
An iterative learning control (ILC) strategy is proposed, and implemented on simple pendulum and double pendulum models of an overhead crane undergoing simultaneous traveling and hoisting maneuvers. The approach is based on generating shaped commands using the full nonlinear equations of motion combined with the iterative learning control, to use as acceleration commands to the jib of the crane. These acceleration commands are tuned to eliminate residual oscillations in rest-to-rest maneuvers. The performance of the proposed strategy is tested using an experimental scaled model of an overhead crane with hoisting. The shaped command is derived analytically and validated experimentally. Results obtained showed that the proposed ILC control strategy is capable of eliminating travel and residual oscillations in simple and double pendulum models with hoisting. It is also shown, in all cases, that the proposed approach has a low sensitivity to the initial cable lengths.
Iterative Learning Control in Engineering Practice, Artificial intelligence, Iterative learning control, Economics, Motion Control, Iterative Learning Control, FOS: Mechanical engineering, Hydraulic Systems Control and Optimization, Adaptive Control, Engineering, Pendulum, Input shaping, Classical mechanics, Position (finance), Vibration control, Control engineering, Physics, Sensitivity (control systems), Mechanical engineering, Algorithm, Residual, Physical Sciences, QC1-999, Acceleration, Structural engineering, Geometry, Control (management), Quantum mechanics, Vibration, Double pendulum, Rest (music), Repetitive Control, Point (geometry), Dynamics and Control of Multibody Mechanical Systems, Control theory (sociology), FOS: Mathematics, Inverted pendulum, Electronic engineering, Mechanical Engineering, Acoustics, Computer science, Overhead (engineering), Input Shaping Control, Control and Systems Engineering, Electrical engineering, Overhead crane, Nonlinear system, Mathematics, Finance
Iterative Learning Control in Engineering Practice, Artificial intelligence, Iterative learning control, Economics, Motion Control, Iterative Learning Control, FOS: Mechanical engineering, Hydraulic Systems Control and Optimization, Adaptive Control, Engineering, Pendulum, Input shaping, Classical mechanics, Position (finance), Vibration control, Control engineering, Physics, Sensitivity (control systems), Mechanical engineering, Algorithm, Residual, Physical Sciences, QC1-999, Acceleration, Structural engineering, Geometry, Control (management), Quantum mechanics, Vibration, Double pendulum, Rest (music), Repetitive Control, Point (geometry), Dynamics and Control of Multibody Mechanical Systems, Control theory (sociology), FOS: Mathematics, Inverted pendulum, Electronic engineering, Mechanical Engineering, Acoustics, Computer science, Overhead (engineering), Input Shaping Control, Control and Systems Engineering, Electrical engineering, Overhead crane, Nonlinear system, Mathematics, Finance
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