Skip to Main Content
 

Global Search Box

 
 
 
 

ETD Abstract Container

Abstract Header

A New Generation of Adaptive Control: An Intelligent Supervisory Loop Approach

Kamalasadan, Sukumar

Abstract Details

2004, Doctor of Philosophy in Engineering, University of Toledo, Electrical Engineering.
A new class of intelligent adaptive control for systems with complex and multimodal dynamics including scheduled and unscheduled ‘Jumps’, is developed. Those systems are often under the challenge of unforeseen changes due to wide range of operations and/or external influences. The underlying structural feature is an introduction of an Intelligent Supervisory Loop (ISL) to augment the Model Reference Adaptive Control (MRAC) framework. Four novel design formulations are developed which evolve from different methods of conceiving ISL, structured into intelligent control algorithms, and then investigated with comprehensive simulation models of a single link flexible robotic manipulator as well as a six degree of freedom F16 fighter aircraft. The first scheme is a Fuzzy Multiple Reference Model Adaptive Controller (FMRMAC). It consists of a fuzzy logic switching strategy introduced to the MRAC framework. The second is a novel Neural Network Parallel Adaptive Controller (NNPAC) for systems with unmodeled dynamics and mode swings. It consists of an online growing dynamic radial basis neural network, which controls the plant in parallel with a direct MRAC. The third scheme is a novel Neural Network Parallel Fuzzy Adaptive Controller (NNPFAC) for dynamic ‘Jump’ systems showing scheduled mode switching and unmodeled dynamics. The scheme consists of a growing online dynamic Neural Network (NN) controller in parallel with a direct MRAC, and a fuzzy multiple reference model generator. The fourth scheme is a Composite Parallel Multiple Reference Model Adaptive Controller (CPMRMAC) for systems showing unscheduled mode switching and unmodeled dynamics. The scheme consists of an online growing dynamic NN controller in parallel with a direct MRAC, and an NN multiple reference model generator. Extensive feasibility simulation studies and investigations have been conducted on the four proposed schemes, and with results consistently showing that the four design formulations developed in this research, for implementing intelligent supervisory loops into the MRAC framework, are feasible, effective and have immense potential for complex systems control. Even though those two systems are specific in nature, they are true representatives of an important and challenging class of dynamic systems that require the new generation of adaptive controllers developed in this project work.
Adel Ghandakly (Advisor)
254 p.

Recommended Citations

Citations

  • Kamalasadan, S. (2004). A New Generation of Adaptive Control: An Intelligent Supervisory Loop Approach [Doctoral dissertation, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1087223752

    APA Style (7th edition)

  • Kamalasadan, Sukumar. A New Generation of Adaptive Control: An Intelligent Supervisory Loop Approach. 2004. University of Toledo, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1087223752.

    MLA Style (8th edition)

  • Kamalasadan, Sukumar. "A New Generation of Adaptive Control: An Intelligent Supervisory Loop Approach." Doctoral dissertation, University of Toledo, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1087223752

    Chicago Manual of Style (17th edition)