Abstract
This chapter presents an architecture for precise tracking of autonomous robots based on a novel intelligent adaptive control approach. The scheme evolved from a supervisory loop concept([9]-[12],[18]) consisting of two control algorithms that work in an autonomous manner for the precision control of such nonlinear dynamic systems. The first algorithm is a neuro-controller that monitors the system’s closed loop dynamics while functional changes occur, based on supervised motor learning. The second one is an adaptive controller which controls the system dynamics when parametric changes occur based on a Model Reference Adpative Control (MRAC) strategy. First, the chapter discusses theoretical formulation and design considerations. The theoretical formulations are also analyzed for closed loop stability based on a Lyapunov function candidate. Then, results are presented for simulation and real-time implementation of the position tracking conducted on a single link flexible manipulator nonlinear model and a mobile wheeled robot, respectively. Finally, the chapter concludes by illustrating how this concept can be expanded in the presence of multiple-modes and emergent behaviors.
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Kamalasadan, S., Ghandakly, A.A. (2009). A Novel Intelligent Control Approach for Precise Tracking of Autonomous Robots. In: Liu, D., Wang, L., Tan, K.C. (eds) Design and Control of Intelligent Robotic Systems. Studies in Computational Intelligence, vol 177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89933-4_12
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DOI: https://doi.org/10.1007/978-3-540-89933-4_12
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