An autopilot design is proposed to control an agile tail-controlled missile system. Traditional autopilot design for the guided missile employs acceleration and rate feedback together with proportional and integral control to stabilize the missile and to track the guidance command signals. However, the gain scheduling method is time-consuming job and it doesn``t assure the performance between two linearization points.
Feedback linearization using nonlinear transformation techniques dynamically linearizes nonlinear systems into linear ones. A plant inversion method, one of the feedback linearization techniques, cannot directly adapt to the non-minimum phase system because of the plant inversion characteristics. To avoid the difficulties associated with the non-minimum phase dynamics of missile acceleration, the plant inversion is applied via output redefinition. Output redefinition method is used to transform the non-minimum phase system to the minimum phase system. Output redefinition method gives us an indirect or direct way to obtain the adequate results.
Nonlinear control require an accurate system and aerodynamic model. And at high angle-of-attack region, the large moment and force are generated because of the asymmetric vortex around the nose of missile system. PID error feedback control, on-line neural network and sliding mode control are used to eliminate the approximation error of the models and to stabilize the attitude of missile. The performances of the proposed autopilots are compared and analyzed through numerical simulations.