A new information-weighted recursive algorithm for time-varying systems: application to UAV system identification |
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Authors: | Zun Liu Honghai Ji Frank L Lewis |
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Affiliation: | 1. Key Laboratory of Autonomous System and Networked Control, Ministry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong, South China University of Technology, Guangzhou, People’s Republic of China;2. Advanced Control Systems Lab, School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, People’s Republic of China;3. UTA Research Institute, The University of Texas at Arlington, Ft.Worth, TX, USA |
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Abstract: | This paper presents a new recursive identification method which can efficiently estimate time-varying parameters in discrete time systems and has significant advantages over standard recursive least-squares (RLS) method. This new information-weighted recursive algorithm for time-varying systems has three novel features, discounting of inaccurate estimates through weighting by the Information matrix, using the reuse of past data in computing current parameter estimates, a new tuneable damping factor parameter and a precisely designed compensation term to neutralise the estimation error caused by time-varying coefficients. A rigorous proof of convergence is also provided. Simulations show that the new algorithm significantly outperforms standard RLS, exhibiting better tracking performance and faster convergence. Flight tests on a T-REX 800 helicopter Unmanned Aerial Vehicle platform show that it gives system parameter estimates that are accurate enough and converge quickly enough that flight controllers can be designed in real-time based on the online identified model. |
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Keywords: | System identification experience replay unmanned aerial vehicle online-identification method time-varying system |
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