Downloads & Free Reading Options - Results

We present the basic language measure algorithms with some preliminary definitions of terms used. Properties of the measure are presented accompanied by proofs. We then describe in detail the algorithm for generating an optimal controller with respect to the language measure, and then prove that the generation is indeed optimal. Next we describe our experimentation regarding extracting language measure parameters from real or simulated modeled scenarios. From this experiment we obtain a constructive method for getting these parameters that can be applied to other types of situations other than MICA situations, thereby validating the language measure as a viable method of measurement. Example controllers and plant models are then used to illustrate the robustness of the measure with respect to small perturbations of its input parameters, and how the optimal algorithm generates results that improve upon the non-optimal measurements.