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Publication Type : Conference Paper
Publisher : 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT)
Source : 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), IEEE, Kollam, India (2017)
Url : https://ieeexplore.ieee.org/document/8074232
ISBN : 9781509049677
Keywords : Acceleration, Cranes, energy time graph acceleration, Genetic algorithm, Genetic algorithms, Graph theory, inequality constraints, Linear programming, Motion planning, Multiobjective optimization, open loop scheme, optimal control, optimal control models, Optimization, optimization SQP, optimization technique, overhead crane, Payloads, PID Controller, Quadratic programming, SQP, swing, three-term control, Trajectory, Transportation, transportation time, underactuated
Campus : Amritapuri
School : School of Engineering
Department : Robotics and Automation, Electrical and Electronics
Year : 2017
Abstract : Overhead cranes are commonly used in industries for the displacement of materials. Overhead cranes are modelled. Various trajectories are generated based on the open loop scheme. So, optimal control models have been proposed including energy, swing and transportation time. For optimization SQP is used as the optimization technique. It includes objective function for energy, swing and transportation time. Various constraints need to be satisfied. Constraints include both equality and inequality constraints. Multi objective optimization is being performed for optimizing both time and energy at the same time. Genetic algorithm is performed. It is a biologically inspired process. Pareto front is obtained which shows the trade offs between energy and time. By taking slope of energy time graph acceleration is obtained which is fed as reference input to a PID controller and is controlled. The simulations obtained are given in detail.
Cite this Research Publication : P. Chandran, A. Vivek, and Amritha S., “Optimisation of overhead crane”, in 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), Kollam, India, 2017.