Abstract
Aerial work platform is a kind of engineering vehicle which is used for hoisting personnel to the appointed place for maintenance or installation. Based on the dynamics model considering the flexible deformation existing in the arm system of folding-boom aerial platform vehicle, this study presents a NN-based backstepping controller used for trajectory tracking control of work platform. The proposed controller can reduce tracking error of work platform and suppress the vibration simultaneously by using the RBF neural network system to compensate model uncertainties and disturbances. Furthermore, we prove that the whole system is stable and convergent by Lyapunov stability theorem. In addition, we give the simulation results which show that the good control performance of the designed controller for trajectory tracking and vibration inhabiting of work platform in the case of model uncertainties.
Highlights
Considering the elastic deformation, the dynamics model of the arm system is created for folding-boom aerial platform vehicle with flexible beam powered by the hydraulic cylinder based on flexible multibody dynamics theory and Lagrange’s equation in Hu et al [3]. e vibration is found in the established equations
Combining the backstepping design method with the artificial neural network (ANN), we propose a controller applied for the trajectory tracking control of work platform
We propose a kind of the NN-based backstepping controller based on a new flexible dynamic model created for aerial platform vehicle with flexible beam driven by hydraulic cylinder
Summary
The elastic deformation will cause vibration and positioning deviation of the work platform. The elastic deformation of beam is ignored in these models established. Considering the elastic deformation, the dynamics model of the arm system is created for folding-boom aerial platform vehicle with flexible beam powered by the hydraulic cylinder based on flexible multibody dynamics theory and Lagrange’s equation in Hu et al [3]. A similar model is created, and a fuzzy PID controller is designed for work platform’s tracking control in Meng [4]. Simulation results reflect the effectiveness of the control method, the stability of the system has not been proved
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