Dynamic Programming And Optimal Control Approximate Dynamic Programming

Dynamic Programming and Optimal Control  Approximate dynamic programming PDF Book Details:
Author: Dimitri P. Bertsekas
Publisher:
ISBN: 9781886529441
Size: 78.59 MB
Format: PDF, Docs
Category : Mathematics
Languages : un
Pages : 694
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Dynamic Programming And Optimal Control Approximate Dynamic Programming PDF

by Dimitri P. Bertsekas, Dynamic Programming And Optimal Control Approximate Dynamic Programming Books available in PDF, EPUB, Mobi Format. Download Dynamic Programming And Optimal Control Approximate Dynamic Programming books,


Approximate Dynamic Programming Based Solutions For Fixed Final Time Optimal Control And Optimal Switching

Approximate Dynamic Programming Based Solutions for Fixed final time Optimal Control and Optimal Switching PDF Book Details:
Author: Ali Heydari
Publisher:
ISBN:
Size: 51.11 MB
Format: PDF, ePub, Docs
Category : Automatic programming (Computer science)
Languages : un
Pages : 239
View: 1569

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Approximate Dynamic Programming Based Solutions For Fixed Final Time Optimal Control And Optimal Switching PDF

by Ali Heydari, Approximate Dynamic Programming Based Solutions For Fixed Final Time Optimal Control And Optimal Switching Books available in PDF, EPUB, Mobi Format. Download Approximate Dynamic Programming Based Solutions For Fixed Final Time Optimal Control And Optimal Switching books, "Optimal solutions with neural networks (NN) based on an approximate dynamic programming (ADP) framework for new classes of engineering and non-engineering problems and associated difficulties and challenges are investigated in this dissertation. In the enclosed eight papers, the ADP framework is utilized for solving fixed-final-time problems (also called terminal control problems) and problems with switching nature. An ADP based algorithm is proposed in Paper 1 for solving fixed-final-time problems with soft terminal constraint, in which, a single neural network with a single set of weights is utilized. Paper 2 investigates fixed-final-time problems with hard terminal constraints. The optimality analysis of the ADP based algorithm for fixed-final-time problems is the subject of Paper 3, in which, it is shown that the proposed algorithm leads to the global optimal solution providing certain conditions hold. Afterwards, the developments in Papers 1 to 3 are used to tackle a more challenging class of problems, namely, optimal control of switching systems. This class of problems is divided into problems with fixed mode sequence (Papers 4 and 5) and problems with free mode sequence (Papers 6 and 7). Each of these two classes is further divided into problems with autonomous subsystems (Papers 4 and 6) and problems with controlled subsystems (Papers 5 and 7). Different ADP-based algorithms are developed and proofs of convergence of the proposed iterative algorithms are presented. Moreover, an extension to the developments is provided for online learning of the optimal switching solution for problems with modeling uncertainty in Paper 8. Each of the theoretical developments is numerically analyzed using different real-world or benchmark problems"--Abstract, page v.


Handbook Of Learning And Approximate Dynamic Programming

Handbook of Learning and Approximate Dynamic Programming PDF Book Details:
Author: Jennie Si
Publisher: John Wiley & Sons
ISBN: 9780471660545
Size: 69.47 MB
Format: PDF, ePub, Mobi
Category : Technology & Engineering
Languages : un
Pages : 672
View: 7315

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Handbook Of Learning And Approximate Dynamic Programming PDF

by Jennie Si, Handbook Of Learning And Approximate Dynamic Programming Books available in PDF, EPUB, Mobi Format. Download Handbook Of Learning And Approximate Dynamic Programming books, A complete resource to Approximate Dynamic Programming (ADP), including on-line simulation code Provides a tutorial that readers can use to start implementing the learning algorithms provided in the book Includes ideas, directions, and recent results on current research issues and addresses applications where ADP has been successfully implemented The contributors are leading researchers in the field


Reinforcement Learning And Approximate Dynamic Programming For Feedback Control

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control PDF Book Details:
Author: Frank L. Lewis
Publisher: John Wiley & Sons
ISBN: 1118453972
Size: 60.52 MB
Format: PDF, Docs
Category : Technology & Engineering
Languages : un
Pages : 648
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Reinforcement Learning And Approximate Dynamic Programming For Feedback Control PDF

by Frank L. Lewis, Reinforcement Learning And Approximate Dynamic Programming For Feedback Control Books available in PDF, EPUB, Mobi Format. Download Reinforcement Learning And Approximate Dynamic Programming For Feedback Control books, Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.


Approximate Dynamic Programming

Approximate Dynamic Programming PDF Book Details:
Author: Dimitri P. Bertsekas
Publisher:
ISBN: 9781886529083
Size: 10.82 MB
Format: PDF, ePub
Category :
Languages : un
Pages :
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Approximate Dynamic Programming PDF

by Dimitri P. Bertsekas, Approximate Dynamic Programming Books available in PDF, EPUB, Mobi Format. Download Approximate Dynamic Programming books,


A Study On Architecture Algorithms And Applications Of Approximate Dynamic Programming Based Approach To Optimal Control

A Study on Architecture  Algorithms  and Applications of Approximate Dynamic Programming Based Approach to Optimal Control PDF Book Details:
Author: Jong Min Lee
Publisher:
ISBN:
Size: 20.79 MB
Format: PDF, ePub, Docs
Category : Dynamic programimng
Languages : un
Pages :
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A Study On Architecture Algorithms And Applications Of Approximate Dynamic Programming Based Approach To Optimal Control PDF

by Jong Min Lee, A Study On Architecture Algorithms And Applications Of Approximate Dynamic Programming Based Approach To Optimal Control Books available in PDF, EPUB, Mobi Format. Download A Study On Architecture Algorithms And Applications Of Approximate Dynamic Programming Based Approach To Optimal Control books, This thesis develops approximate dynamic programming (ADP) strategies suitable for process control problems aimed at overcoming the limitations of MPC, which are the potentially exorbitant on-line computational requirement and the inability to consider the future interplay between uncertainty and estimation in the optimal control calculation. The suggested approach solves the DP only for the state points visited by closed-loop simulations with judiciously chosen control policies. The approach helps us combat a well-known problem of the traditional DP called 'curse-of-dimensionality, ' while it allows the user to derive an improved control policy from the initial ones. The critical issue of the suggested method is a proper choice and design of function approximator. A local averager with a penalty term is proposed to guarantee a stably learned control policy as well as acceptable on-line performance. The thesis also demonstrates versatility of the proposed ADP strategy with difficult process control problems. First, a stochastic adaptive control problem is presented. In this application an ADP-based control policy shows an "active" probing property to reduce uncertainties, leading to a better control performance. The second example is a dual-mode controller, which is a supervisory scheme that actively prevents the progression of abnormal situations under a local controller at their onset. Finally, two ADP strategies for controlling nonlinear processes based on input-output data are suggested. They are model-based and model-free approaches, and have the advantage of conveniently incorporating the knowledge of identification data distribution into the control calculation with performance improvement.


Self Learning Optimal Control Of Nonlinear Systems

Self Learning Optimal Control of Nonlinear Systems PDF Book Details:
Author: Qinglai Wei
Publisher: Springer
ISBN: 981104080X
Size: 35.25 MB
Format: PDF, ePub, Docs
Category : Technology & Engineering
Languages : un
Pages : 230
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Self Learning Optimal Control Of Nonlinear Systems PDF

by Qinglai Wei, Self Learning Optimal Control Of Nonlinear Systems Books available in PDF, EPUB, Mobi Format. Download Self Learning Optimal Control Of Nonlinear Systems books, This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum. With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.


Optimal And Simulation Based Approximate Dynamic Programming Approaches For The Control Of Re Entrant Line Manufacturing Models

Optimal and Simulation based Approximate Dynamic Programming Approaches for the Control of Re entrant Line Manufacturing Models PDF Book Details:
Author: Jose A. Ramirez-Hernandez
Publisher:
ISBN:
Size: 16.19 MB
Format: PDF, Kindle
Category :
Languages : un
Pages : 210
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Optimal And Simulation Based Approximate Dynamic Programming Approaches For The Control Of Re Entrant Line Manufacturing Models PDF

by Jose A. Ramirez-Hernandez, Optimal And Simulation Based Approximate Dynamic Programming Approaches For The Control Of Re Entrant Line Manufacturing Models Books available in PDF, EPUB, Mobi Format. Download Optimal And Simulation Based Approximate Dynamic Programming Approaches For The Control Of Re Entrant Line Manufacturing Models books, This dissertation considers the application of simulation-based Approximate Dynamic Programming Approaches (ADP) for near-optimal control of Re-entrant Line Manufacturing (RLM) models. This study departs from the analysis of the optimal control problem under a discounted cost (DC) criterion in two simple RLM models with both job sequencing and job releasing control operations. Results on optimality conditions, structural properties of the optimal control policy, and sufficient conditions for optimality are provided. For the same models, four different simulation-based ADP approaches, namely, Q-Learning, Q-Learning with State Aggregation, SARSA(Lambda), and an Actor-Critic Architecture were utilized for control optimization. The ADP approaches studied include methods based on lookup tables and methods based on parametric approximations of the optimal cost function using temporal difference learning. Numerous simulation experiments were conducted to evaluate and compare the performance of the ADP methods employed against that of optimal solutions. Results indicate that the Actor-Critic approach consistently obtained a performance close to the optimal solutions while providing the best features for scalability in the state and action spaces which is essential for implementations of ADP in realistic RLM models. Upon these results, an extension of the Actor-Critic for larger RLM models is proposed under both a DC and average cost (AC) criterion. The formulation of the proposed approach is based on the representation of the RLM system as a model with an arbitrary number of single exponential servers and binary controls which can be seen as an abstraction of the simple RLM models previously studied. The proposed model is then amenable for the application of the uniformization procedure, which in turns allows for the derivation of optimality equations and conditions. These provide structural properties that also facilitate the definition and implementation of the control or actor in the proposed ADP algorithm. As an example, the so-called Intel Mini-Fab model was utilized in numerous simulation experiments on the optimization of job sequencing operations under an AC criterion. These experiments compared the performance of policies obtained with the proposed ADP against that of well known dispatching rules. Results from these experiments demonstrated the applicability of the proposed approach under different operational conditions, including different preventive maintenance schedules, random and deterministic processing times in the machines, and different load factors in the system. The results also demonstrate that, in general, the policies obtained with the proposed ADP approach provided good performance when compared to the dispatching rules considered. Moreover, the results show that under given operational conditions ADP-generated policies can even outperform the dispatching rules considered in the experiments. Finally, this dissertation also provides experimental results from the application of a simulation-based ADP approach for the optimization of preventive maintenance (PM) schedules in RLM models. The proposed approach utilizes an Actor-Critic architecture and the so-called post-decision state variable approach to define the actor in the ADP architecture. As an illustrative example, simulation experiments were conducted with the Intel Mini-Fab model. Results from these experiments demonstrated that ADP-generated PM policies were able to significatively reduce both the average work-in-process and the average cycle-time when compared to selected fixed PM policies.


Reinforcement Learning For Optimal Feedback Control

Reinforcement Learning for Optimal Feedback Control PDF Book Details:
Author: Rushikesh Kamalapurkar
Publisher: Springer
ISBN: 331978384X
Size: 38.66 MB
Format: PDF, Kindle
Category : Technology & Engineering
Languages : un
Pages : 293
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Reinforcement Learning For Optimal Feedback Control PDF

by Rushikesh Kamalapurkar, Reinforcement Learning For Optimal Feedback Control Books available in PDF, EPUB, Mobi Format. Download Reinforcement Learning For Optimal Feedback Control books, Reinforcement Learning for Optimal Feedback Control develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. In order to achieve learning under uncertainty, data-driven methods for identifying system models in real-time are also developed. The book illustrates the advantages gained from the use of a model and the use of previous experience in the form of recorded data through simulations and experiments. The book’s focus on deterministic systems allows for an in-depth Lyapunov-based analysis of the performance of the methods described during the learning phase and during execution. To yield an approximate optimal controller, the authors focus on theories and methods that fall under the umbrella of actor–critic methods for machine learning. They concentrate on establishing stability during the learning phase and the execution phase, and adaptive model-based and data-driven reinforcement learning, to assist readers in the learning process, which typically relies on instantaneous input-output measurements. This monograph provides academic researchers with backgrounds in diverse disciplines from aerospace engineering to computer science, who are interested in optimal reinforcement learning functional analysis and functional approximation theory, with a good introduction to the use of model-based methods. The thorough treatment of an advanced treatment to control will also interest practitioners working in the chemical-process and power-supply industry.