Choon Yik Tang

University of Oklahoma

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Jie Lu

University of Michigan–Ann Arbor

John N. Jiang

University of Oklahoma

R. Ramakumar

Tata Institute of Social Sciences

Semyon M. Meerkov

University of Michigan–Ann Arbor

Pierre T. Kabamba

University of Michigan–Ann Arbor

Yi Guo

National Center of Ocean Standards and Metrology

Junke Wang

University of Oklahoma

E.A. Misawa

Oklahoma State University Oklahoma City

Seyed Hossein Hosseini

Yazd University

Mu Yang

University of Science and Technology of China

Cooperative Institutions

University of Oklahoma

University of Michigan–Ann Arbor

University of Science and Technology of China

University of Illinois Urbana-Champaign

Chinese Academy of Sciences

Georgia Institute of Technology

Southeast University

Beijing Jiaotong University

Stony Brook University

Massachusetts Institute of Technology

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Feedforward control of data rate in wireless networks

IEEE Transactions on Vehicular Technology (2002)

Pierre T. Kabamba Semyon M. Meerkov W.E. Stark Choon Yik Tang

This paper develops a feedforward approach to data-rate control in wireless networks. The development is based on designing an optimal but noncausal controller and its subsequent modification, which leads to a causal implementable suboptimal controller driven by an estimate of the bit-error probability. It is shown that this controller results in a minimum of 5%-85% increase in average throughput without additional power utilization, as compared with fixed data rate operation.

Feed forward

10.1109/tvt.2002.800622

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Citations (7)

Model Predictive and Adaptive Control of Wind Farm Active Power Output

Advances in industrial control (2016)

John N. Jiang Choon Yik Tang R. Ramakumar

Model Predictive Control

10.1007/978-3-319-39135-9_4

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An Algorithm for Jointly Optimizing Quantization and Multiple Constant Multiplication

ACM Transactions on Design Automation of Electronic Systems (2012)

Matthew B. Gately Mark Yeary Choon Yik Tang

This article presents a joint framework for quantization and Multiple Constant Multiplication (MCM) optimization, which yields a computationally efficient implementation of multiplierless multiplication in hardware and software. Frameworks of this nature have been developed in the context of Finite Impulse Response (FIR) filters, where frequency response specifications are used to drive the design. In this work, we look at a general case, considering as given a vector of ideal, real constants, which may come from any application and do not necessarily represent FIR filter coefficients. We first formulate a joint optimization problem for finding a fixed-point vector and a shift-add network that are optimal in terms of quantization error and MCM complexity. We then describe ways to finitize and prune the search space, leading to an efficient algorithm called JOINT_SOLVE that solves the problem. Finally, via extensive randomized experiments, we show that our joint framework is notably more computationally efficient than a disjointed one, reducing the MCM cost by 15%--60% on moderate size problems.

Finite impulse response

10.1145/2348839.2348846

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Introduction

Advances in industrial control (2016)

John N. Jiang Choon Yik Tang R. Ramakumar

Scope (computer science)

10.1007/978-3-319-39135-9_1

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An Approximate Wind Turbine Control System Model for Wind Farm Power Control

IEEE Transactions on Sustainable Energy (2012)

Yi Guo Seyed Hossein Hosseini Choon Yik Tang John N. Jiang R. Ramakumar

Wind farm power control is key to reliable large-scale wind integration. The design of a sophisticated wind farm controller, however, is challenging partly because there is a lack of models that appropriately simplify the complex overall dynamics of a large number of wind turbine control systems (WTCSs). In this paper, using system identification approaches, we develop a simple approximate model that attempts to mimic the active and reactive power dynamics of two generic WTCS models under normal operating conditions: an analytical model described by nonlinear differential equations, and an empirical one by input-output measurement data. The approximate model contains two parts-one for active power and one for reactive-each of which is a third-order system that would have been linear if not for a static nonlinearity. For each generic model, we also provide an identification scheme that sequentially determines the approximate model parameters. Finally, we show via simulation that, despite its structural simplicity, the approximate model is accurate and versatile, capable of closely imitating several different analytical and empirical WTCS models from the literature and from real data. The results suggest that the approximate model may be used to facilitate research on wind farm power control.

Identification

10.1109/tste.2012.2217992

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Citations (32)

Distributed estimation of graph spectrum

2022 American Control Conference (ACC) (2015)

Mu Yang Choon Yik Tang

In this paper, we develop a two-stage distributed algorithm that enables nodes in a graph to cooperatively estimate the spectrum of a matrix W associated with the graph, which includes the adjacency and Laplacian matrices as special cases. In the first stage, the algorithm uses a discrete-time linear iteration and the Cayley-Hamilton theorem to convert the problem into one of solving a set of linear equations, where each equation is known to a node. In the second stage, if the nodes happen to know that W is cyclic, the algorithm uses a Lyapunov approach to asymptotically solve the equations with an exponential rate of convergence. If they do not know whether W is cyclic, the algorithm uses a random perturbation approach and a structural controllability result to approximately solve the equations with an error that can be made small. Finally, we provide simulation results that illustrate the algorithm.

Adjacency matrix

Linear equation

Adjacency list

10.1109/acc.2015.7171143

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Convergence rate of Controlled Hopwise Averaging on various graphs

Jie Lu Choon Yik Tang

This paper analyzes the convergence properties of Ideal Controlled Hopwise Averaging (ICHA) and Controlled Hopwise Averaging (CHA), two recently proposed asynchronous distributed averaging algorithms for wireless networks, which were shown via simulation to be more bandwidth/energy efficient than several existing schemes. We first derive deterministic upper bounds on the exponential convergence rate of ICHA on general graphs and specific ones (i.e., path, cycle, regular, strongly regular, and complete graphs), expressing the bounds explicitly in terms of the graph invariants. We then show that such bounds of ICHA are roughly 20% better than the average-case, stochastic convergence rate of Pairwise Averaging on path, cycle, and complete graphs. Finally, we obtain upper bounds on the convergence rate of CHA with respect to iteration and time, and show that iteration-wise CHA enjoys the same bounds as ICHA, closely mimicking its behavior while being practical.

Bounding overwatch

10.1109/cdc.2011.6160531

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Distributed Estimation of Graph Spectrum

arXiv (Cornell University) (2015)

Mu Yang Choon Yik Tang

In this paper, we develop a two-stage distributed algorithm that enables nodes in a graph to cooperatively estimate the spectrum of a matrix $W$ associated with the graph, which includes the adjacency and Laplacian matrices as special cases. In the first stage, the algorithm uses a discrete-time linear iteration and the Cayley-Hamilton theorem to convert the problem into one of solving a set of linear equations, where each equation is known to a node. In the second stage, if the nodes happen to know that $W$ is cyclic, the algorithm uses a Lyapunov approach to asymptotically solve the equations with an exponential rate of convergence. If they do not know whether $W$ is cyclic, the algorithm uses a random perturbation approach and a structural controllability result to approximately solve the equations with an error that can be made small. Finally, we provide simulation results that illustrate the algorithm.

Adjacency matrix

Linear equation

Adjacency list

10.48550/arxiv.1503.08192

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Distributed Asynchronous Algorithms for Solving Positive Definite Linear Equations over Networks—Part I: Agent Networks

IFAC Proceedings Volumes (2009)

Jie Lu Choon Yik Tang

10.3182/20090924-3-it-4005.00043

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Citations (20)