![]() ![]() What the robot should do, rather than designing how it should do it. This relieves some burden by letting the designer reason at the level of OptimalĬontrol allows a control designer to specify the dynamic model and theĭesired outcomes, and the algorithm will compute an optimized control. A driving styleĬan be composed of some balanced combination of these goals. Like to reach a desired location while achieving several other goals:Į.g., avoiding obstacles, not driving erratically, maintaining aĬomfortable level of accelerations for human passengers. Optimal control asks to compute a control function (either open loop orĬlosed loop) that optimizes some performance metric regarding theĬontrol and the predicted state. Shortcomings in a highly general framework. ![]() However, our previous predictive methods were largely Systems like robots, predictive control allows the controller to makeīetter decisions at the current time to account for future Or operational space control, as well as some predictive controllers In previous chapters we have seen the use of myopic controllers like PID ![]()
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