The speed of autonomous vehicles will have a significant influence on the safety and comfort of driving. When the autonomous vehicle passes through the consecutive speed control humps, how to automatically select the most appropriate speed has become a practical research subject. The paper chooses the genetic algorithm to build a multi-objective optimization model and then designs and carries out the solution process of the multi-objective optimization problem for the vehicle.

Eliminating the hysteresis effect is highly desired in harmonic drive, which results in challenges in the control design. In this paper, we construct a new compound optimal controller to improve the compensational effect of hysteresis torque. The new controller is proposed based on the optimal theory and the linearization of nonlinear system. Numerical simulation shows that this new controller can track the complex reference trajectory with a relative error less than 1%.

In this research the motion planning problem for systems that admit a polynomial description of the system dynamics through differential flatness is tackled by parameterizing the system's so-called flat output as a piecewise polynomial. Sufficient conditions on the spline coefficients are derived ensuring satisfaction of the operating constraints over the entire time horizon and an intuitive relaxation is proposed to tackle conservatism.