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This paper presents an intelligent adaptive trajectory tracking controller using fuzzy basis function networks FBFN for an autonomous small-scale helicopter. The FNFN is used online to learn the vehicle mass and the coupling effect between the force and the moments, and the intelligent adaptive controller then is synthesized systematically using a backstepping technique. This controller is designed to accomplish the ultimate boundedness of the closed-loop helicopter dynamics and accommodate agile flight maneuvers. Two nonlinear simulations on hovering and trajectory tracking are conducted to show the effectiveness and merit of the proposed controller, which is also shown to be superior by performance comparison with a well-known neural-network controller.

This paper presents techniques for adaptive pressure tracking and breathing period prediction in an obstructive sleep apnea (OSA) treatment system by means of bi‐level positive airway pressure (BiP...

This paper presents a two degree‐of‐freedom control method for achieving constant continuous positive airway pressure (CPAP) of an obstructive sleep apnea (OSA) treatment system. After constructing a closed‐loop DC brushless motor drive together with a blower and an airway module, we develop a pressure control system for achieving CPAP control. A mathematical model of the overall open‐loop system is established based on the input‐output data and its system parameters are sequentially determined using the recursive least‐squares (RLS) method. A two degree‐of‐freedom (DOF) controller, including a feedforward controller and a feedback proportional‐integral controller, is proposed to maintain and follow the desired pressure setpoints. Through experimental results, the proposed control method is shown useful and effective in achieving airway pressure tracking and regulation.

This paper develops an adaptive dynamic motion controller for position control and trajectory tracking of the omnidirectional mobile robot equipped with four independent omnidirectional wheels equally spaced at 90 degrees from one to another. Such a controller is synthesized by backstepping and will be is proven globally asymptotically stable via the Lyapunov stability theory. The controller is particularly adequate for the robot while navigating over its working environment at any speeds. The effectiveness and merit of the proposed control method is exemplified by conducting several simulations.

This paper presents a two degree-of-freedom control method for achieving bi-level positive airway pressure (Bi-PAP) of an obstructive sleep apnea (OSA) treatment system. After constructing a closed-loop DC brushless motor which is based on a microchip (dsPIC30F3010) drive together with a blower and an airway module, we develop a pressure control system for achieving Bi-PAP control. A mathematical model of the overall open-loop system is established based on the input-output data and its system parameters are sequentially determined using the recursive least-squares (RLS) approach. A two degree-of-freedom (DOF) controller, including a nonlinear feedforward controller and a feedback proportional-integral-derivative controller (PID controller) with gain scheduling, is proposed to maintain and follow the desired bi-level pressure setpoints. Through experimental results, the proposed control method is shown useful and effective in achieving bi-level airway pressure tracking.