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This paper describes the design and implementation of a repetitive controller (RC) for tracking periodic trajectories in aerial robots, such as unmanned aerial vehicles (UAVs). The RC is ideally suited for situations where the robot is required to execute a defined flight pattern, over and over again in a periodic fashion. Applications include precision agriculture, and search and rescue, where the...
In this paper, we consider a feedforward neural network for the control of a class of multi-input, multi-output nonlinear systems. While feedforward neural networks offer a simple and appealing approach to enhance the trajectory tracking performance of the closed loop system, stability analysis is often more difficult than the conventional implementation of a neural network embedded within the feedback...
This paper addresses the issue of trajectory tracking control based on a neural network controller for industrial manipulators. A new control scheme is proposed based on neural network technology and linear feedback approach for tracking a planned trajectory. The control system is established with two parallel subsystems designed separately. One is a linear controller based on state feedback with...
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