Design of Anti-Swing PID Controller for Bridge Crane Based on PSO and SA Algorithm

Abstract

Since the swing of the lifting load and the positioning of the trolley during the operation of a bridge crane seriously affect the safety and reliability of its work, we have not only designed Proportional Integral Derivative (PID) controllers for the anti-swing and positioning control but also proposed a hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithm to optimize the gains of the controllers. In updating the PSO algorithm, a nonlinear adaptive method is utilized to update the inertia weight and learning coefficients, and the SA algorithm is also integrated when the PSO algorithm is searching for a global optimal solution, to reduce the probability of falling into the local optimal solution. The simulation results demonstrate that the PSO–SA algorithm proposed in this paper is prone to be a more effective method in searching for the optimal parameters for the controllers, compared with three other algorithms. As shown by the experimental results, the swing angle stabilization time of the novel algorithm is 6.9 s, while the values of the other algorithms range from 10.3 to 13.1 s under a common working condition. Simultaneously, the maximum swing angle of the novel algorithm is 7.8°, which is also better than the other algorithms.

The Prescribed-Time Sliding Mode Control for Underactuated Bridge Crane

“…The problem of positioning and swing elimination in bridge crane systems has been extensively researched. This research encompasses open-loop control methods such as input shaping [1] and trajectory planning [2,3], as well as closed-loop control methods, like PID control [4,5], backstepping control [6,7], fuzzy control [8], and sliding mode control [9][10][11][12]. The core idea of input shaping and trajectory planning is to design the acceleration of the trolley, so as to reduce the swing of the load as much as possible during the movement of the trolley.…”

Intelligent Positioning System Design for Bridge Crane in Hydropower Plant

“…In the early stage, the focus was mainly on the S-curve velocity trajectory planning [1] and trapezoidal velocity trajectory planning [2], and studied the uniform acceleration and variable acceleration control of the bridge crane respectively. Later, with the deepening of the research, scholars began to focus on applying classical control theory to the anti-swing control of bridge crane, which mainly includes fuzzy PID control [3][4][5][6] and sliding mode control [7,8]. At the same time, many scholars have applied computer vision to the 3D map construction of cranes [9], swing angle measurement [10], and position detection [11,12], etc.…”

Specific Point in Time Excitation Control Method for Spatial Multi-Degree-of-Freedom Systems under Continuous Operation

“…A proportional integral differential controller is designed for anti-swing and positioning control, and a hybrid particle swarm optimization and simulated annealing algorithm are proposed to optimize the gain of the controller. A coordinated control method between the track and trolley of double-pendulum cranes is also proposed, which improves the working efficiency of double-pendulum cranes and realizes the anti-pendulum control of them in a three-dimensional motion mode [13][14][15].…”