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基于自适应小脑模型关节控制器的导弹制导律设计

Missile guidance law design using adaptive cerebellar model articulation controller.

作者信息

Lin Chih-Min, Peng Ya-Fu

机构信息

Department of Electrical Engineering, Yuan-Ze University, Chung-Li 320 Taiwan, ROC.

出版信息

IEEE Trans Neural Netw. 2005 May;16(3):636-44. doi: 10.1109/TNN.2004.839358.

Abstract

An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law.

摘要

提出了一种自适应小脑模型关节控制器(CMAC)用于视线(CLOS)导弹制导律设计。在该设计中,三维(3-D)CLOS制导问题被表述为一个时变非线性系统的跟踪问题。自适应CMAC控制系统由一个CMAC和一个补偿控制器组成。CMAC控制用于模仿反馈线性化控制律,补偿控制器用于补偿反馈线性化控制律与CMAC控制之间的差异。基于李雅普诺夫稳定性定理推导了在线自适应律,以学习CMAC控制中感受野基函数的权重。此外,为了放宽对逼近误差界的要求,推导了一种估计律来估计误差界。然后设计自适应CMAC控制系统以实现令人满意的跟踪性能。不同交战场景的仿真结果说明了所提出的基于自适应CMAC的制导律的有效性。

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