov synthesis, all the signals involved in the closed-loop system are proved to be bounded while Zeno phenomena is circumvented, and system outputs are well within the predefined region. Finally, an application on control design for a micro-electro-mechanical system gyroscope is given to validate the efficiency and superiority of proposed intelligent control scheme. Keywords Event-triggered mechanism MLP-based state observer Modified barrier Lyapunov function Uncertain nonlinear systems
1 Introduction Nowadays, system nonlinearities and external disturbances are ubiquitous and can be easily found in industrial engineering practices, such as robots [1–3], flexible air-
& Xingling Shao [email protected] 1
Key Laboratory of Instrumentation Science and Dynamic Measurement, Ministry of Education, North University of China, Taiyuan 030051, China
2
National Key Laboratory for Electronic Measurement Technology, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
3
School of Information and Communication Engineering, North University of China, Taiyuan 030051, China
4
School of Instrument and Electronics, North University of China, Taiyuan 030051, China
breathing hypersonic vehicles [4–6], micro-electro-mechanical system (MEMS) gyroscopes [7, 8] and spacecrafts [9, 10]. For instance, MEMS gyroscope, as an indispensable measuring instrument, has been widely employed in inertial navigations, consumer electronics and even mili
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