Energy Optimization of Under-actuated Crane Model for Time-Variant Load Transferring Using Optimized Adaptive Combined Hierarchical Sliding Mode Controller

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AHMADI MARZIEH; FARAJI ALIREZA

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Journal Paper

Paper Information

Journal: JOURNAL OF ENERGY MANAGEMENT Year:2022 | Volume:11 | Issue:4 Page(s): 2-9

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Information Journal Paper

Title

Energy Optimization of Under-actuated Crane Model for Time-Variant Load Transferring Using Optimized Adaptive Combined Hierarchical Sliding Mode Controller

Author(s)

AHMADI MARZIEH | FARAJI ALIREZA | Issue Writer Certificate

Keywords

Time-varying crane model

Uncertainty modelling

Adaptive Control

Combined Hierarchical Sliding Mode Control

Genetic algorithm

Particle Swarm Optimization

Abstract

This paper designs an Optimized Adaptive Combined Hierarchical Sliding Mode Controller (OACHSMC) for a timevarying crane model in presence of uncertainties. Uncertainties have always been one of the most important challenges in designing control systems, which include unknown parameters or un-modeled dynamics in systems. Sliding mode controller (SMC) is able to compensate the system in the presence of uncertainties due to un-modeled dynamics and is used for robust stability and performance behavior in the presence of additive un-modeled dynamics of system and multiplicative friction forces. This under-actuated crane has two sub-systems: trolley and payload. Therefore, it can be controlled by a single input signal with Combined Hierarchical Sliding Mode Controller (CHSMC) using a two-layersliding manifold accurately. Payload mass and cable length are time-variant variables through load transferring. Due to the Time-varying models and the inefficiency of most controllers, the use of an Adaptive Controller can help improve system performance. This controller is adapted by considering a time-varying coefficient of the second layer sliding manifold. For energy saving of the input signal, the parameter of the first layer sliding manifold of ACHSMC is optimized by two intelligent strategies: Genetic algorithm (GA) and Particle Swarm Optimization (PSO) method. The simulation results show robust stability and performance of the proposed optimized controller.

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APA: Copy

AHMADI, MARZIEH, & FARAJI, ALIREZA. (2022). Energy Optimization of Under-actuated Crane Model for Time-Variant Load Transferring Using Optimized Adaptive Combined Hierarchical Sliding Mode Controller. JOURNAL OF ENERGY MANAGEMENT, 11(4 ), 2-9. SID. https://sid.ir/paper/992593/en

Vancouver: Copy

AHMADI MARZIEH, FARAJI ALIREZA. Energy Optimization of Under-actuated Crane Model for Time-Variant Load Transferring Using Optimized Adaptive Combined Hierarchical Sliding Mode Controller. JOURNAL OF ENERGY MANAGEMENT[Internet]. 2022;11(4 ):2-9. Available from: https://sid.ir/paper/992593/en

IEEE: Copy

MARZIEH AHMADI, and ALIREZA FARAJI, “Energy Optimization of Under-actuated Crane Model for Time-Variant Load Transferring Using Optimized Adaptive Combined Hierarchical Sliding Mode Controller,” JOURNAL OF ENERGY MANAGEMENT, vol. 11, no. 4 , pp. 2–9, 2022, [Online]. Available: https://sid.ir/paper/992593/en

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