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This paper describes how the process of synthesizing the design of both the topology and the numerical parameter values (tuning) for a controller can be automated by using genetic programming. Genetic programming can be used to automatically make the decisions concerning the total number of signal processing blocks to be employed in a controller, the type of each block, the topological interconnections between the blocks, and the values of all parameters for all blocks requiring parameters. In synthesizing the design of controllers, genetic programming can simultaneously optimize prespecified performance metrics (such as minimizing the time required to bring the plant output to the desired value), satisfy time-domain constraints (such as overshoot and disturbance rejection), and satisfy frequency domain constraints. Evolutionary methods have the advantage of not being encumbered by preconceptions that limit its search to well-traveled paths. Genetic programming is applied to an illustrative problem involving the design of a controller for a three-lag plant with a significant (five-second) time delay in the external feedback from the plant to the controller. A delay in the feedback makes the design of an effective controller especially difficult.