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This paper investigates the boost phase’s longitudinal autopilot of a ballistic missile equipped with thrust vector control. The existing longitudinal autopilot employs time-invariant passive resistor-inductor-capacitor (RLC) network compensator as a control strategy, which does not take into account the time-varying missile dynamics. This may cause the closed-loop system instability in the presence of large disturbance and dynamics uncertainty. Therefore, the existing controller should be redesigned to achieve more stable vehicle response. In this paper, based on gain-scheduling adaptive control strategy, two different types of optimal controllers are proposed. The first controller is gain-scheduled optimal tuning-proportional-integral-derivative (PID) with actuator constraints, which supplies better response but requires a priori knowledge of the system dynamics. Moreover, the controller has oscillatory response in the presence of dynamic uncertainty. Taking this into account, gain-scheduled optimal linear quadratic (LQ) in conjunction with optimal tuning-compensator offers the greatest scope for controller improvement in the presence of dynamic uncertainty and large disturbance. The latter controller is tested through various scenarios for the validated nonlinear dynamic flight model of the real ballistic missile system with autopilot exposed to external disturbances.
This paper investigates the boost phase’s longitudinal autopilot of a ballistic missile equipped with thrust vector control. The existing longitudinal autopilot employs time-invariant passive resistor-inductor-capacitor (RLC) network compensator as a control strategy, which does not take into account the time This may cause the closed-loop system instability in the presence of large disturbance and dynamics uncertainty. Thus, the existing controller should be redesigned to achieve more stable vehicle response. In this paper, based on gain-scheduling adaptive control strategy, two different types of optimal controllers are proposed. The first controller is gain-scheduled optimal tuning-proportional-integral-derivative (PID) with actuator constraints, which supplies better response but requires a priori knowledge of the system dynamics. controller has oscillatory response in the presence of dynamic uncertainty. Taking this into account, gain-s cheduled optimal linear quadratic (LQ) in conjunction with optimal tuning-compensator offers the greatest scope for controller improvement in the presence of dynamic uncertainty and large disturbance. The latter controller is tested through the various scenarios for the validated nonlinear dynamic flight model of the real ballistic missile system with autopilot exposed to external disturbances.