A self-learning fuzzy logic system is given for control of unknown multiple-input-multiple-output (MIMO) plants. Some nomenclature and several data types are introduced to develop a general formulation for controller activity. A random optimization algorithm is given to train the controller. A plant model is not required for training. Instead, training is guided by observations of plant responses to inputs.