A course in fuzzy systems and control
A course in fuzzy systems and control
Design of a GA-based fuzzy PID controller for non-minimum phase systems
Fuzzy Sets and Systems
Multi-objective Evolutionary Design of Fuzzy Autopilot Controller
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Practical Genetic Algorithms with CD-ROM
Practical Genetic Algorithms with CD-ROM
Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers
Engineering Applications of Artificial Intelligence
Multiobjective evolution based fuzzy PI controller design for nonlinear systems
Engineering Applications of Artificial Intelligence
Journal of Intelligent and Robotic Systems
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In this paper, an efficient strategy is proposed to design the altitude hold mode autopilot for a UAV which is non-minimum phase, and its model includes both parametric uncertainties and unmodeled nonlinear dynamics. This work has been motivated by the challenge of developing and implementing an autopilot that is robust with respect to these uncertainties. By combination of classic controller as the principal section of the autopilot and the fuzzy logic controller to increase the robustness in a single loop scheme, it is tried to exploit both methods advantages. The multi-objective genetic algorithm is used to mechanize the optimal determination of fuzzy logic controller parameters based on an efficient cost function that comprises undershoot, overshoot, rise time, settling time, steady state error and stability. Simulation results show that the proposed strategy performances are desirable in terms of the time response characteristics for both phugoid mode and short period mode, the robustness, and the adaptation of itself with respect to the large commands.