Tamer Başar
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Tamer Başar
Mustafa Tamer Başar (born January 19, 1946) is a control and game theorist who is the ''Swanlund Endowed Chair'' and Center for Advanced Study Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign, USA. He is also the Director of the Center for Advanced Study (since 2014). Education Tamer Başar received a B.S. in Electrical Engineering from Boğaziçi University ''(formerly known as Robert College)'' at Bebek, in Istanbul, Turkey, in 1969, and M.S., M.Phil., and Ph.D. in engineering and applied science from Yale University, in 1970, 1971 and 1972, respectively. Academic life He joined the University of Illinois at Urbana–Champaign - Electrical and Computer Engineering Department in 1981. He was the founding president of the International Society of Dynamic Games during 1990–1994, the president of the IEEE Control Systems Society in 2000, and the president of the American Automatic Control Council during 2010–2011. ...
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National Academy Of Engineering
The National Academy of Engineering (NAE) is an American Nonprofit organization, nonprofit, NGO, non-governmental organization. It is part of the National Academies of Sciences, Engineering, and Medicine (NASEM), along with the National Academy of Sciences (NAS) and the National Academy of Medicine (NAM). The NAE operates engineering programs aimed at meeting national needs, encourages education and research, and recognizes the superior achievements of engineers. New members are annually elected by current members, based on their distinguished and continuing achievements in original research. The NAE is autonomous in its administration and in the selection of its members, sharing with the rest of the National Academies the role of advising the federal government. History The National Academies of Sciences, Engineering, and Medicine#History, National Academy of Sciences was created by an Act of Incorporation dated March 3, 1863, which was signed by then president of the United ...
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Minimax Estimator
In statistical decision theory, a minimax estimator \delta^M \,\! is an estimator which performs best in the worst possible case allowed in a problem. With problems of estimating a deterministic parameter (vector) \theta \in \Theta from observations x \in \mathcal, an estimator (estimation rule) \delta^M \,\! is called minimax if its maximal Risk function, risk is minimal among all estimators of \theta \,\!. Definition Definition : An estimator \delta^M:\mathcal \rightarrow \Theta \,\! is called minimax with respect to a risk function R(\theta,\delta) \,\! if it achieves the smallest maximum risk among all estimators, satisfying : \sup_ R(\theta,\delta^M) = \inf_\delta \sup_ R(\theta,\delta). \, Problem setup An example is the problem of estimating a deterministic (not Bayes estimator, Bayesian) parameter \theta \in \Theta from noisy or corrupt data x \in \mathcal related through the conditional probability distribution P(x\mid\theta)\,\!. The goal is to find a "good" estimato ...
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Distributed Computing
Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components are located on different networked computers. The components of a distributed system communicate and coordinate their actions by passing messages to one another in order to achieve a common goal. Three significant challenges of distributed systems are: maintaining concurrency of components, overcoming the lack of a global clock, and managing the independent failure of components. When a component of one system fails, the entire system does not fail. Examples of distributed systems vary from SOA-based systems to microservices to massively multiplayer online games to peer-to-peer applications. Distributed systems cost significantly more than monolithic architectures, primarily due to increased needs for additional hardware, servers, gateways, firewalls, new subnets, proxies, and so on. Also, distributed systems are prone to ...
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Decentralised System
A decentralised system in systems theory is a system in which lower level components operate on local information to accomplish global goals. The global pattern of behaviour is an emergent property of dynamical mechanisms that act upon local components, such as indirect communication, rather than the result of a central ordering influence of a centralised system. Centralised versus decentralised systems A centralised system is one in which a central controller exercises control over the lower-level components of the system directly or through the use of a power hierarchy (such as instructing a middle level component to instruct a lower level component). The complex behaviour exhibited by this system is thus the result of the central controller's "control" over lower level components in the system, including the active supervision of the lower-level components. A decentralised system, on the other hand, is one in which complex behaviour emerges through the work of lower level c ...
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Decentralized
Decentralization or decentralisation is the process by which the activities of an organization, particularly those related to planning and decision-making, are distributed or delegated away from a central, authoritative location or group and given to smaller factions within it. Concepts of decentralization have been applied to group dynamics and management science in private businesses and organizations, political science, law and public administration, technology, economics and money. History The word "''centralisation''" came into use in France in 1794 as the post-Revolution French Directory leadership created a new government structure. The word "''décentralisation''" came into usage in the 1820s. "Centralization" entered written English in the first third of the 1800s; mentions of decentralization also first appear during those years. In the mid-1800s Tocqueville would write that the French Revolution began with "a push towards decentralization" but became, "in the en ...
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Control Systems Engineering
Control engineering, also known as control systems engineering and, in some European countries, automation engineering, is an engineering discipline that deals with control systems, applying control theory to design equipment and systems with desired behaviors in control environments. The discipline of controls overlaps and is usually taught along with electrical engineering, chemical engineering and mechanical engineering at many institutions around the world. The practice uses sensors and detectors to measure the output performance of the process being controlled; these measurements are used to provide corrective feedback helping to achieve the desired performance. Systems designed to perform without requiring human input are called automatic control systems (such as cruise control for regulating the speed of a car). Multi-disciplinary in nature, control systems engineering activities focus on implementation of control systems mainly derived by mathematical modeling of a diver ...
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Control Systems
A control system manages, commands, directs, or regulates the behavior of other devices or systems using control loops. It can range from a single home heating controller using a thermostat controlling a domestic boiler to large industrial control systems which are used for controlling Process (engineering), processes or machines. The control systems are designed via control engineering process. For continuously modulated control, a feedback controller is used to automatically control a process or operation. The control system compares the value or status of the process variable (PV) being controlled with the desired value or Setpoint (control system), setpoint (SP), and applies the difference as a control signal to bring the process variable output of the Plant (control theory), plant to the same value as the setpoint. For Sequential logic, sequential and combinational logic, software logic, such as in a programmable logic controller, is used. Open-loop and closed-loop co ...
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Dynamic Game
In game theory, a sequential game is defined as a game where one player selects their action before others, and subsequent players are informed of that choice before making their own decisions. This turn-based structure, governed by a time axis, distinguishes sequential games from simultaneous games, where players act without knowledge of others’ choices and outcomes are depicted in payoff matrices (e.g., rock-paper-scissors). Sequential games are a type of dynamic game, a broader category where decisions occur over time (e.g., differential games), but they specifically emphasize a clear order of moves with known prior actions. Because later players know what earlier players did, the order of moves shapes strategy through information rather than timing alone. Sequential games are typically represented using decision trees, which map out all possible sequences of play, unlike the static matrices of simultaneous games. Examples include chess, infinite chess, backgammon, tic-ta ...
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Hybrid Systems
A hybrid system is a dynamical system that exhibits both continuous and discrete dynamic behavior – a system that can both ''flow'' (described by a differential equation) and ''jump'' (described by a state machine, automaton, or a difference equation). Often, the term "hybrid dynamical system" is used instead of "hybrid system", to distinguish from other usages of "hybrid system", such as the combination neural nets and fuzzy logic, or of electrical and mechanical drivelines. A hybrid system has the benefit of encompassing a larger class of systems within its structure, allowing for more flexibility in modeling dynamic phenomena. In general, the ''state'' of a hybrid system is defined by the values of the ''continuous variables'' and a discrete ''mode''. The state changes either continuously, according to a flow condition, or discretely according to a ''control graph''. Continuous flow is permitted as long as so-called ''invariants'' hold, while discrete transitions can o ...
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Stability Theory
In mathematics, stability theory addresses the stability of solutions of differential equations and of trajectories of dynamical systems under small perturbations of initial conditions. The heat equation, for example, is a stable partial differential equation because small perturbations of initial data lead to small variations in temperature at a later time as a result of the maximum principle. In partial differential equations one may measure the distances between functions using Lp space, Lp norms or the sup norm, while in differential geometry one may measure the distance between spaces using the Gromov–Hausdorff convergence, Gromov–Hausdorff distance. In dynamical systems, an orbit (dynamics), orbit is called ''Lyapunov stability, Lyapunov stable'' if the forward orbit of any point is in a small enough neighborhood or it stays in a small (but perhaps, larger) neighborhood. Various criteria have been developed to prove stability or instability of an orbit. Under favorable ...
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Adaptive Control
Adaptive control is the control method used by a controller which must adapt to a controlled system with parameters which vary, or are initially uncertain. For example, as an aircraft flies, its mass will slowly decrease as a result of fuel consumption; a control law is needed that adapts itself to such changing conditions. Adaptive control is different from robust control in that it does not need ''a priori'' information about the bounds on these uncertain or time-varying parameters; robust control guarantees that if the changes are within given bounds the control law need not be changed, while adaptive control is concerned with control law changing itself. Parameter estimation The foundation of adaptive control is parameter estimation, which is a branch of system identification. Common methods of estimation include recursive least squares and gradient descent. Both of these methods provide update laws that are used to modify estimates in real-time (i.e., as the system operates). ...
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Control Theory
Control theory is a field of control engineering and applied mathematics that deals with the control system, control of dynamical systems in engineered processes and machines. The objective is to develop a model or algorithm governing the application of system inputs to drive the system to a desired state, while minimizing any ''delay'', ''overshoot'', or ''steady-state error'' and ensuring a level of control Stability theory, stability; often with the aim to achieve a degree of Optimal control, optimality. To do this, a controller with the requisite corrective behavior is required. This controller monitors the controlled process variable (PV), and compares it with the reference or Setpoint (control system), set point (SP). The difference between actual and desired value of the process variable, called the ''error'' signal, or SP-PV error, is applied as feedback to generate a control action to bring the controlled process variable to the same value as the set point. Other aspects ...
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