This article presents a wind plant control strategy that optimizes the yaw settings of turbines for improved energy production whole by taking into account wake effects. The optimization controller is based on novel internal parametric model effects called FLOw Redirection and Induction in Steady-state (FLORIS) model. FLORIS predicts steady-state locations effective flow velocities at each turbine, resulting turbine electrical levels, as function axial induction angle different rotors. has...

We present a view of cooperative control using the language learning in games. review game-theoretic concepts potential and weakly acyclic games, demonstrate how several problems, such as consensus dynamic sensor coverage, can be formulated these settings. Motivated by this connection, we build upon to better accommodate broader class problems. In particular, extend existing algorithms restricted action sets caused limitations agent capabilities group based decision making. Furthermore, also...

We consider an autonomous vehicle-target assignment problem where a group of vehicles are expected to optimally assign themselves set targets. introduce game-theoretical formulation the in which viewed as self-interested decision makers. Thus, we seek optimization global utility function through that capable making individually rational decisions optimize their own functions. The first important aspect is choose functions such way objectives localized each vehicle yet aligned with function....

This brief explores the applicability of recent results in game theory and cooperative control to problem optimizing energy production wind farms. One such result is a model-free strategy that completely decentralized leads efficient system behavior virtually any distributed system. We demonstrate this learning rule can provably maximize farms without explicitly modeling aerodynamic interaction amongst turbines.

We consider multi-player repeated games involving a large number of players with strategy spaces and enmeshed utility structures. In these ldquolarge-scalerdquo games, are inherently faced limitations in both their observational computational capabilities. Accordingly, large-scale need to make decisions using algorithms that accommodate information gathering processing. This disqualifies some the well known decision making models such as ldquoFictitious Playrdquo (FP), which each player must...

The central goal in multiagent systems is to design local control laws for the individual agents ensure that emergent global behavior desirable with respect a given system level objective. Ideally, designer seeks satisfy this while conditioning each agent's law on least amount of information possible. This paper focuses achieving using field game theory. In particular, we derive systematic methodology designing agent objective functions guarantees (i) an equivalence between resulting Nash...

We consider repeated multiplayer games in which players repeatedly and simultaneously choose strategies from a finite set of available according to some strategy adjustment process. focus on the specific class weakly acyclic games, is particularly relevant for multiagent cooperative control problems. A process determines how select their at any stage as function information gathered over previous stages. Of particular interest are “payoff-based” processes which, stage, know only own actions...

Game-theoretic tools are becoming a popular design choice for distributed resource allocation algorithms. A central component of this is the assignment utility functions to individual agents. The goal assign each agent an admissible function such that resulting game possesses host desirable properties, including scalability, tractability, and existence efficiency pure Nash equilibria. In paper we formally study question on class games termed welfare games. We identify several methodologies...

This paper presents a novel parametric model that will be used to optimize the yaw settings of wind turbines in plant for improved electrical energy production whole plant. The predicts effective steady-state flow velocities at each turbine, as well resulting productions, function axial induction and angle different rotors. has limited number parameters are estimated based on data. Moreover, it is shown how this can using game-theoretic approach. In case study we demonstrate our fits data...

We propose a simple payoff-based learning rule that is completely decentralized and leads to an efficient configuration of actions in any $n$-person finite strategic-form game with generic payoffs. The algorithm follows the theme exploration versus exploitation hence stochastic nature. prove if all agents adhere this algorithm, then will select action profile maximizes sum agents' payoffs high percentage time. requires no communication. Agents respond solely changes their own realized...

Game theory is the study of decision problems in which there are multiple makers and quality a maker's choice depends on both that choices others. While game has been studied predominantly as modeling paradigm mathematical social sciences, strong connection to control systems controller can be viewed decision-making entity. Accordingly, relevant settings with interacting controllers. This article presents an introduction theory, followed by sampling results three specific topics where played...

Game-theoretic control is a promising new approach for distributed resource allocation. In this paper, we describe how game-theoretic can be viewed as having an intrinsic layered architecture, which provides modularization that simplifies the design. We illustrate architectural view by presenting details about one particular instantiation using potential games interface. This example serves to highlight strengths and limitations of proposed architecture while also illustrating relationship...

We consider the problem of designing distribution rules to share “welfare” (cost or revenue) among individually strategic agents. There are many known that guarantee existence a (pure) Nash equilibrium in this setting, e.g., Shapley value and its weighted variants; however, characterization space guarantees is unknown. Our work provides an exact for specific class scalable separable games includes variety applications such as facility location, routing, network formation, coverage games....

No-regret algorithms have been proposed to control a wide variety of multi-agent systems. The appeal no-regret is that they are easily implementable in large scale systems because players make decisions using only retrospective or "regret based" information. Furthermore, there existing results proving the collective behavior will asymptotically converge set points "no-regret" any game. We illustrate, through simple example, need not reflect desirable operating conditions for system....

Several multiagent systems exemplify the need for establishing distributed control laws that ensure resulting agents' collective behavior satisfies a given coupled constraint. This technical note focuses on design of such through game-theoretic framework. In particular, this provides two systematic methodologies local agent objective functions guarantee all Nash equilibria optimize system level while also satisfying Furthermore, designed fit into framework state based potential games....

Game theory is emerging as a popular tool for distributed control of multiagent systems. To take advantage these game theoretic tools, the interactions autonomous agents must be designed within game-theoretic environment. A central component this design assignment local utility function to each agent. One promising approach assigning agent according agent's Shapley value. This method frequently results in games that possess many desirable features, such existence pure Nash equilibria with...

This paper surveys recent results in game theory and cooperative control highlights their implications for the problem of optimizing energy production wind farms. One such result is a simple payoff-based learning rule that completely decentralized leads to an efficient configuration actions virtually any distributed system. We demonstrate this can be used provably maximize farms without explicitly modeling aerodynamic interaction amongst turbines.

In a multiagent system, transitioning from centralized to distributed decision-making strategy can introduce vulnerability adversarial manipulation. We study the potential for manipulation in class of graphical coordination games where adversary pose as friendly agent game, thereby influencing rules subset agents. The adversary's influence cascade throughout indirectly other agents' behavior and significantly impacting emergent collective behavior. main results this paper focus on...

Many of today's engineered systems are tightly interconnected with their users, and in many cases, system performance depends greatly on user behavior [1]. As a result, the traditional lines between engineering social sciences becoming increasingly blurred, analytical tools such as game theory finding new applications [2], [3]. It is often insufficient to judge an its technical merits alone since strategic can lead unpredictable and/or undesirable results [4]. Of particular importance this...

This paper presents a view of cooperative control using the language learning in games. We review game theoretic concepts potential games and weakly acyclic demonstrate how specific problem consensus can be formulated these settings. Motivated by this connection, we build upon to better accommodate broader class problems. In particular, introduce sometimes for time-varying objective functions action sets, provide distributed algorithms convergence an equilibrium. Finally, illustrate...

The central goal in multiagent systems is to design local control laws for the individual agents ensure that emergent global behavior desirable with respect a given system level objective. Ideally, designer seeks satisfy this while conditioning each agent's law on least amount of information possible. Unfortunately, there are no existing methodologies addressing challenge. paper address challenge using field game theory. Utilizing theory and requires two steps: (i) defining objective...