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In their beginnings, control systems were developed out of a full knowledge of the mathematical model of the process to be controlled. Nowadays, however, the trend for advanced control systems points to the fact that they can be developed without a previous knowledge of the mathematical model of the system to be controlled, hence leading to advantages and drawbacks at the moment of their application (Craig, 2006). Amongst the most remarkable disadvantages we have the fact that the higher accuracy we ask the controller, the more response delay we have (Ogata, 1996). That is why, if we can get a good enough system description, control systems can be simplified, enhancing their accuracy as well as their speed (Pierro et al., 2008). Advanced control techniques allow us an accurate control from a system predictor model, as the case of adaptive control techniques by reference model, studied in this chapter. An adaptive control system is a controller capable of modifying system's adjustable parameters generating an acting signal, in order to keep optimum performance independently from environmental modifications. Adaptive control can be represented through the following block diagram:

Comparison of Identification Techniques for a 6-DOF Real Robot and Development of an Intelligent Controller