An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...

Sometimes conventional feedback controllers may not perform well online because of the variation in process dynamics due to nonlinear actuators, changes in environmental conditions and variation in the character of the disturbances. To overcome the above problem, this paper deals with the designing of a controller for a second order system with Model Reference Adaptive Control (MRAC) scheme usi...

By using the concept of on-line goal adaptation, we develop a new paradigm of performance shaping in MRAC. The general idea is to replace the single reference model generated trajectory in classical adaptive designwith a tube referencemodel. Two alternative adaptive control schemes that lead to tractable design formulations are developed in which the performance is adapted on-line to satisfy a ...