Intelligent control of nonlinear systems based upon case-based reasoning

提出了一种基于案例推理的智能控制与信号处理方法。用小波变换提取非线性对象的I/O特征，用多分辨模式分析方法区分I/O信号的全局特征和局部特征。利用分层图像编码技术，对提取的特征进行了无退化压缩，并设计了有效的存储过程。推导了一种基于n近邻方法的非线性自适应估计方法，用于从迄今已见的I/O数据中估计查询的输出。观察到的I/O数据以k-d Trie的形式存储在数据库中，并基于正则化理论推导出回答每个查询的非线性局部模型。推导了一种有效的数据库内容跟踪非平稳数据的时间更新方案。为了减少处理时间和存储需求，开发了一种允许简单而高效的更新的存储过程。仿真数据和实际语音信号验证了该方法的有效性。在此基础上，开发了基于人类技能模型的自动着陆系统。该模型被表示为从飞行器状态到人类专家提供的控制命令的非线性I/O映射。所有由人类专家提供的I/O数据都被先验地存储在数据库中，并建立一个本地模型来回答当前飞机的状态，以产生接近人类操作的控制输入。为了提高系统的鲁棒性，引入了一种增益自适应技术。

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.