Intelligent control of nonlinear systems based upon case-based reasoning

基于案例推理的非线性系统智能控制

• 批准号: 08455197
• 负责人: MAEDA Hajime
• 金额: $ 4.42万
• 依托单位: Osaka University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 1996
• 资助国家: 日本
• 起止时间: 1996 至 1998
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-08455197/
• 关键词: nonlinear system; wavelet transform; database; feature extraction; nonlinear signal processing; control law; 非線型システム; 非線型信号処理; ウェーブレット変換; 階層符号化

An approach to intelligent control and signal processing based upon case-based reasoning is presented. The wavelet transform is used to extract I/O characteristics of nonlinear plant, and the multiresolution pattern analysis method is applied to distinguish global and local features of the I/O signals. Using a hierarchical image coding technique, the extracted feasters are compressed without any degradation and their efficient storage procedure is designed. A nonlinear adaptive estimation method based on the n-nearest neighbor approach is derived to estimate the output for a query from the I/O data seen so far. Observed I/O data are stored in a database in the form of a k-d trie and a nonlinear local model to answer each query is derived based upon regularization theory. An efficient time-updating scheme of the database contents to follow nonstationary data is derived. A storage procedure allowing a simple and efficient update is developed for reduction in processing time and storage requirement. The effectiveness of the proposed method is demonstrated with both simulation data and real speech signals. Furthermore, an automatic landing system is developed on the basis of a human skill model. The model is expressed as a nonlinear I/O mapping from the aircraft state to the control command provided by a human expert. All the I/O data provided by the human expert are stored in a database a priori, and a local model to answer the current aircraft state is built to generate a control input close to the human operation. A gain adaptation technique is introduced for improving the robustness.

提出了一种基于案例推理的智能控制和信号处理方法。利用小波变换提取非线性对象的I/O特征，并应用多分辨率模式分析方法区分I/O信号的全局和局部特征。使用分层图像编码技术，对提取的盛宴进行无任何降级的压缩，并设计了其高效的存储过程。推导了一种基于 n​​ 最近邻方法的非线性自适应估计方法，用于根据目前看到的 I/O 数据来估计查询的输出。观察到的 I/O 数据以 k-d trie 的形式存储在数据库中，并根据正则化理论导出用于回答每个查询的非线性局部模型。导出了一种遵循非平稳数据的数据库内容的有效时间更新方案。开发了一种允许简单且高效更新的存储过程，以减少处理时间和存储要求。仿真数据和真实语音信号都证明了该方法的有效性。此外，自动着陆系统是在人类技能模型的基础上开发的。该模型表示为从飞机状态到人类专家提供的控制命令的非线性 I/O 映射。人类专家提供的所有I/O数据都预先存储在数据库中，并建立回答当前飞行器状态的本地模型，以生成接近人类操作的控制输入。引入增益自适应技术来提高鲁棒性。

项目成果

K.Sakitani et al.: "Wavelet representation of linear time-varing systems" Proc.of the 41st Annual Conference of the Institute of Systems, Control and Information Engineers. 223-224 (1997)

K.Sakitani 等人：“线性时变系统的小波表示”，系统、控制和信息工程师学会第 41 届年会论文集。

花木孝史 他: "一般化ホールドを用いた場合の2次形式評価関数の離散可について" 第41回システム制御情報学会研究発表講演会講演論文集. 311-312 (1998)

Takashi Hanaki 等人：“论使用广义保持时二次评估函数的离散性”系统、控制和信息工程师学会第 41 届年会论文集 311-312 (1998)。

Y.Iiguni et al.: "An intelligent landing system based upon a human skill model" IEEE Trans. Aerospace Eletronics Systems. 34/4. 877-882 (1998)

Y.Iiguni 等人：“基于人类技能模型的智能着陆系统”IEEE Trans。

Y.Ito et al.: "Bisection algorithm for computing the frequency response gain of sampled-data systems" Proc.of the 37th IEEE Con-ference on Decision and Control. 841-846 (1998)

Y.Ito 等人：“用于计算采样数据系统频率响应增益的二分算法”Proc.of the 37th IEEE Con​​ference on Decision and Control。

Y.Iiguni et al.: "A nonlinear adaptive estimation method based upon local approximation" IEEE Trans. Signal Processing. vo.45, no.7. 1831-1841 (1997)

Y.Iiguni 等人：“基于局部近似的非线性自适应估计方法”IEEE Trans。