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An Introduction to Intelligent and Autonomous Control-Chapter 3:Model-Based Architecture Concepts for Autonomous Systems Design and Simulation

Tham khảo tài liệu 'an introduction to intelligent and autonomous control-chapter 3:model-based architecture concepts for autonomous systems design and simulation', công nghệ thông tin, quản trị web phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 3 Model-Based Architecture Concepts for Autonomous Systems Design and Simulation Bernard P. Zeigler and Sungdo Chi Al-Simulation Group Department of Electrical and Computer Engineering University of Arizona Tucson AZ 85721 Abstract This chapter presents a coherent methodology to integrate planning operation and diagnosis within autonomous systems. After briefly reviewing the functional aspects of high autonomy we describe a systematic methodology to integrate these aspects within a model-based architecture. Such an architecture is based on suites of models developed to support the various functional aspects or tasks. A general approach to task-based model development is then summarized in a Hierarchical Encapsulation and Abstraction Principle HEAP and this principle is illustrated in the planning operations and diagnosis task domains. 1. OVERVIEW To cope with complex objectives an autonomous system requires integration of symbolic and numeric data qualitative and quantitative information reasoning and computation robustness and refinement discrete event system specification and continuous system specification. In general the Al approach is too qualitatively oriented to handle quantitative information very well. For example classic Al planning approaches 1 2 3 do not consider the timing effects which should be of primary concern in representing our dynamic world. On the other hand control researchers have a fairly narrow view-point so that they mainly focus on refinement rather than robustness of a system 4 and they usually consider only the normal operational aspects of a system 5 6 . However autonomous systems have to deal with abnormal behavior of a system as well. Thus it is crucial to have a strong formalism and an environment that allows coherent integration of symbolic and numeric information in a valid representation process to deal with our complex dynamic world. 58 INTELLIGENT AND AUTONOMOUS CONTROL 1.1 Model-Base Autonomous System Architecture Figure 1.1