The Experts below are selected from a list of 63684 Experts worldwide ranked by ideXlab platform
Paul Dupuis - One of the best experts on this subject based on the ideXlab platform.
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minimax Optimal control of stochastic uncertain systems with relative entropy constraints
IEEE Transactions on Automatic Control, 2000Co-Authors: Ian R. Petersen, Matthew R. James, Paul DupuisAbstract:This paper considers a new class of discrete time stochastic uncertain systems in which the uncertainty is described by a constraint on the relative entropy between a nominal noise distribution and the perturbed noise distribution. This uncertainty description is a natural extension to the case of stochastic uncertain systems, of the sum quadratic constraint uncertainty description. This paper solves problems of worst-case robust performance analysis and output feedback minimax Optimal Controller synthesis in a general nonlinear setting. Specializing these results to the linear case leads to a minimax linear quadratic Gaussian (LQG) Optimal Controller. This Controller is defined by Riccati difference equations and a Kalman filter-like state equation. The paper also shows that the minimax LQG problem will have a solution if and only if a corresponding H/sup /spl infin// control problem has a solution. A linear example is presented to illustrate the minimax LQG methodology.
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minimax Optimal control of stochastic uncertain systems with relative entropy constraints
Conference on Decision and Control, 1997Co-Authors: Ian R. Petersen, Matthew R. James, Paul DupuisAbstract:Considers a class of discrete time stochastic uncertain systems in which the uncertainty is described by a constraint on the relative entropy between a nominal noise distribution and the perturbed noise distribution. The paper solves problems of worst case robust performance analysis and output feedback minimax Optimal Controller synthesis in a general nonlinear setting. Specializing these results to the linear case leads to a minimax LQG Optimal Controller.
Jibril Mustefa - One of the best experts on this subject based on the ideXlab platform.
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H2 Optimal and μ-synthesis Design of Quarter Car Active Suspension System
The International Institute for Science Technology and Education (IISTE), 2020Co-Authors: Jibril Mustefa, Alluvada PrashanthAbstract:Better journey comfort and controllability of automobile are pursued via car industries with the aid of considering using suspension system which plays a very crucial function in handling and ride comfort characteristics. This paper presents the design of an active suspension of quarter automobile system using robust H2 Optimal Controller and robust μ - synthesis Controller with a second order hydraulic actuator. Parametric uncertainties have been additionally considered to model within the system. Numerical simulation become completed to the designed Controllers. Results display that during spite of introducing uncertainties, the designed μ - synthesis Controller improves ride consolation and road protecting of the automobile while as compared to the H2 Optimal Controller. Index Terms:Quarter car active suspension system, H2 Optimal Controller, μ - synthesis Controller DOI: 10.7176/ISDE/11-2-01 Publication date:March 31st 202
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H2 Optimal and μ -synthesis Design of Quarter Car Active Suspension System
Control Theory and Informatics, 2020Co-Authors: Jibril MustefaAbstract:Better journey comfort and controllability of automobile are pursued via car industries with the aid of considering using suspension system which plays a very crucial function in handling and ride comfort characteristics. This paper presents the design of an active suspension of quarter automobile system using robust H2 Optimal Controller and robust μ - synthesis Controller with a second order hydraulic actuator. Parametric uncertainties have been additionally considered to model within the system. Numerical simulation become completed to the designed Controllers. Results display that during spite of introducing uncertainties, the designed μ - synthesis Controller improves ride consolation and road protecting of the automobile while as compared to the H2 Optimal Controller. Index Terms--- Quarter car active suspension system, H2 Optimal Controller, μ - synthesis Controller DOI: 10.7176/CTI/10-03 Publication date:July 31st 202
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H2 Optimal and μ-synthesis design of quarter car active suspension system
2020Co-Authors: Jibril MustefaAbstract:Better journey comfort and controllability of automobile are pursued via car industries with the aid of considering using suspension system which plays a very crucial function in handling and ride comfort characteristics. This paper presents the design of an active suspension of quarter automobile system using robust H2 Optimal Controller and robust μ - synthesis Controller with a second order hydraulic actuator. Parametric uncertainties have been additionally considered to model within the system. Numerical simulation become completed to the designed Controllers. Results display that during spite of introducing uncertainties, the designed μ - synthesis Controller improves ride consolation and road protecting of the automobile while as compared to the H2 Optimal Controller
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Comparison of Mixed H 2 H∞ with Regional Pole Placement Control and H 2 Optimal Control for the Design of Steam Condenser
2020Co-Authors: Jibril MustefaAbstract:This paper investigates the comparison between mixed H 2 /H∞ with regional pole placement control and H 2 Optimal control for the design of steam condenser. The comparison have been made for a step change in the steam condenser pressure set point for a step change of 10 & 23 seconds using MATLAB/Simulink environment for the steam condenser with mixed H 2 /H∞ with regional pole placement Controller, steam condenser with H 2 Optimal Controller and steam condenser without Controller. The steam condenser with mixed H 2 /H∞ with regional pole placement Controller presented excellent and superior dynamic performance in response to the two step changes and an improvement in settling time. The overall simulation results demonstrated that the steam condenser with mixed H 2 /H∞ with regional pole placement Controller can be an efficient alternative to the steam condenser with H 2 Optimal Controller for the steam condenser
Sanjay Lall - One of the best experts on this subject based on the ideXlab platform.
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Optimal Controller synthesis for the decentralized two player problem with output feedback
Advances in Computing and Communications, 2012Co-Authors: Laurent Lessard, Sanjay LallAbstract:In this paper, we present a Controller synthesis algorithm for a decentralized control problem. We consider an architecture in which there are two interconnected linear subsystems. Both Controllers seek to optimize a global quadratic cost, despite having access to different subsets of the available measurements. Many special cases of this problem have previously been solved, most notably the state-feedback case. The generalization to outputfeedback is nontrivial, as the classical separation principle does not hold. Herein, we present the first explicit state-space realization for an Optimal Controller for the general two-player problem.
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Optimal Controller synthesis for a decentralized two player system with partial output feedback
American Control Conference, 2011Co-Authors: John Swigart, Sanjay LallAbstract:In this paper, we derive the Optimal control policy for a decentralized control problem. The system considered here consists of two interconnected subsystems with communication allowed in only one direction. In addition, full state feedback is not assumed, as in previous instances of this problem. We construct the Optimal Controllers via a spectral factorization approach. Explicit state-space formulae are provided, and the orders of the Optimal Controllers are established.
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an explicit state space solution for a decentralized two player Optimal linear quadratic regulator
Advances in Computing and Communications, 2010Co-Authors: John Swigart, Sanjay LallAbstract:We develop Controller synthesis algorithms for decentralized control problems, where individual subsystems are connected over a network. We focus on the simplest information structure, consisting of two interconnected linear systems, and construct the Optimal Controller subject to a decentralization constraint via a spectral factorization approach. We provide explicit state-space formulae for the Optimal Controller, characterize its order, and show that its states are those of a particular Optimal estimator.
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an explicit dynamic programming solution for a de centralized two player Optimal linear quadratic regulator
2010Co-Authors: John Swigart, Sanjay LallAbstract:We develop Optimal Controller synthesis algorithms for decentralized control problems, in which individual subsystems are connected over a network. We consider a simple information structure, consisting of two interconnected linear systems, and construct the Optimal Controller subject to a decentralization constraint via a novel dynamic programming method. We provide explicit state-space formulae for the Optimal Controller, and show that each player has to do more than simply estimate the states that they cannot observe. In other words, the simplest separation principle does not hold for this decentralized control problem.
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Optimal control of distributed markov decision processes with network delays
Conference on Decision and Control, 2007Co-Authors: Sachin Adlakha, Sanjay Lall, R Madan, Andrea GoldsmithAbstract:We consider the problem of finding an Optimal feedback Controller for a network of interconnected subsystems, each of which is a Markov decision process. Each subsystem is coupled to its neighbors via communication links by which signals are delayed but are otherwise transmitted noise-free. One of the subsystems receives input from a Controller, and the Controller receives delayed state- measurements from all of the subsystems. We show that an Optimal Controller requires only a finite amount of memory which does not grow with time, and obtain a bound on the amount of memory that a Controller needs to have for each subsystem. This makes the computation of an Optimal Controller through dynamic programming tractable. We illustrate our result by a numerical example, and show that it generalizes previous results on Markov decision processes with delayed state measurements.
Dongbin Zhao - One of the best experts on this subject based on the ideXlab platform.
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data based adaptive critic designs for nonlinear robust Optimal control with uncertain dynamics
Systems Man and Cybernetics, 2016Co-Authors: Ding Wang, Derong Liu, Qichao Zhang, Dongbin ZhaoAbstract:In this paper, the infinite-horizon robust Optimal control problem for a class of continuous-time uncertain nonlinear systems is investigated by using data-based adaptive critic designs. The neural network identification scheme is combined with the traditional adaptive critic technique, in order to design the nonlinear robust Optimal control under uncertain environment. First, the robust Optimal Controller of the original uncertain system with a specified cost function is established by adding a feedback gain to the Optimal Controller of the nominal system. Then, a neural network identifier is employed to reconstruct the unknown dynamics of the nominal system with stability analysis. Hence, the data-based adaptive critic designs can be developed to solve the Hamilton–Jacobi–Bellman equation corresponding to the transformed Optimal control problem. The uniform ultimate boundedness of the closed-loop system is also proved by using the Lyapunov approach. Finally, two simulation examples are presented to illustrate the effectiveness of the developed control strategy.
Haiyang Fang - One of the best experts on this subject based on the ideXlab platform.
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adaptive Optimal Controller design for a class of ldi based neural network systems with input time delays
Neurocomputing, 2020Co-Authors: Chenglong Wang, Haiyang FangAbstract:Abstract In this paper, a new online adaptive Optimal Controller design scheme is studied for a class of nonlinear systems with input time-delays. First, we linearize the original nonlinear systems by means of linear differential inclusion technique. Then the adaptive Optimal Controller of the linearized systems with input time-delays is obtained by online policy iteration algorithm. It also proves the convergence of the designed adaptive Optimal control algorithm. Finally, the effectiveness of the proposed method is verified by two simulation examples.
