Modified adaptive input shaping for maneuvering cranes using a feedback MEM gyroscope with null drift

Abstract

This paper presents an adaptive algorithm to reduce residual vibrations when the feedback sensor used has the drawback of having null drift along the time. The adaptive approaches are useful to deal with large variations of the system parameters at each maneuver, such as it occurs in cranes. For the feedback sensor, the use of inertial measurement units such as Micro-Electro-Mechanical Systems (MEMS) is increasingly extended because of their cost, size, robustness and power consumption. However, the effectiveness of the adaptive input shaping algorithms is compromised because of this drift, which is a commonly raised issue in this kind of devices. For a standard crane application, this major drawback could be avoided with a frequent time-basis calibration of the sensor, but it is not a feasible solution. The study presented in this manuscript focuses on the development of an automatic compensation of this drift to obviate such frequent calibrations. It is based on a non-asymptotic algebraic identification technique, which has the advantage of not requiring initial conditions and having a short convergence time. The new formulation uses the Zero-Vibration (ZV) input shaper technique, and the null drift is added to the algorithm as a new parameter to be identified. The proposed method has been particularized for single maneuvers of cranes with a gyroscope as feedback sensor, in a real time scenario. Experimental results show the efficacy of the method with its application to a scaled crane test platform. P R E -P R I N T V E R S I O N

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Nonlinear state feedback controller combined with RBF for nonlinear underactuated overhead crane system

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