Model reference adaptive control of a gantry crane scale model

A method of reference model decomposition, an extension of model reference adaptive control, is presented. The decomposition method can be regarded as a way of including knowledge about the structure and parameters of unmodeled dynamics in the adaptive system, making it possible to choose a lower order controller which is only equipped for the nominal process part. To illustrate the decomposition method, an adaptive controller for a scale model of a gantry crane is presented. Simplifying and linearizing the mathematical equations describing the crane yields a fourth-order model, of which the dynamics of the load swing take two. A standard adaptive control algorithm needs eight parameters, which in practice yields unacceptable behavior. The decomposition method allows the use of only two adjustable parameters, and real-time experiments showing practical results obtained with the method are described.<>