Design of Adaptive Network Based Fuzzy Inference PID Control Methodology For 3 Degree of Freedom Gimbal Stabilized Platform

3-Axis Gimbal framework that used to observe a stationary or moving point in space with the use of optical sensors such as Laser, IR, or camera mounted on the platform. The main goal is to track the trajectory of the target. Numerous control methodologies have been documented in order to improve the gimbal’s response to rate command inputs and enable it to continue following the rate input even in the presence of perturbations. For precise surveillance and three-axis gimbal stabilisation, an adaptive network based Fuzzy Inference PID control methodology is presented. Soft computing’s adaptive neuro-fuzzy inference system (ANFIS) is a useful tool for performance projection. For a 3- axis inertially stabilised platform system, a statistical analysis and soft computing technique based on the ANFIS neuro-fuzzy proportional-integral-differential (ANFP) control are presented to estimate the performance of a fuzzy PID controller. The proposed ANFIS-PID controller improves the gimbal system’s adaptation to disturbances and fluctuating missile angular rotations. ANFIS-PID controller improves both transient and steady state response. Results show 73.36% improvement in tracking performance w.r.t ISE, 67.24% improvement in control effort and 8.51% improvement in the rejection time of step disturbance in comparison with conventional PID control strategy.