Positioning And Anti-Swing Control Of Tower Crane

Tower crane has the advantages of small occupied area and easy installation and transportation.It is widely used for on-site cargo transportation in modern industry especially in construction industry.The load and the car are connected by a cable in the tower crane,therefore,it is susceptible to environmental disturbances during operation.The swing phenomenon appears during load transportation,which brings difficulties for controller design and safety risks.At present,when the load swings are reduced by manual operation of the workers,which need the skill of the worker and cause the working efficiency decreasing and also security risks.In this paper,INTECO's Tower Crane experimental system is used as the plant to study the anti-swing control.According to the operating characteristics of the tower crane,its movement includes variable amplitude movement,rotary motion and lifting movement.This paper mainly focus on the variable amplitude motion of tower cranes.In order to achieve the accurate positioning and anti-swing,the main work is as follows:First,in order to achieve accurate positioning of the car while suppressing load swing,the two PID controller parameters are optimized by the multi-objective particle swarm optimization(PSO)algorithm.When the plant parameters used in the PSO are inaccurate or there is an uncertain environment disturbance,the car will deviate from the desired position and the load swing angle is enlarged.Therefore,conventional PID control has restriction in the application of tower crane systems.Secondly,since the complete feedback linearization cannot be achieved for the under-actuation tower cranes,the partial feedback linearization method is used to linearize the nonlinear model and stabilize its internal dynamics.Simulation and experiment are carried out,and the results show the effectiveness of the scheme.The controller can drive the crane quickly and accurately prevent the large swing.Thirdly,a traditional sliding mode variable structure controller(SMC)and a hierarchical sliding mode controller(HSMC)are designed and verified by experiments.The hyperbolic tangent function is used instead of the sgn function to solve the jitter problem.The SMC can still achieve the control requirements well when the uncertainty of the parameters and the upper limit of the disturbance are known.Fourth,in practical applications,the uncertainty of parameters and the upper limit of disturbance are often unknown.Therefore,SMC and HSMC applications are limited in this case.An adaptive backstepping sliding mode control(ABSMC)method is proposed to estimate the uncertainty and external disturbance of the model to obtain better robustness.Fifth,the accurate model of the crane is usually difficult to obtain.The RBF neural network and the sliding mode variable structure control can realize the object control without the need of the model.This paper verifies the positioning and anti-swing the tower crane based on the RBF neural sliding mode controller.