Adsorption control of a pipeline robot based on improved PSO algorithm
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ORIGINAL ARTICLE
Adsorption control of a pipeline robot based on improved PSO algorithm Yilin Yu1 · Yanli Xu1
· Fusheng Wang1 · Wensheng Li2 · Xiaoming Mai2 · Hao Wu2
Received: 2 April 2020 / Accepted: 17 August 2020 © The Author(s) 2020
Abstract Particle swarm optimization (PSO) is a widely used method that can provide good parameters for the motion controller of mobile robots. In this paper, an improved PSO algorithm that optimize the control PID parameters of a specific robot have been proposed. This paper first presents a brief review of recently proposed PSO methods, and then presents a detailed analysis of the PID optimization algorithm, which uses H∞ theory to reduce the search space and fuses the information entropy to ensure the diversity of particles. Simulations in Matlab show that the algorithm can improve the convergence speed and get a better global optimization ability than the standard PSO algorithm. Experimental results present a sound effects for the control of the negative pressure adsorption motor in the power grid pipeline robot during its adsorption along the circular movements, which verifies the effectiveness of the proposed method. Keywords Particle swarm optimization · Pipeline robot · Parameter optimization · PID control · Surface adsorption · H∞ theory
Introduction When adsorption robots carry out circular movement along the inner wall of the electric power pipeline [1], it is necessary to adjust the parameters of the adsorption motor in real time, so as to control the appropriate adsorption force, thus the robot can stably adsorb on each position of the inner wall of the pipeline under the composite action of gravity and suction [2]. In actual motion, the robot often appears adsorption instability or motion jam, due to the time delay of control parameters [3]. This problem of the control system is mainly due to the delay between the feedback and the system output. For the classical PID control algorithm used for the adsorption motor, the main problem is the optimization of key parameters, whose quality directly affects the performance of the system, and even leads to the divergence and oscillation of the control system [4]. Therefore, the parameter optimization of the controller plays an important role for this kind of time-delay system [5], and meanwhile the high-
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Yanli Xu [email protected]
1
Northeast Forestry University, Harbin, China
2
Electric Power Research Institute of Guangdong Power Grid Co., Ltd, Guangzhou, China
order and nonlinearity of the control make it very difficult to adjust the parameters [6]. The traditional PID parameter optimization methods include stable boundary method, attenuation curve method, dynamic characteristic method and Ziegler Nichols empirical method, etc. [7–9]. In recent years, there are many PID parameter tuning methods based on artificial intelligence technology [10], such as expert system method. The PSO PID control algorithm proposed in reference [11] has a good control effect on the process control with large time delay. In r
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