ThisAutomated Manual Transmission (AMT) chapter shows how the standard control methods enable to design robust controller for the automotive AMTAutomated Manual Transmission (AMT). The control problem in AMT control is to provide smooth and oscillation-free speed transitions while meeting the transparency constraint. The latter constraint expresses the need to respect the driver’s request in despite of the high degree of uncertainties. These uncertainties are due to the unknown road characteristics and despite a total ignorance of all the mechanical parameters involved non withstanding the settings of the other controllers which manage the motor torque and clutch position behavior. Although the final step of the solution involves the use of parameterized Model Predictive Control (MPC)Model Predictive Control (which is not detailed in the chapter), the main reason of the success comes from the simplified modeling-related choices and the use of state estimator in order to cope with the many unknown sources of uncertainties on the equations governing the main quantities to be controlled. This use-case is an example of the efficiency of standard control, learning-free, methodologies in handling the presence of high level of uncertainties. It can be conjectured that no data-driven solutions can provide comparable efficiency in addressing this challenging control problem. This is precisely why this use-case is included.