| Li Heng(李 恒),Zhu Gongcai,Liu Andong,Ni Hongjie.[J].高技术通讯(英文),2026,32(1):49~59 |
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| Gaussian process based model predictive tracking control with improved iLQR |
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| DOI：10. 3772 / j. issn. 1006-6748. 2026. 01. 006 |
| 中文关键词: |
| 英文关键词: model predictive control, Gaussian process, iterative linear quadratic regulator,trajectory tracking |
| 基金项目: |
| Author Name | Affiliation | | Li Heng(李 恒) | (College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, P. R. China) | | Zhu Gongcai | | | Liu Andong | | | Ni Hongjie | |
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| 中文摘要: |
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| 英文摘要: |
| This article proposes a Gaussian process (GP) based model predictive control (MPC) method to solve the tracking control of wheeled mobile robot ( WMR) with uncertain model parameters.Firstly, a Gaussian process velocity prediction model is proposed to compensate for the unknown dynamic model, as the kinematic model cannot accurately characterize the motion characteristics of the robot. Then, by introducing the Lorentz function, the improved iterative linear quadratic regulator (iLQR) method is used to solve the nonlinear MPC (NMPC) controller with constraints. In addition, in order to reduce computational burden, a closed gradient calculation method is introduced to improve algorithm efficiency. Finally, the feasibility and effectiveness of this method are verified through simulation and experiment. |
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