New approach to intelligent control systems with self-exploring process

Liang Hsuan Chen, Cheng Hsiung Chiang

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)


This paper proposes an intelligent control system called self-exploring-based intelligent control system (SEICS). The SEICS is comprised of three basic mechanisms, namely, controller, performance evaluator (PE), and adaptor. The controller is constructed by a fuzzy neural network (FNN) to carry out the control tasks. The PE is used to determine whether or not the controller's performance is satisfactory. The adaptor, comprised of two elements, action explorer (AE) and rule generator (RG), plays the main role in the system for generating new control behaviors in order to enhance the control performance. AE operates through a three-stage self-exploration process to explore new actions, which is realized by the multiobjective genetic algorithm (GA). The RG transforms control actions to fuzzy rules based on numerical method. The application of the adaptor can make a control system more adaptive in various environments. A simulation of the robotic path-planning is used to demonstrate the proposed model. The results show that the robot reaches the target point from the start point successfully in the lack-of-information and changeable environments.

Original languageEnglish
Pages (from-to)56-66
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number1
Publication statusPublished - 2003 Jan 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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