We consider a mean field game among a large population of noncooperative agents divided into two categories: leaders and followers. Each agent is subject to heterogeneous convex constraints and minimizes a quadratic c...
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ISBN:
(纸本)9781467386838
We consider a mean field game among a large population of noncooperative agents divided into two categories: leaders and followers. Each agent is subject to heterogeneous convex constraints and minimizes a quadratic cost function;the cost of each leader is affected by the leaders' aggregate strategy, while the cost of each follower is affected by both the leaders' and followers' aggregate strategy. We propose a decentralized scheme in which the agents update their strategies optimally with respect to a global incentive signal, possibly different for leaders and followers, broadcast by a central coordinator. We propose several incentive update rules that, under different conditions on the problem data, are guaranteed to steer the population to an ε-Nash equilibrium, with ε decreasing linearly to zero as the number of players increases. We illustrate our theoretical results on a demand-response program between electricity consumers and producers in the day-ahead market.
Many problems of interest in systems and control can be formulated in the framework of convex optimization by using convex relaxation techniques. A well-known example is the use of the l1-norm as a substitute for the ...
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Many problems of interest in systems and control can be formulated in the framework of convex optimization by using convex relaxation techniques. A well-known example is the use of the l1-norm as a substitute for the so-called l0-norm in order to enhance sparseness in a parameter vector. Another important example is to use the nuclear norm as a convex relaxation in rank-constrained optimization problems. We will discuss how to apply such convex relaxation techniques to three important problems in control and system *** first problem is how to use the l1 norm, with extensions, to handle piecewise constant or linear constraints. This technique is used in mean and trend filtering for change point detection, but also in model predictive control with extensions. We will apply this approach to smooth driving model predictive control of self-driving heavy *** second problem is how to use nuclear norm regularization to handle a Hankel matrix rank constraint. Since the rank of the impulse response Hankel matrix equals the order of the underlying dynamical system, we can use nuclear norm regularization to prefer low order models. We will discuss how to use this approach to obtain a convex system identification method by minimizing a quadratic cost subject to a nuclear norm Hankel matrix constraint. Here the trade-off between the fit and the constraint is governed by a regularization parameter. A main contribution is an algorithm to determine the so-called approximate regularization path for such nuclear norm problem, that is the optimal solution up to a given error tolerance as a function of the regularization *** third problem is about experiment design for system identification, where the model will be used for control. This framework is related to optimal input design and is referred to as application-oriented input design. The idea is to find the "cheapest" identification experiment while fulfilling performance specifications on the applica
Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve the...
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This paper presents a novel analytical method for electro-mechanical design of a high speed long-term flywheel energy storage system and thermal evaluation of possible operating modes of the system. Flywheel's com...
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This paper presents a novel analytical method for electro-mechanical design of a high speed long-term flywheel energy storage system and thermal evaluation of possible operating modes of the system. Flywheel's composite shell rotor along with the motor/generator unit are assumed to be placed into a sealed vacuum chamber, which presents a challenge of heat transfer, produced by rotor losses. Developed method takes into account thermal radiation properties of the rotor and is realised using Mathcad software, which allows for quick investigation of any flywheel configuration. The method involves calculations for preliminary rotor sizing and determining achievable operation modes, while keeping the rotor under a specified temperature limit. Results of using this method for studying dependencies of thermal performance on initial system parameters are presented and conclusions are drawn. Based on the conducted study, recommendations on system design considerations are given.
This paper is concerned with the problem of distributed Kalman filtering in a network of interconnected subsystems with distributed control protocols. We consider networks, which can be either homogeneous or heterogen...
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In this paper, we propose novel relay selection policies that aim at reducing the average delay by incorporating the buffer size of the relay nodes into the relay selection process. More specifically, we propose two d...
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ISBN:
(纸本)9781467398152
In this paper, we propose novel relay selection policies that aim at reducing the average delay by incorporating the buffer size of the relay nodes into the relay selection process. More specifically, we propose two delay-aware protocols that are based on the max - link relay selection protocol. First, a delay-aware only approach while it reduces the delays considerably it starves the buffers and increases the outage probability of the system. Towards this end, we propose a delay- and diversity-aware buffer-aided relay selection policy that aims at reducing the average delay considerably and at the same time maintaining good diversity. The protocols are analyzed by means of Markov Chains and expressions for the outage, throughput and delay are derived. The performance and use of our proposed algorithms is demonstrated via extensive simulations and comparisons.
The control of low power systems, which include renewable energy sources, a local network, an electrochemical storage subsystem and a grid connection, is inherently hierarchical. The lower level consists on the contro...
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ISBN:
(纸本)9781509013159
The control of low power systems, which include renewable energy sources, a local network, an electrochemical storage subsystem and a grid connection, is inherently hierarchical. The lower level consists on the controlsystems of wind sources (power limitation at rated value in full load regime and energy optimization in partial load regime) and photovoltaic (energy conversion optimization). The control problem at the higher level is treated in this paper and aims at generating the control solution for the energetic transfer between the system components, given that the powers of the renewable energy sources and the power in the local network are random variables. For the higher level, the paper proposes a mixed performance criterion, which includes an energy sub-criterion concerning the costs of electricity supplied to local consumers, and a sub-criterion related to the lifetime of the battery. It was defined an algorithm to control the energy transfer in the system, implemented by using fuzzy techniques and a deficit/surplus prediction of energy in the system.
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