Research On Intelligent Anti-Sway Control Strategy Of Underactuated Bridge Crane

An underactuated mechanical system means a mechanical system where the number of the driver is less than the degree of freedom.Compared with the fully driven mechanical system,due to less driver,an underactuated mechanical system features with reduced weight,lowered energy consumption and flexible movement,therefore is widely used in various fields of industry with a dominating status.However,it is less driver that limits the state of the system in an indeterminate configuration in the motion space,which greatly increases the complexity of designing its control system.As a result,over the past two decades the control problem of underactuated mechanical systems has been a big challenge in the field of engineering control.Bridge crane is a typical kind of underactuated system with strong nonlinearity and intercoupling.Because of larger load capacity,lower energy consumption,simpler and more flexible operation,it has been widely used in industrial production,port & transportation and other fields.On the other hand,as it could be greatly affected by the external disturbances,it becomes prone to swing,which would reduce system stability and hence reduce production economy.Therefore,its control system design needs to further investigated to obtain a reasonable anti-shake algorithm or control strategy.In recent years,Model predictive control(MPC)has widely been put into use in industrial applications.MPC is a control algorithm designed on the basis of the model of the control system.It takes effect by predicting the future outputs based on historical information and future inputs of the system.Any type of the set of information,as long as it has predictive capability,can be transformed to a predictive model.Differing from the traditional optimal control method,MPC adopts online real-time iterative optimization and timely compensation for the interference,thus effectively solves the problems caused by the uncertainties arising from model mismatch,time-varying and interference.As a result,MPC can play a good role in the control of the crane system.In this paper,MPC of the crane system is researched in-depth.The PID control algorithm is traditionally used in crane system control.It can lead better control effects even while the accurate mathematical model does not exist as long as the PID parameters are adjusted properly.However,if PID control is used in a double-closed-loop system,the control performance will greatly deteriorate in the case of interference and parameter changes,even worst cause an accident.Therefore in this paper we use MPC to replace the traditional double closed-loop PID control,and study the control strategy for a two-degree of freedom fixed rope long crane system.By using the Homeomorphic transformation method,the nonlinear characteristics of the system are equivalently transformed into Equivalent Input Disturbance(EID),which makes the crane system be equivalent to a linear system and then reduces the difficulty of control system design.With comprehensively considering the untestable constant value interference,modeling error and external environment impact on the system performance of the actual system,a predictive control strategy without static error is designed to realize the global stability control of crane operation.The simulation and experimental results show that the intelligent bridge crane control strategy designed in this paper can effectively realize the high-precision positioning and load-proof swing of the crane,and improve the stability and safety of the crane movement.The superiority of the controller proposed in this paper is verified by experiments under the MATLAB Simulink simulation platform.In addition,by establishing an experimental platform,the experimental results verify the correctness and feasibility of the predictive control algorithm we proposed.