Intelligent anti-swing control for bridge crane

A new intelligent anti-swing control scheme,which combined fuzzy neural network(FNN) and sliding mode control(SMC) with particle swarm optimization(PSO),was presented for bridge crane.The outputs of three fuzzy neural networks were used to approach the uncertainties of the positioning subsystem,lifting-rope subsystem and anti-swing subsystem.Then,the parameters of the controller were optimized with PSO to enable the system to have good dynamic performances.During the process of high-speed load hoisting and dropping,this method can not only realize the accurate position of the trolley and eliminate the sway of the load in spite of existing uncertainties,and the maximum swing angle is only ±0.1 rad,but also completely eliminate the chattering of conventional sliding mode control and improve the robustness of system.The simulation results show the correctness and validity of this method.

Robust Anti⁃swing Control for Unmanned Helicopter Slung⁃Load System with Prescribed Performance

A robust anti-swing control method based on the error transformation function is proposed,and the problem is handled for the unmanned helicopter slung-load system(HSLS)deviating from the equilibrium state due to the disturbances in the lifting process.First,the nonlinear model of unmanned HSLS is established.Second,the errors of swing angles are constructed by using the two ideal swing angle values and the actual swing angle values for the unmanned HSLS under flat flight,and the error transformation functions are investigated to guarantee that the errors of swing angles satisfy the prescribed performance.Third,the nonlinear disturbance observers are introduced to estimate the bounded disturbances,and the robust controllers of the unmanned HSLS,the velocity and the attitude subsystems are designed based on the prescribed performance method,the output of disturbance observer and the sliding mode backstepping strategy,respectively.Fourth,the Lyapunov function is developed to prove the stability of the closed-loop system.Finally,the simulation studies are shown to demonstrate the effectiveness of the control strategy.