Markov data-based LQG control

In this paper the Markov data-based LQG control problem is considered. The Markov data-based quadratic cost function over some finite interval [0, N]. To solve this problem, we show LQG control problem is to find the optimal control sequence which minimizes that a complete input-output description o f the system is not necessary. Obviously a complete state space model is no t necessary! for this problem either. The main contributions of this paper include: (i) develop a new data-based LQG controller in a recursive form an d a batch-form, (ii) derive a closed form expression for the system's optim al performance in terms of the Markov parameters, (iii) develop an algorith m for choosing the output weighting matrix, and (iv) demonstrate that the a mount of information about the system required by the data-based controller design is less than the amount required to construct the full state space model. A numerical example is given to show the effectiveness of the darn-b ased design method.