Distributed proximal-gradient method for convex optimization with inequality constraints
- Authors: Li, Jueyou , Wu, Changzhi , Wu, Zhiyou , Long, Qiang , Wang, Xiangyu
- Date: 2014
- Type: Text , Journal article
- Relation: ANZIAM Journal Vol. 56, no. 2 (2014), p. 160-178
- Full Text: false
- Reviewed:
- Description: We consider a distributed optimization problem over a multi-agent network, in which the sum of several local convex objective functions is minimized subject to global convex inequality constraints. We first transform the constrained optimization problem to an unconstrained one, using the exact penalty function method. Our transformed problem has a smaller number of variables and a simpler structure than the existing distributed primal-dual subgradient methods for constrained distributed optimization problems. Using the special structure of this problem, we then propose a distributed proximal-gradient algorithm over a time-changing connectivity network, and establish a convergence rate depending on the number of iterations, the network topology and the number of agents. Although the transformed problem is nonsmooth by nature, our method can still achieve a convergence rate, O (1/k), after k iterations, which is faster than the rate, O (1/k), of existing distributed subgradient-based methods. Simulation experiments on a distributed state estimation problem illustrate the excellent performance of our proposed method. Copyright © 2014 Australian Mathematical Society.
A direct optimization method for low group delay FIR filter design
- Authors: Wu, Changzhi , Gao, David , Lay Teo, Kok
- Date: 2013
- Type: Text , Journal article
- Relation: Signal Processing Vol. 93, no. 7 (2013), p. 1764-1772
- Full Text: false
- Reviewed:
- Description: This paper studies the design of FIR filter with low group delay, where the desired phase response is not being approximated. It is formulated as a constrained optimization problem, which is then solved globally. Numerical experiments show that our design method can produce a filter with smaller group delay than that obtained by the existing convex optimization method used in conjunction with a minimum phase spectral factorization method under the same design criteria. Furthermore, our formulation offers us the flexibility for the trade-off between the group delay and the magnitude response directly. It also allows the feasibility of imposing constraints on the group delay. © 2013 Elsevier B.V.
- Description: 2003011019
Min-max optimal control of linear systems with uncertainty and terminal state constraints
- Authors: Wu, Changzhi , Lay Teo, Kok , Wu, Soonyi
- Date: 2013
- Type: Text , Journal article
- Relation: Automatica Vol. 49, no. 6 (2013), p. 1809-1815
- Full Text: false
- Reviewed:
- Description: In this paper, a class of min-max optimal control problems with continuous dynamical systems and quadratic terminal constraints is studied. The main contribution is that the original terminal state constraint in which the disturbance is involved is transformed into an equivalent linear matrix inequality without disturbance under certain conditions. Then, the original min-max optimal control problem is solved via solving a sequence of semi-definite programming problems. An example is presented to illustrate the proposed method. © 2013 Elsevier Ltd. All rights reserved.
- Description: 2003011022