In this thesis, a new mode! reference adaptive controller, the Minimal Controller Synthesis ( MCS algorithm is esented. This algorithm 15 derived for the control of linear and nonlinear time varying single input-single output and multivariable systems having a phase canonical state space representation. Apart from the knowledge of the plant state dimension and the sign of some elements of the plant feedforward matrix, no other plant parameters need to be known for the derivation of the MCS algorithm. The robustness of the MCS algorithm is then investigated in the presence of varying plant parameters, nonlinearities and it is shown that slowly external disturbances and plant the MCS algorithm is robust in the If the plant is subject to rapidly varying then the boundedness of the .presence of such variations. external disturbances and plant parameters, to those of the MCS algorithm. Then, the MCS algorithm is analysed and an analytical expression of the minimum settling time of the error norm 15 explicitly derived as a function of different parameters of the plant-reference model system. When the reference inputs are persistently exciting, model reference adaptive identification of slowly varying linear systems. Moreover, by adding a suitable extra term to the MCS input, Finally, then the MCS algorithm can be used for constant input disturbances can then be estimated. the value of in order to reject the effect of bounded and rapidly varying plant parameters, external disturbances and plant nonlinearities, the Extended MCS algorithm ( EMCS ) is presented. The EMCS algorithm consists of adding a suitably designed extra element to the MCS input. It is then shown that the errors are globally asymptotically stable in the presence of such rapidly varying parameters. Throughout this thesis, many simulation and practical implementation examples are presented. The overall conclusion is that the excellence of results obtained and the simplicity of implementation of the MCS algorithm make the use of the later extremely attractive to practising control engineers.