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

Aishwary Joshi; Shana Moothedath; Prasanna Chaporkar

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arXiv · 1712.08404

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

Aishwary Joshi·Shana Moothedath·Prasanna Chaporkar

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Abstract

In this paper, we study 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 an optimal 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. We first prove the NP-hardness of the problem using a reduction from a well known NP-hard problem, the weighted set cover problem. In addition, we also prove that the optimal feedback selection problem for dedicated i/o is 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 optimal feedback selection problem for dedicated i/o. The proposed algorithm consists of a potential function incorporated with a greedy scheme and attains a solution with a guaranteed approximation ratio. Then 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 (log n)-approximate solution, where n denotes the system dimension. For hierarchical networks, we give a dynamic programming based algorithm to obtain an optimal solution in polynomial time.

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BibTeX RIS

Aishwary Joshi, Shana Moothedath, Prasanna Chaporkar. 2017-12-22. Minimum Cost Feedback Selection in Structured Systems: Hardness and Approximation Algorithm. https://arxiv.org/abs/1712.08404

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