tailieunhanh - High order sliding mode control with anti-sway based compensation on artificial neural network by pso algorithm for overhead crane

This paper proposes a second order sliding mode controller combined with signal set calibrator for overhead crane tracking desired position and resisting disturbance. High order sliding mode controller ensures that the overhead crane tracks desired trajectory and resists disturbance. | Vietnam Journal of Science and Technology 55 (3) (2017) 347-356 DOI: HIGH ORDER SLIDING MODE CONTROL WITH ANTI-SWAY BASED COMPENSATION ON ARTIFICIAL NEURAL NETWORK BY PSO ALGORITHM FOR OVERHEAD CRANE Le Xuan Hai1,*, Nguyen Van Thai1, Vu Thi Thuy Nga1, Hoang Thi Tu Uyen1, Nguyen Thanh Long1, Thai Huu Nguyen2, Phan Xuân Minh1 1 2 Hanoi University of Science and Technology, No 1, Dai Co Viet Street, Hai Ba Trung District, Ha Noi City Vinh University of Technology Education, Hung Dung Ward, Vinh City, Nghe An Province * Email: Received: 15 August 2016; Accepted for publication: 2 March 2017 ABSTRACT This paper proposes a second order sliding mode controller combined with signal set calibrator for overhead crane tracking desired position and resisting disturbance. High order sliding mode controller ensures that the overhead crane tracks desired trajectory and resists disturbance. Neural network is trained by particle swarm optimization algorithm (PSO) to compensate anti-sway for load. The results on the computer simulation show that high order sliding mode controller with anti-sway compensation for overhead crane tracks desired trajectory and the swing of load that is smaller than high order sliding mode controller without anti-sway compensation. Keywords: high order sliding mode control, artificial neural network, particle swarm optimization algorithm (PSO), anti-sway for overhead crane. 1. PROBLEM STATEMENT Overhead crane is one of the essential equipment that are commonly used in industrial factory, harbors for transporting heavy goods and it is also researching object recently. Mathematical model of overhead crane is categorized as under-actuated robot. The solution to track desired trajectory of trolley and anti-sway of load are particular characteristics of overhead crane. The approaches for anti-sway are based on PD techniques control [1], partial feedback linearization control [2, 3], nonlinear control

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• Vietnam Journal of Science and Technology
• High order sliding mode control
• Anti sway based compensation
• Artificial neural network
• Pso algorithm for overhead crane
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