Finite-time performance guaranteed event-triggered adaptive control for nonlinear systems with unknown control direction |
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| Institution: | 1. Federal University of São João del-Rei, 170 Frei Orlando, São João del-Rei;1. School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510006, China;2. College of Information Science and Engineering, Huaqiao Univesity, Xiamen 361002, China;3. School of Information Science, Guangzhou Xinhua University, Dongguan 523133, China;4. Marcau Centre for Mathematical Sciences, Macau University of Science and Technology, Macau, China;1. School of Electrical Engineering, University of Jinan, Jinan 250022;2. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016;3. Shool of Control Science and Engineering, Shandong University, Jinan 250061;1. College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, PR China;2. School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, PR China;3. Department of Electrical Engineering, Lakehead University, Thunder Bay P7B 5E1, Canada;1. School of Mathematics and Statistics, Liaoning University, Shenyang 110036, China;2. State Key Laboratory of Synthetical Automation for Process Industries Northeastern University, Shenyang 110819, China |
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| Abstract: | This paper studies the issue of finite-time performance guaranteed event-triggered (ET) adaptive neural tracking control for strict-feedback nonlinear systems with unknown control direction. A novel finite-time performance function is first constructed to describe the prescribed tracking performance, and then a new lemma is given to show the differentiability and boundedness of the performance function, which is important for the verification of the closed-loop system stability. Furthermore, with the help of the error transformation technique, the origin constrained tracking error is transformed into an equivalent unconstrained one. By utilizing the first-order sliding mode differentiator, the issue of “explosion of complexity” caused by the backstepping design is adequately addressed. Subsequently, an ingenious adaptive updated law is given to co-design the controller and the ET mechanism by the combination of the Nussbaum-type function, thus effectively handling the influences of the measurement error resulted from the ET mechanism and the challenge of the controller design caused by the unknown control direction. The presented event-triggered control scheme can not only guarantee the prescribed tracking performance, but also alleviate the communication burden simultaneously. Finally, numerical and practical examples are provided to demonstrate the validity of the proposed control strategy. |
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