Probability rate optimization of positive Markov jump linear systems via DC programming

We investigate the stabilization problem of positive Markov jump linear systems by optimizing their transition probability rates. By using the convex property of posynomials and the standard mathematical programming that deals with the difference in convex functions, we show that transition probability rate synthesis problems can be solved via difference-of-convex (DC) programming. A numerical example is used to illustrate the effectiveness of our results.