This paper discusses flying objects’ adaptive control with direct application to the flight of helicopters. Two new automatic adaptive control systems are suggested: the former is used for pitch angle control, while the latter is used for control of helicopter pitch angle and velocity; this second system is an extension of the first one. The adaptive control is based on the dynamic inversion principle and the use of neural networks. The two adaptive control systems have reference models, linear dynamic compensators, linear observers, and neural networks. The adaptive components of the automatic control laws compensate for the approximation errors of the dynamic model’s nonlinear functions. The used actuators are linear or nonlinear. To eliminate the neural networks’ adapting difficulties, a pseudo-control hedging (PCH) block is inserted in the adaptive system; it limits the adaptive pseudo-control by means of a component that represents the estimation error of the actuator dynamics. Thus, the PCH block moves back the reference model—i.e., it introduces a reference model response correction with respect to the actuator position estimation; the signal provided by the PCH block represents a reference model’s additional input. For the two new automatic adaptive control systems, a technical computing environment is used to obtain time characteristics of the adaptive systems with linear and nonlinear actuators. Phase trajectories of the two adaptive control systems with nonlinear actuators express the convergence of the nonlinear systems to stable limit cycles.
Adaptive Control of Helicopter Pitch Angle and Velocity
Journal of Aerospace Engineering ; 27 , 5
17.10.2012
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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