Online adjustment method for control parameters of autonomous aircraft based on MCMC optimized Q learning

The invention discloses an online adjustment method for the control parameters of an autonomous aircraft based on MCMC optimized Q learning, which includes the following steps: first, doing statisticsof possible changes of the PID control parameters of an aircraft according to the actual situation to get an action set of parameter adjustment, and initializing the PID control parameters accordingto the aircraft control experience; then, randomly selecting an action to act on the autonomous aircraft, carrying out sampling through an MCMC algorithm according to the function value Q* of each action obtained in a Q learning algorithm to get an action to be taken next moment, and adjusting the learning factor l in the Q learning algorithm through an SPSA step size adjustment algorithm with thepassage of time; and finally, getting the optimal control parameters in the current environment through repeated adjustment of the control parameters. The problems of overshoot and delay in the navigation process of an autonom