2018/05/04 by Md Meftahul Ferdaus, Mahardhika Pratama, Ferdaus, Md Meftahul +5
Computer Science · Engineering · #Adaptive Control of Nonlinear Systems #Adaptive Dynamic Programming Control #Advanced Control Systems Optimization #FOS: Computer and information sciences #FOS: Electrical engineering #Robotic Path Planning Algorithms #Robotics (cs.RO) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1805.02508
openalex publication_date 2018/05/04 · openalex created_date 2022/08/16 · openalex updated_date 2026/07/28
Nowadays, the application of fully autonomous system like rotary wing\nunmanned air vehicles (UAVs) is increasing sharply. Due to the complex\nnonlinear dynamics, a huge research interest is witnessed in developing\nlearning machine based intelligent, self-organizing evolving controller for\nthese vehicles notably to address the system's dynamic characteristics. In this\nwork, such an evolving controller namely Generic-controller (G-controller) is\nproposed to control the altitude of a rotary wing UAV namely hexacopter. This\ncontroller can work with very minor expert domain knowledge. The evolving\narchitecture of this controller is based on an advanced incremental learning\nalgorithm namely Generic Evolving Neuro-Fuzzy Inference System (GENEFIS). The\ncontroller does not require any offline training, since it starts operating\nfrom scratch with an empty set of fuzzy rules, and then add or delete rules on\ndemand. The adaptation laws for the consequent parameters are derived from the\nsliding mode control (SMC) theory. The Lyapunov theory is used to guarantee the\nstability of the proposed controller. In addition, an auxiliary robustifying\ncontrol term is implemented to obtain a uniform asymptotic convergence of\ntracking error to zero. Finally, the G-controller's performance evaluation is\nobserved through the altitude tracking of a UAV namely hexacopter for various\ntrajectories.\n