Minimum Cost Feedback Selection in Structured Systems: Hardness and Approximation Algorithm

This article deals with output feedback selection in linear time-invariant structured systems. We assume that the inputs and the outputs are dedicated , i.e., each input directly actuates a single state and each output directly senses a single state. Given a structured system with dedicated inputs and outputs and a cost matrix that denotes the cost of each feedback connection, our aim is to select a minimum cost set of feedback connections such that the closed-loop system satisfies arbitrary pole-placement. This problem is referred to as the optimal feedback selection problem for dedicated i/o. The optimal feedback selection problem for dedicated i/o is NP-hard and inapproximable to a constant factor of log $ n$ , where $n$ denotes the system dimension. To this end, we propose an algorithm to find an approximate solution to the problem. The proposed algorithm consists of a potential function incorporated with a greedy scheme and attains a solution with a guaranteed approximation ratio. We consider two special network topologies of practical importance, referred to as back-edge feedback structure and hierarchical networks . For the first case, which is NP-hard and inapproximable to a multiplicative factor of log $ n$ , we provide a $\text{log} n$ -approximate solution. For hierarchical networks, we give a dynamic programming based algorithm to obtain an optimal solution in polynomial time.