AIMar 27, 2013

A Hierarchical Approach to Designing Approximate Reasoning-Based Controllers for Dynamic Physical Systems

arXiv:1304.1124v178 citations
Originality Synthesis-oriented
AI Analysis

This provides a complementary approach to conventional analytical control methods, useful in scenarios where precise mathematical models are unavailable, but it appears incremental in its application to a standard benchmark problem.

The paper tackles the problem of controlling dynamic physical systems with interacting goals by introducing a hierarchical approximate reasoning-based controller, and demonstrates its effectiveness by solving the cart-pole balancing problem in real-time using a rule-based program and prototype hardware.

This paper presents a new technique for the design of approximate reasoning based controllers for dynamic physical systems with interacting goals. In this approach, goals are achieved based on a hierarchy defined by a control knowledge base and remain highly interactive during the execution of the control task. The approach has been implemented in a rule-based computer program which is used in conjunction with a prototype hardware system to solve the cart-pole balancing problem in real-time. It provides a complementary approach to the conventional analytical control methodology, and is of substantial use where a precise mathematical model of the process being controlled is not available.

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