Dynamic simulation and adaptive backlash compensation control for the naval gun follow-up system with unknown backlash

This paper proposes an adaptive gear backlash compensation control strategy to mitigate the adverse effects of gear backlash nonlinearity on control performance of naval gun follow-up systems, thereby improving shooting accuracy. A nonlinear model of the naval gun follow-up system with gear backlash nonlinearity is established. Therein, a smooth approximate deadband inverse model is constructed to replace the actual discontinuous deadband inverse function, and combined with an RBF (Radial Basis Function) neural network to dynamically approximate the inverse error. On this basis, a nonlinear dynamic model of the naval gun system coupling multiple nonlinearities is established, and the effectiveness of the designed controller is verified through co-simulation comparisons with both a PID (Proportional–Integral–Derivative) controller and a backstepping controller. The results provide significant guidance on mitigating the impact of structural nonlinear factors in the follow-up system and enhancing the firing accuracy of naval guns.