Abstract
The existing third-order tracker known as α-β-γ filter has been used for target tracking and predicting for years. The filter can track the target’s position and velocity, but not the acceleration. To extend its capability, a new fourth-order target tracker called α-β-γ-δ filter is proposed. The main objective of this study was to find the optimal set of filter parameters that leads to minimum position tracking errors. The tracking errors between using the α-β-γ filter and the α-β-γ-δ filter are compared. As a result, the new filter exhibits significant improvement in position tracking accuracy over the existing third-order filter, but at the expense of computational time in search of the optimal filter. To reduce the computational time, a simulation-based optimization technique via Taguchi method is introduced.
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Chun-Mu Wu received the B. Sc. and M. Sc. degrees from Tamkang University, Taiwan, China, and Ph.D. degree from National Cheng Kung University, Taiwan, China. He is currently an associate professor in Department of Mechanical and Automation Engineering at Kao Yuan University, Taiwan, China.
His research interests include numerical analysis, heat transfer analysis, automation engineering, and system monitoring.
Zheng-Yu Han received the B. Sc. degree from China University of Petroleum, China in 2006. He is currently a Ph.D. candidate at the College of Information and Control Engineering, China University of Petroleum.
His research interests include optimal control and robotics, especially the control of robots and trajectory planning.
Shu-Rong Li received the B. Sc. degree from Shandong University, China in 1987, and M. Sc. and Ph.D. degrees from Chinese Academy of Sciences, China in 1990 and 1993. He is currently a professor at the College of Information and Control Engineering, China University of Petroleum, China.
His research interests include nonlinear system, optimal control, and robotics.
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Wu, CM., Lin, P.P., Han, ZY. et al. Simulation-based optimal design of α-β-γ-δ filter. Int. J. Autom. Comput. 7, 247–253 (2010). https://doi.org/10.1007/s11633-010-0247-8
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DOI: https://doi.org/10.1007/s11633-010-0247-8