Dahleh, Munther A.
Overview
Works:  50 works in 90 publications in 2 languages and 550 library holdings 

Roles:  Author 
Classifications:  TJ213, 629.8312 
Publication Timeline
.
Most widely held works by
Munther A Dahleh
Control of uncertain systems : a linear programming approach by
Munther A Dahleh(
Book
)
8 editions published in 1995 in English and held by 183 WorldCat member libraries worldwide
8 editions published in 1995 in English and held by 183 WorldCat member libraries worldwide
Computational methods for controller design by
Nicola Elia(
Book
)
12 editions published in 1998 in English and German and held by 175 WorldCat member libraries worldwide
The monograph is concerned with computational methods for controller design that allow several typical performance specifications to be directly imposed on a system. The general approach proposed, is applicable to a large class of problems; it is based on posing multiobjective control problems as convex infinite dimensional optimization problems. Particularly interesting and useful are the following methodological as pects of the approach proposed in the monograph. These are: A unified way to pose the problems as generalized linear programs. Duality theory results that characterize the duality relationship for the generalized linear programs arising from multiobjective control problems. A set of tools to analyse the convergence properties of the computational method based on the duality relationship. The complete analysis and extension of methods developed for the L1 problem, for several important multiobjective problems. This book is primarily concerned with multiobjective control problems as convex optimizations on the space of the closed loop maps. However, the issue of deriving exact or approximate solutions is similar when the problems are posed as dynamic games in s tate space. Therefore the problem of finding the state feedback controller that minimizes the worstcase peaktopeak amplification of the closed loop system, is considered in the last chapter. The objective of this work is to propose generic computation methods that can be used to solve a wide range of multiobjective control problems. Infinite dimensional convex optimization problems are considered, giving the book a broader focus than other competitive titles in this field. This nonexclusive approach will have a wide appeal for scientists and graduate students. They will be able to determine and analyse readily implementable computational methods to derive exact or approximate solutions. Key words for the catalogue index: Controller design, multi objective control, computational methods, linear programming, robust control. USPs:Generic computational methods are proposed  these can be used to solve a wide range of multiobjective control p roblems. A new computational method for the L1 problem is suggested, which is superior to existing approaches and is based on the solution of a mixed objective problem. The reader will greatly benefit from the comprehensive treatment of this topic
12 editions published in 1998 in English and German and held by 175 WorldCat member libraries worldwide
The monograph is concerned with computational methods for controller design that allow several typical performance specifications to be directly imposed on a system. The general approach proposed, is applicable to a large class of problems; it is based on posing multiobjective control problems as convex infinite dimensional optimization problems. Particularly interesting and useful are the following methodological as pects of the approach proposed in the monograph. These are: A unified way to pose the problems as generalized linear programs. Duality theory results that characterize the duality relationship for the generalized linear programs arising from multiobjective control problems. A set of tools to analyse the convergence properties of the computational method based on the duality relationship. The complete analysis and extension of methods developed for the L1 problem, for several important multiobjective problems. This book is primarily concerned with multiobjective control problems as convex optimizations on the space of the closed loop maps. However, the issue of deriving exact or approximate solutions is similar when the problems are posed as dynamic games in s tate space. Therefore the problem of finding the state feedback controller that minimizes the worstcase peaktopeak amplification of the closed loop system, is considered in the last chapter. The objective of this work is to propose generic computation methods that can be used to solve a wide range of multiobjective control problems. Infinite dimensional convex optimization problems are considered, giving the book a broader focus than other competitive titles in this field. This nonexclusive approach will have a wide appeal for scientists and graduate students. They will be able to determine and analyse readily implementable computational methods to derive exact or approximate solutions. Key words for the catalogue index: Controller design, multi objective control, computational methods, linear programming, robust control. USPs:Generic computational methods are proposed  these can be used to solve a wide range of multiobjective control p roblems. A new computational method for the L1 problem is suggested, which is superior to existing approaches and is based on the solution of a mixed objective problem. The reader will greatly benefit from the comprehensive treatment of this topic
BIBO stability robustness in the presence of coprime factor perturbations by
Munther A Dahleh(
Book
)
3 editions published in 1990 in English and held by 5 WorldCat member libraries worldwide
3 editions published in 1990 in English and held by 5 WorldCat member libraries worldwide
Optimal asymptotic identification under bounded disturbances by
David N. C Tse(
Book
)
2 editions published in 1990 in English and held by 4 WorldCat member libraries worldwide
2 editions published in 1990 in English and held by 4 WorldCat member libraries worldwide
L¹optimal attitude control of a space station by
Munther A Dahleh(
Book
)
2 editions published in 1990 in English and held by 3 WorldCat member libraries worldwide
2 editions published in 1990 in English and held by 3 WorldCat member libraries worldwide
Optimal rejection of bounded persistent disturbances in periodic systems by
Munther A Dahleh(
Book
)
2 editions published in 1990 in English and held by 3 WorldCat member libraries worldwide
2 editions published in 1990 in English and held by 3 WorldCat member libraries worldwide
Bayesian learning in social networks by
Daron Acemoglu(
Book
)
5 editions published in 2008 in English and held by 3 WorldCat member libraries worldwide
We study the perfect Bayesian equilibrium of a model of learning over a general social network. Each individual receives a signal about the underlying state of the world, observes the past actions of a stochasticallygenerated neighborhood of individuals, and chooses one of two possible actions. The stochastic process generating the neighborhoods defines the network topology (social network). The special case where each individual observes all past actions has been widely studied in the literature. We characterize purestrategy equilibria for arbitrary stochastic and deterministic social networks and characterize the conditions under which there will be asymptotic learning  that is, the conditions under which, as the social network becomes large, individuals converge (in probability) to taking the right action. We show that when private beliefs are unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some minimal amount of "expansion in observations". Our main theorem shows that when the probability that each individual observes some other individual from the recent past converges to one as the social network becomes large, unbounded private beliefs are sufficient to ensure asymptotic learning. This theorem therefore establishes that, with unbounded private beliefs, there will be asymptotic learning an almost all reasonable social networks. We also show that for most network topologies, when private beliefs are bounded, there will not be asymptotic learning. In addition, in contrast to the special case where all past actions are observed, asymptotic learning is possible even with bounded beliefs in certain stochastic network topologies
5 editions published in 2008 in English and held by 3 WorldCat member libraries worldwide
We study the perfect Bayesian equilibrium of a model of learning over a general social network. Each individual receives a signal about the underlying state of the world, observes the past actions of a stochasticallygenerated neighborhood of individuals, and chooses one of two possible actions. The stochastic process generating the neighborhoods defines the network topology (social network). The special case where each individual observes all past actions has been widely studied in the literature. We characterize purestrategy equilibria for arbitrary stochastic and deterministic social networks and characterize the conditions under which there will be asymptotic learning  that is, the conditions under which, as the social network becomes large, individuals converge (in probability) to taking the right action. We show that when private beliefs are unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some minimal amount of "expansion in observations". Our main theorem shows that when the probability that each individual observes some other individual from the recent past converges to one as the social network becomes large, unbounded private beliefs are sufficient to ensure asymptotic learning. This theorem therefore establishes that, with unbounded private beliefs, there will be asymptotic learning an almost all reasonable social networks. We also show that for most network topologies, when private beliefs are bounded, there will not be asymptotic learning. In addition, in contrast to the special case where all past actions are observed, asymptotic learning is possible even with bounded beliefs in certain stochastic network topologies
H [subscript infinity] optimal control for the attitude control and momentum management of the space station by A Pothiawala(
Book
)
2 editions published in 1990 in English and held by 3 WorldCat member libraries worldwide
The objective of this research is to use the H[subscript infinity] optimality criterion to design a controller for the linearized set of Space Station dynamics equations. Besides studying the various closedloop properties of the resulting linear system, we would like to examine the robustness properties of this controller i.e. how well it performs in the presence of unmodelled dynamics, nonlinearities and disturbances. Furthermore, we will compare and contrast the control action of the H[subscript infinity] controller with that of the LQR controller."
2 editions published in 1990 in English and held by 3 WorldCat member libraries worldwide
The objective of this research is to use the H[subscript infinity] optimality criterion to design a controller for the linearized set of Space Station dynamics equations. Besides studying the various closedloop properties of the resulting linear system, we would like to examine the robustness properties of this controller i.e. how well it performs in the presence of unmodelled dynamics, nonlinearities and disturbances. Furthermore, we will compare and contrast the control action of the H[subscript infinity] controller with that of the LQR controller."
H[infinity] and H² optimal controllers for periodic and multirate systems by Petros Voulgaris(
Book
)
3 editions published in 1991 in English and held by 3 WorldCat member libraries worldwide
3 editions published in 1991 in English and held by 3 WorldCat member libraries worldwide
A class of adaptive controllers with application to robust adaptive control by
Mohammed A Dahleh(
Book
)
2 editions published in 1988 in English and held by 2 WorldCat member libraries worldwide
2 editions published in 1988 in English and held by 2 WorldCat member libraries worldwide
On slowly timevarying systems by
Mohammed A Dahleh(
Book
)
1 edition published in 1989 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 1989 in English and held by 2 WorldCat member libraries worldwide
Reducedorder modelling and control of a class of systems for which balanced truncation is Hankelnorm optimal by
D Mustafa(
Book
)
1 edition published in 1992 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 1992 in English and held by 2 WorldCat member libraries worldwide
L1̳ sensitivity minimization for plants with commensurate delays by
Munther A Dahleh(
Book
)
2 editions published in 1988 in English and held by 2 WorldCat member libraries worldwide
2 editions published in 1988 in English and held by 2 WorldCat member libraries worldwide
Timevarying compensation can yield no improvement for l₁ sensitivity minimization by
Munther A Dahleh(
Book
)
2 editions published in 1988 in English and held by 2 WorldCat member libraries worldwide
2 editions published in 1988 in English and held by 2 WorldCat member libraries worldwide
Gun/turret system identification and controller design by
Dragan Obradovic(
Book
)
1 edition published in 1992 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 1992 in English and held by 2 WorldCat member libraries worldwide
Minimization of the L[infinity]induced norm for sampleddata systems by
Bassam Bamieh(
Book
)
2 editions published in 1991 in English and held by 2 WorldCat member libraries worldwide
2 editions published in 1991 in English and held by 2 WorldCat member libraries worldwide
Nonlinear Control and Identification(
Book
)
2 editions published in 2002 in English and held by 1 WorldCat member library worldwide
This research is motivated by the problem of motion planning of autonomous vehicles in an uncertain environment. A possible approach to reduce the computational complexity of the motion planning problem for a nonlinear, high dimensional system, is based on a quantization of the system dynamics, in the sense that we restrict the feasible nominal system trajectories to the family of timeparametrized curves that can be obtained by the Interconnection of appropriately defined primitives. These primitives will then constitute a 'maneuver library' from which the nominal trajectory will be constructed. Instead of solving an optimal control problem over a high dimensional, continuous space, we solve a mixed integer programming problem, over a much smaller space. At the core of the control architecture lies a hybrid automaton, the states of which represent feasible trajectory primitives for the vehicle. Each constituent subsystem of the hybrid controller will be the agent responsible for the maneuver execution. The task of the automaton will be the generation of complete, feasible and 'optimal' trajectories, via the interconnection of the available primitives. Apart from the reduction in computational complexity, one of the objectives of this approach is the ability to provide a mathematical foundation for generating a provably stable hierarchical system, and for developing the tools to analyze robustness in the presence of uncertainty in the process as well as in the environment
2 editions published in 2002 in English and held by 1 WorldCat member library worldwide
This research is motivated by the problem of motion planning of autonomous vehicles in an uncertain environment. A possible approach to reduce the computational complexity of the motion planning problem for a nonlinear, high dimensional system, is based on a quantization of the system dynamics, in the sense that we restrict the feasible nominal system trajectories to the family of timeparametrized curves that can be obtained by the Interconnection of appropriately defined primitives. These primitives will then constitute a 'maneuver library' from which the nominal trajectory will be constructed. Instead of solving an optimal control problem over a high dimensional, continuous space, we solve a mixed integer programming problem, over a much smaller space. At the core of the control architecture lies a hybrid automaton, the states of which represent feasible trajectory primitives for the vehicle. Each constituent subsystem of the hybrid controller will be the agent responsible for the maneuver execution. The task of the automaton will be the generation of complete, feasible and 'optimal' trajectories, via the interconnection of the available primitives. Apart from the reduction in computational complexity, one of the objectives of this approach is the ability to provide a mathematical foundation for generating a provably stable hierarchical system, and for developing the tools to analyze robustness in the presence of uncertainty in the process as well as in the environment
Robust controller designminimizing peaktopeak gain by
Munther A Dahleh(
Book
)
2 editions published in 1992 in English and held by 1 WorldCat member library worldwide
In this report, we address the general problem of designing controllers that minimize the maximum peaktopeak gain, otherwise known as the iota1 optimal control problem, in the presence of structured uncertainty
2 editions published in 1992 in English and held by 1 WorldCat member library worldwide
In this report, we address the general problem of designing controllers that minimize the maximum peaktopeak gain, otherwise known as the iota1 optimal control problem, in the presence of structured uncertainty
Robust Identification and Control(
Book
)
2 editions published in 1998 in English and held by 1 WorldCat member library worldwide
This final report summarizes the research contributions under AFOSR grant No. F496209510219. The work covered two major research directions. The first is in the area of robust linear and nonlinear control. In the linear area, a complete computationallybased methodology was developed for designing controllers that can meet multiple performance objectives in both the time and frequency domain. The research culminated in a book on multiobjective control. In the nonlinear area, an alternative to gainscheduling that requires scheduling in Lyapunov space has been proposed which gives rise to a computational tool for synthesizing controllers with guaranteed stability. In addition, the theory of Neurodynamic programming was developed to handle largescale nonlinear optimal control problems. This research culminated in another' book on the theory and applications of NeuroDynamic programming. The second research direction is in the area of system identification. In that field, a new paradigm was proposed that allows deriving simple lowcomplexity models from noisy data obtained from complex systems. Within this paradigm, it is shown how to bridge the gap between stochastic and deterministic descriptions of noise. These developments have been shown to play a major role in many application domains
2 editions published in 1998 in English and held by 1 WorldCat member library worldwide
This final report summarizes the research contributions under AFOSR grant No. F496209510219. The work covered two major research directions. The first is in the area of robust linear and nonlinear control. In the linear area, a complete computationallybased methodology was developed for designing controllers that can meet multiple performance objectives in both the time and frequency domain. The research culminated in a book on multiobjective control. In the nonlinear area, an alternative to gainscheduling that requires scheduling in Lyapunov space has been proposed which gives rise to a computational tool for synthesizing controllers with guaranteed stability. In addition, the theory of Neurodynamic programming was developed to handle largescale nonlinear optimal control problems. This research culminated in another' book on the theory and applications of NeuroDynamic programming. The second research direction is in the area of system identification. In that field, a new paradigm was proposed that allows deriving simple lowcomplexity models from noisy data obtained from complex systems. Within this paradigm, it is shown how to bridge the gap between stochastic and deterministic descriptions of noise. These developments have been shown to play a major role in many application domains
Robust controller design : a boundedinput boundedoutput worstcase approach by
Munther A Dahleh(
Book
)
2 editions published between 1991 and 1992 in English and held by 1 WorldCat member library worldwide
The problem of designing controllers that minimize the peaktopeak gain, or the 1one optimal control problem, in the presence of structured uncertainty is discussed in this report. Four problems are discussed. First, controller design in the presence of structureduncertainty with a general discussion of the synthesis of 1one optimal controllers is presented. Next, the 1one state feedback problem is discussed. Then, the advantages of nonlinear controllers in minimizing the 1infinity induced norm are summarized. Finally, peaktopeak performance for slowly time varying systems are considered ... 1 one Optimal control, Structured uncertainty, Nonlinear control, Time varying systems
2 editions published between 1991 and 1992 in English and held by 1 WorldCat member library worldwide
The problem of designing controllers that minimize the peaktopeak gain, or the 1one optimal control problem, in the presence of structured uncertainty is discussed in this report. Four problems are discussed. First, controller design in the presence of structureduncertainty with a general discussion of the synthesis of 1one optimal controllers is presented. Next, the 1one state feedback problem is discussed. Then, the advantages of nonlinear controllers in minimizing the 1infinity induced norm are summarized. Finally, peaktopeak performance for slowly time varying systems are considered ... 1 one Optimal control, Structured uncertainty, Nonlinear control, Time varying systems
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