Electrical and Electronic Engineering - Research Publications
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ItemTwo extensions of topological feedback entropy(SPRINGER LONDON LTD, 2013-12)
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ItemConvergence Analysis of Quantized Primal-dual Algorithm in Quadratic Network Utility Maximization Problems(IEEE, 2015)This paper examines the effect of quantized communications on the convergence behavior of the primal-dual algorithm in quadratic network utility maximization problems with linear equality constraints. In our set-up, it is assumed that the primal variables are updated by individual agents, whereas the dual variables are updated by a central entity, called system, which has access to the parameters quantifying the system-wide constraints. The notion of differential entropy power is used to establish a universal lower bound on the rate of exponential mean square convergence of the primal-dual algorithm under quantized message passing between agents and the system. The lower bound is controlled by the average aggregate data rate under the quantization, the curvature of the utility functions of agents, the number of agents and the number of constraints. An adaptive quantization scheme is proposed under which the primal-dual algorithm converges to the optimal solution despite quantized communications between agents and the system. Finally, the rate of exponential convergence of the primal-dual algorithm under the proposed quantization scheme is numerically studied.
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ItemLower Bounds on the Best-Case Complexity of Solving a Class of Non-cooperative Games(Elsevier, 2016)This paper studies the complexity of solving the class G of all N-player non-cooperative games with continuous action spaces that admit at least one Nash equilibrium (NE). We consider a distributed Nash seeking setting where agents communicate with a set of system nodes (SNs), over noisy communication channels, to obtain the required information for updating their actions. The complexity of solving games in the class G is defined as the minimum number of iterations required to find a NE of any game in G with ε accuracy. Using information-theoretic inequalities, we derive a lower bound on the complexity of solving the game class G that depends on the Kolmogorov 2ε-capacity of the constraint set and the total capacity of the communication channels. We also derive a lower bound on the complexity of solving games in G which depends on the volume and surface area of the constraint set.
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ItemPerformance Analysis of Gradient-Based Nash Seeking Algorithms Under Quantization(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2016-12-01)This paper investigates the impact of quantized inter-agent communications on the asymptotic and transient behavior of gradient-based Nash-seeking algorithms in non-cooperative games. Using the information-theoretic notion of entropy power, we establish a universal lower bound on the asymptotic rate of exponential mean-square convergence to the Nash equilibrium (NE). This bound depends on the inter-agent data rate and the local behavior of the agents' utility functions, and is independent of the quantizer structure. Next, we study transient performance and derive an upper bound on the average time required to settle inside a specified ball around the NE, under uniform quantization. Furthermore, we establish an upper bound on the probability that agents' actions lie outside this ball, and show that this bound decays double-exponentially with time. Finally, we propose an adaptive quantization scheme that allows the gradient algorithm to converge to the NE despite quantized inter-agent communications.
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ItemQuantized Control and Data Rate Constraints †(Springer London, 2013)
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ItemOPTIMAL INFINITE HORIZON CONTROL UNDER A LOW DATA RATE 2(Elsevier BV, 2006)
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ItemA DATA-RATE LIMITED VIEW OF ADAPTIVE CONTROL(Elsevier BV, 2006)
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ItemFinite horizon LQ optimal control and computation with data rate constraints(IEEE - Institute of Electrical and Electronic Engineers, 2005)
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ItemFeedback control under data rate constraints: An overview(INSTITUTE OF ELECTRICAL ELECTRONICS ENGINEERS (IEEE), 2007)The emerging area of control with limited data rates incorporates ideas from both control and information theory. The data rate constraint introduces quantization into the feedback loop and gives the interconnected system a two-fold nature, continuous and symbolic. In this paper, we review the results available in the literature on data-rate-limited control. For linear systems, we show how fundamental tradeoffs between the data rate and control goals, such as stability, mean entry times, and asymptotic state norms, emerge naturally. While many classical tools from both control and information theory can still be used in this context, it turns out that the deepest results necessitate a novel, integrated view of both disciplines.
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ItemSystems engineering for irrigation systems: Successes and challenges(Elsevier, 2005)In Australia, gravity fed irrigation systems are critical infrastructure essential to agricultural production and export. By supplementing these large scale civil engineering systems with an appropriate information infrastructure, sensors, actuators and a communication network it is feasible to use systems engineering ideas to improve the exploitation of the irrigation system. This paper reports how classical ideas from system identification and control can be used to automate irrigation systems to deliver a near on-demand water supply with vastly improved overall distribution efficiency.