Dynamic analysis and neural adaptive control of multi-load coupled tracking system under foundation motion excitation

For the high-precision control problem of multi-load coupled tracking systems under foundation motion excitation, the multi-load coupled tracking system is simplified into two independent sets of two inertia servo systems through forward and inverse kinematics solutions. The nonlinear dynamic models of the system with lumped uncertainty are derived and the lumped uncertainty is estimated using a class of BP neural networks. The neural adaptive controller for a multi-load coupled tracking system under foundation motion excitation is designed to achieve decoupling control of the system. On this basis, a naval gun is set as the verification object. The mechanical–electrical-hydraulic coupling dynamic model of the naval gun and the random foundation motion model of the pedestal are established. The effectiveness of the research method in the paper is verified through the application simulation on the naval gun pointing control problem under the foundation motion excitation of the warship. The research provides technical references for high-precision control of multi-load coupled tracking systems under foundation motion excitations such as naval guns and wave compensation gangways.