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Distributed consensus-based multi-agent convex optimization via gradient tracking technique

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2019年第6期356卷 3733-3761页

作者： Li, Huaqing Zhang, Hao Wang, Zheng Zhu, Yifan Han, Qi Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Chongqing Univ Sci & Technol Coll Elect & Informat Engn Chongqing 401331 Peoples R China

This paper considers solving a class of optimization problems over a network of agents, in which the cost function is expressed as the sum of individual objectives of the agents. The underlying communication graph is assumed to be undirected and connected. A distributed algorithm in which agents employ time-varying and heterogeneous step-sizes is proposed by combining consensus of multi-agent systems with gradient tracking technique. The algorithm not only drives the agents' iterates to a global and consensual minimizer but also finds the optimal value of the cost function. When the individual objectives are convex and smooth, we prove that the algorithm converges at a rate of O(1/root t) if the homogeneous step-size does not exceed some upper bound, and it accelerates to O(1/t) if the homogeneous step-size is sufficiently small. When at least one of the individual objectives is strongly convex and all are smooth, we prove that the algorithm converges at a linear rate of O(lambda(t)) with 0 < lambda < 1 even though the step-sizes are time-varying and heterogeneous. Two numerical examples are provided to demonstrate the efficiency of the proposed algorithm and to validate the theoretical findings. (C) 2019 Published by Elsevier Ltd on behalf of The Franklin Institute.

关键词： Cost functions

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Kernel Least Mean Square Based on the Sparse Nystrom Method 52

Kernel Least Mean Square Based on the Sparse Nystrom Method

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IEEE International Symposium on circuits and Systems (ISCAS)

作者： Zhang, Haonan Jiang, Han Wang, Shiyuan Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China

ISBN: (纸本)9781728133201

Kernel least mean square based on the Nystrom method (NysKLMS) has been proposed to fix the network structure of kernel least mean square (KLMS) by approximating a large Gram matrix with a low-rank matrix generated by sampling from input vectors. However, the computational burden of NysKLMS increases with the growth of the input dimension. To alleviate this computational burden, a novel KLMS based on a sparse Nystrom method (SNKLMS) algorithm is proposed in this paper. Unlike NysKLMS using the k-means sampling to obtain k centroids from input data, the proposed SNKLMS algorithm first divides input data into several clusters, and then selects k centroids from the obtained clusters equally. According to the relation between the Gaussian kernel and the distance of different clusters, partial submatrices in the low-rank matrix of SNKLMS can be omitted to further reduce the operations of multiplication and addition, and thus a sparse low-rank matrix is obtained. Simulations on the channel equalization and chaotic time-series prediction validate the superiorities of SNKLMS.

关键词： Nystrom method sparsification k-means kernel least mean square Gaussian kernel submatrices

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A Distributed Strategy Based on ADMM for Dynamic Economic Dispatch Problems Considering Environmental Cost Function with Exponential term 43

A Distributed Strategy Based on ADMM for Dynamic Economic Di...

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43rd Annual Conference of the IEEE-Industrial-Electronics-Society (IECON)

作者： Zhao, You He, Xing Chen, Ling Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China

ISBN: (纸本)9781538611272

In this paper, a dynamic economic dispatch problem (DEDP) which considers the benefit function, environmental cost function and fuel cost function is studied by the distributed strategy. We propose a distributed algorithm based on undirected graphs and alternating direction method of multipliers (ADMM). Firstly, the DEDP is decomposed into three minimization steps to solve according to ADMM. Secondly, in the first minimization iterative step, with the E exponential term introduced into the environmental cost function and coupling constraint of all generators, we proposed a distributed consensus algorithm with Lambert W function to acquire the values of first minimization iterative step;in the second minimization iterative step, we use ADMM based on parallel projection and distributed consensus strategy to gain the values of it. Based on the above designed, our algorithm is distributed, i.e., all the generators only communicate with their neighbors. Simulation results tested on IEEE14-bus system show that the proposed algorithm is capable of converging to the optimal solution of DEDP.

关键词： Dynamic Economic dispatch Distributed Consensus algorithm Lambert W function Smart grid

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Accelerated Convergence Algorithm for Distributed Constrained Optimization under Time-Varying General Directed Graphs

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2020年第7期50卷 2612-2622页

作者： Li, Huaqing Lu, Qingguo Liao, Xiaofeng Huang, Tingwen Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Texas A&M Univ Qatar Sci Program Doha Qatar

This paper studies a class of distributed convex optimization problems by a set of agents in which each agent only has access to its own local convex objective function and the estimate of each agent is restricted to both coupling linear constraint and individual box constraints. Our focus is to devise a distributed primal-dual gradient algorithm for working out the problem over a sequence of time-varying general directed graphs. The communications among agents are assumed to be uniformly strongly connected. A column-stochastic mixing matrix and a fixed step-size are applied in the algorithm which exactly steers all the agents to asymptotically converge to a global optimal solution. Based on the standard strong convexity and the smoothness assumptions of the objective functions, we show that the distributed algorithm is capable of driving the whole network to geometrically converge to an optimal solution of the convex optimization problem only if the step-size does not exceed some upper bound. We also give an explicit analysis for the convergence rate of the proposed optimization algorithm. Simulations on economic dispatch problems and demand response problems in power systems are performed to illustrate the effectiveness of the proposed optimization algorithm.

关键词： Optimization Convergence Linear programming Convex functions Multi-agent systems Generators Couplings Distributed convex optimization geometric convergence multiagent systems primal-dual algorithm time-varying directed graphs

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Synchronous Slow and Fast Light Based on Plasmon-Induced Transparency and Absorption in Dual Hexagonal Ring Resonators

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IEEE TRANSACTIONS ON NANOTECHNOLOGY 2018年第3期17卷 552-558页

作者： Xie, Yiyuan Ye, Yichen Liu, Yuzhu Wang, Shujian Zhang, Jingping Liu, Yong Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Natl Joint Engn Lab Intelligent Transmiss & Contr Chongqing 400715 Peoples R China Univ Elect Sci & Technol Chengdu Sch Optoelect Informat Chengdu 611731 Sichuan Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China

Slow and fast light effects have many potential applications. In this paper, slow and fast light were obtained synchronously based on plasmon-induced transparency (PIT) and plasmon-induced absorption (PIA). The proposed structure consisted of dual hexagonal ring resonators coupled with two parallel metal-insulator-metal waveguides. The theoretical model established using temporal coupled-mode theory showed that the core-core separation and resonance wavelength detuning between two hexagonal rings were the key factors to PIT and PIA. The finite-difference time-domain simulation results revealed that the structural parameters have an important influence on the transmission characteristics and group indices. Moreover, there was a feasible way for adjusting the slow and fast light effects without changing the geometric dimensions. This proposed structure can provide a way toward controlling the velocity of light in highly integrated devices.

关键词： Fast light hexagonal ring resonator plasmon-induced absorption plasmon-induced transparency slow light

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Pattern Formation in a Reaction-Diffusion BAM Neural Network With Time Delay: (k1, k2) Mode Hopf-Zero Bifurcation Case

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2022年第12期33卷 7266-7276页

作者： Dong, Tao Xiang, Weilai Huang, Tingwen Li, Huaqing Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Texas A&M Univ Qatar Dept Math Doha Qatar

This article investigates the joint effects of connection weight and time delay on pattern formation for a delayed reaction-diffusion BAM neural network (RDBAMNN) with Neumann boundary conditions by using the (k(1), k(2)) mode Hopf-zero bifurcation. First, the conditions for k(1) mode zero bifurcation are obtained by choosing connection weight as the bifurcation parameter. It is found that the connection weight has a great impact on the properties of steady state. With connection weight increasing, the homogeneous steady state becomes inhomogeneous, which means that the connection weight can affect the spatial stability of steady state. Then, the specified conditions for the k(2) mode Hopf bifurcation and the (k(1), k(2)) mode Hopf-zero bifurcation are established. By using the center manifold, the third-order normal form of the Hopf-zero bifurcation is obtained. Through the analysis of the normal form, the bifurcation diagrams on two parameters' planes (connection weight and time delay) are obtained, which contains six areas. Some interesting spatial patterns are found in these areas: a homogeneous periodic solution, a homogeneous steady state, two inhomogeneous steady state, and two inhomogeneous periodic solutions.

关键词： Center manifold Hopf-Zero bifurcation reaction-diffusion BAM neural network (RDBAMNN) spatial patterns

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A Novel Multi-Functional Plasmonic Logic Device by Angle Manipulation

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IEEE TRANSACTIONS ON NANOTECHNOLOGY 2020年 19卷 94-101页

作者： Ye, Yichen Wang, Yun Xie, Yiyuan Song, Tingting Liu, Bocheng Chai, Junxiong Liu, Yong Southwest Univ Sch Elect & Informat Engn Chongqing 400715 Peoples R China Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Natl Joint Engn Lab Intelligent Transmiss & Contr Coll Elect & Informat Engn Chongqing 400715 Peoples R China Univ Elect Sci & Technol Chengdu Sch Optoelect Informat Chengdu 611731 Sichuan Peoples R China

Optical logic devices are indispensable for optical computing and data processing. In order to acquire high performance optical logic device, a novel plasmonic structure based on plasmon-induced transparency (PIT) effect is proposed. It can implement multiple logic functions simultaneously with high output contrast ratios between "0" and "1" states through a new manipulation method of angle rotation. The optical logic device consists of dual identical hexagonal resonators with rotatable ellipses embedded in resonators and two parallel metal-insulator-metal (MIM) waveguides. The specific rotation angles of ellipses are defined as the input logic states. In addition, according to the transmissions at output ports, the thresholds are set to distinguish the output logic states. Ultimately, four kinds of logic functions: AND, NAND, NOR and NOT can be implemented with fairly high output contrast ratios in this compact device. Most importantly, among these logic functions, AND, NAND, and NOR can be operated simultaneously with wavelength division multiplexing (WDM) technique. Therefore, this work supplies a potential application for optical logic integrated circuits.

关键词： Optical logic devices plasmon-induced transparency (PIT) rotatable ellipse surface plasmon polaritons

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A study of variation in dynamical behavior of fractional complex Ginzburg-Landau model for different fractional operators

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PATTERN RECOGNITION LETTERS 2023年 170卷 106-112页

作者： Zhang, Tianguang Zhang, Wei Zhang, Zheng Gan, Yan Southwest Univ Dept Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China Open Univ Henan Zhengzhou 450046 Henan Peoples R China Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China

Recently, the Transformers have shown great potential in computer vision tasks, such as classification detection, segmentation , image synthesis, etc. The success of Transformers has been long attributed to the attention-based token mixer. However, the computational complexity of the attention-based token mixer module is quadratic to the number of tokens to be mixed. Therefore, the attention-based token mixer module requires more parameters , will cause a very large amount of computation. As far as image synthesis task is concerned, the attention-based token mixer module increases the computation amount of generative adversarial networks (GANs) based on Transformers. To address this problem, we propose the PFGAN method. The motivation is based on our observation that the computational com-plexity of pooling is linear to the sequence length, without any other learnable parameters. Based on this observation, we use pooling rather than self-attention as the token mixer. Experimental results on CelebA, CIFAR-10 and LSUN datasets demonstrate that our proposed method has fewer parameters and fewer computational complexity. (c) 2023 Elsevier B.V. All rights reserved.

关键词： Transformers Generative adversarial networks Token mixer Pooling

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Event-Triggered Adaptive Fault-Tolerant Control for a Class of nonlinear Multiagent Systems With Sensor and Actuator Faults

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IEEE TRANSACTIONS ON circuits AND SYSTEMS I-REGULAR PAPERS 2022年第10期69卷 4203-4214页

作者： Wang, Xin Zhou, Yuhao Huang, Tingwen Chakrabarti, Prasun Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Guangdong Prov Key Lab Intelligent Decis & Cooper Guangzhou 510006 Peoples R China Texas A&M Univ Qatar Doha Qatar ITM SLS Baroda Univ Vadodara 391510 Gujarat India

This paper investigates the leader-following consensus control problem for a class of nonlinear multiagent systems subject to sensor and actuator faults under a fixed directed graph. First, a fault compensation mechanism is proposed because of multiple faults wherein the adaptive parameters substitute the fault coefficients. Then, the command filtering method is employed to avoid the burst of complexity rendered by the duplicative differentiation of the virtual control signal. Furthermore, the neural networks-based state observers are designed to reconstruct the unmeasurable states of the nonlinear multiagent systems. According to the given design approach, a switching threshold-based event-triggered adaptive fault-tolerant control strategy is developed and ensures all the signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB). Finally, the simulation result is provided to demonstrate the validity of the presented method.

关键词： Circuit faults Actuators Adaptive systems Fault tolerant systems Fault tolerance Multi-agent systems Consensus control Event-triggered leader-following consensus sensor and actuator faults

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A Fixed-Time Projection Neural Network for Solving L₁-Minimization Problem

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2022年第12期33卷 7818-7828页

作者： He, Xing Wen, Hongsong Huang, Tingwen Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Texas A&M Univ Qatar Dept Math Doha Qatar

In this article, a new projection neural network (PNN) for solving L-1-minimization problem is proposed, which is based on classic PNN and sliding mode control technique. Furthermore, the proposed network can be used to make sparse signal reconstruction and image reconstruction. First, a sign function is introduced into the PNN model to design fixed-time PNN (FPNN). Then, under the condition that the projection matrix satisfies the restricted isometry property (RIP), the stability and fixed-time convergence of the proposed FPNN are proved by the Lyapunov method. Finally, based on the experimental results of signal simulation and image reconstruction, the proposed FPNN shows the effectiveness and superiority compared with that of the existing PNNs.

关键词： Fixed-time convergence fixed-time projection neural network (FPNN) l(1)-minimization sliding mode control technique sparse signal reconstruction

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