%0 Thesis %1 tunstel:thesis %A Tunstel, Edward W. %C Albuquerque, New Mexico, NM 87131, USA %D 1996 %K algorithms, genetic programming, robot %T Adaptive Hierarchy of Distributed Fuzzy Control: Application to Behavior Control of Rovers %U http://www.eece.unm.edu/grad/tunstel/diss/disspage.htm %X This dissertation addresses the synthesis of knowledge-based controllers for complex autonomous systems that interact with the real world. A fuzzy logic rule-based architecture is developed for intelligent control of dynamic systems possessing a significant degree of autonomy. It represents a novel approach to controller synthesis which incorporates fuzzy control theory into the framework of behavior-based control. The controller intelligence is distributed amongst a number of individual fuzzy logic controllers and systems arranged in a hierarchical structure such that system behavior at any given level is a function of behavior at the level(s) below. This structure addresses the combinatorial problem associated with large rule-base cardinality, as the totality of rules in the system are not processed during any control cycle. A method of computationally evolving fuzzy rule-bases is also introduced. It is based on the genetic programming paradigm of evolutionary computation and directly manipulates linguistic terminology of the system. This provides a systematic rule-base design method which is more direct than current approaches that mandate numerical encoding/decoding of rule representations. Finally, a mechanism for multi-rule base coordination is devised by generalization of fuzzy logic theoretic concepts. It is incorporated to endow the system with the capability to dynamically adapt its control policy in response to goals, internal system state, and perception of the environment. The validity and practical utility of the approach is verified by application to autonomous navigation control of wheeled mobile robots, or rovers. Simulated and experimental navigation results produced by the adaptive hierarchy of distributed fuzzy control are reported. Results show that the proposed ideas can be useful for realization of autonomous rovers that are meant to be deployed in dynamic and possibly unstructured environments. This class of computer-controlled, wheeled mobile vehicles includes industrial mobile robots, automated guided vehicles, office or hospital robots, and in some cases natural terrain vehicles such as planetary rovers. The proposed intelligent control architecture is generally applicable to autonomous systems whose overall behavior can be decomposed into a bottom-up hierarchy of increased behavioral complexity, or a decentralized structure of multiple rule-bases.

@phdthesis{tunstel:thesis, abstract = {This dissertation addresses the synthesis of knowledge-based controllers for complex autonomous systems that interact with the real world. A fuzzy logic rule-based architecture is developed for intelligent control of dynamic systems possessing a significant degree of autonomy. It represents a novel approach to controller synthesis which incorporates fuzzy control theory into the framework of behavior-based control. The controller intelligence is distributed amongst a number of individual fuzzy logic controllers and systems arranged in a hierarchical structure such that system behavior at any given level is a function of behavior at the level(s) below. This structure addresses the combinatorial problem associated with large rule-base cardinality, as the totality of rules in the system are not processed during any control cycle. A method of computationally evolving fuzzy rule-bases is also introduced. It is based on the genetic programming paradigm of evolutionary computation and directly manipulates linguistic terminology of the system. This provides a systematic rule-base design method which is more direct than current approaches that mandate numerical encoding/decoding of rule representations. Finally, a mechanism for multi-rule base coordination is devised by generalization of fuzzy logic theoretic concepts. It is incorporated to endow the system with the capability to dynamically adapt its control policy in response to goals, internal system state, and perception of the environment. The validity and practical utility of the approach is verified by application to autonomous navigation control of wheeled mobile robots, or rovers. Simulated and experimental navigation results produced by the adaptive hierarchy of distributed fuzzy control are reported. Results show that the proposed ideas can be useful for realization of autonomous rovers that are meant to be deployed in dynamic and possibly unstructured environments. This class of computer-controlled, wheeled mobile vehicles includes industrial mobile robots, automated guided vehicles, office or hospital robots, and in some cases natural terrain vehicles such as planetary rovers. The proposed intelligent control architecture is generally applicable to autonomous systems whose overall behavior can be decomposed into a bottom-up hierarchy of increased behavioral complexity, or a decentralized structure of multiple rule-bases.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Albuquerque, New Mexico, NM 87131, USA}, author = {Tunstel, Edward W.}, biburl = {https://www.bibsonomy.org/bibtex/2da8e4019f9539414b9f1edc8bd59a925/brazovayeye}, interhash = {248dd015c104788516d3038c33d33531}, intrahash = {da8e4019f9539414b9f1edc8bd59a925}, keywords = {algorithms, genetic programming, robot}, month = {December}, school = {Electrical and Computer Engineering, University of New Mexico}, size = {pages}, timestamp = {2008-06-19T17:53:22.000+0200}, title = {Adaptive Hierarchy of Distributed Fuzzy Control: Application to Behavior Control of Rovers}, url = {http://www.eece.unm.edu/grad/tunstel/diss/disspage.htm}, year = 1996 }