Data-Based H∞Tracking Control for Time-Delay Systems Via Adaptive Dynamic Programming
| Autor: | Yang Liu, Xu Jian, Qitong Fu, Zuoxia Xing, Li Li, Lijun Zhao |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
010401 analytical chemistry Control (management) State vector 02 engineering and technology 021001 nanoscience & nanotechnology Tracking (particle physics) 01 natural sciences 0104 chemical sciences Dynamic programming Control theory Bellman equation Trajectory Symmetric matrix Reinforcement learning 0210 nano-technology |
| Zdroj: | 2020 Chinese Automation Congress (CAC). |
| DOI: | 10.1109/cac51589.2020.9327243 |
| Popis: | In this paper, an data-based H ∞ tracking control algorithm is studied for the discrete delay system with disturbances. The augmented system is constructed and then transformed into a data-based system consist of inputs, outputs, and reference trajectories, which replace the state vector by a data vector. Next, based on the Bellman optimality principle, the historical data is adopted to derive a new Bellman equation. In order to realize H ∞ tracking control, the input and disturbance are generalized to the zero-sum game problem. Finally, by collecting operational data online, a H ∞ tracking control method based on databased reinforcement learning algorithm is presented. Simulation example shows that the proposed reinforcement learning tracking control method is effective. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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