Author: Edoardo Mosca
Publisher: Pearson Education
ISBN:
Category : Mathematics
Languages : en
Pages : 504
Book Description
Using a common unifying framework, this volume explores the main topics of Linear Quadratic control, predictive control, and adaptive predictive control -- in terms of theoretical foundations, analysis and design methodologies, and application-orient ed tools.Presents LQ and LQG control via two alternative approaches: the Dynamic Programming (DP) and the Polynomial Equation (PE) approach. Discusses predicable control, an important tool in industrial applications, within the framework of LQ control, and presents innovative predictive control schemes having guaranteed stability properties. Offers a unique, thorough presentation of indirect adaptive multi-step predictive controllers, with detailed proofs of globally convergent schemes for both the ideal and the bounded disturbance case. Extends the self-tuning property of one-step-ahead control to multi-step control.For engineers and mathematicians interested in the theory, analysis and design methodologies, and application-oriented tools of optimal, predictive and adaptive control.
Optimal, Predictive, and Adaptive Control
Author: Edoardo Mosca
Publisher: Pearson Education
ISBN:
Category : Mathematics
Languages : en
Pages : 504
Book Description
Using a common unifying framework, this volume explores the main topics of Linear Quadratic control, predictive control, and adaptive predictive control -- in terms of theoretical foundations, analysis and design methodologies, and application-orient ed tools.Presents LQ and LQG control via two alternative approaches: the Dynamic Programming (DP) and the Polynomial Equation (PE) approach. Discusses predicable control, an important tool in industrial applications, within the framework of LQ control, and presents innovative predictive control schemes having guaranteed stability properties. Offers a unique, thorough presentation of indirect adaptive multi-step predictive controllers, with detailed proofs of globally convergent schemes for both the ideal and the bounded disturbance case. Extends the self-tuning property of one-step-ahead control to multi-step control.For engineers and mathematicians interested in the theory, analysis and design methodologies, and application-oriented tools of optimal, predictive and adaptive control.
Publisher: Pearson Education
ISBN:
Category : Mathematics
Languages : en
Pages : 504
Book Description
Using a common unifying framework, this volume explores the main topics of Linear Quadratic control, predictive control, and adaptive predictive control -- in terms of theoretical foundations, analysis and design methodologies, and application-orient ed tools.Presents LQ and LQG control via two alternative approaches: the Dynamic Programming (DP) and the Polynomial Equation (PE) approach. Discusses predicable control, an important tool in industrial applications, within the framework of LQ control, and presents innovative predictive control schemes having guaranteed stability properties. Offers a unique, thorough presentation of indirect adaptive multi-step predictive controllers, with detailed proofs of globally convergent schemes for both the ideal and the bounded disturbance case. Extends the self-tuning property of one-step-ahead control to multi-step control.For engineers and mathematicians interested in the theory, analysis and design methodologies, and application-oriented tools of optimal, predictive and adaptive control.
Adaptive Prediction and Predictive Control
Author: Partha Pratim Kanjilal
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 518
Book Description
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 518
Book Description
Robust Adaptive Model Predictive Control of Nonlinear Systems
Author: Darryl DeHaan
Publisher:
ISBN:
Category : Technology
Languages : en
Pages :
Book Description
Robust Adaptive Model Predictive Control of Nonlinear Systems.
Publisher:
ISBN:
Category : Technology
Languages : en
Pages :
Book Description
Robust Adaptive Model Predictive Control of Nonlinear Systems.
Robust and Adaptive Model Predictive Control of Non-linear Systems
Author: Martin Guay
Publisher:
ISBN: 9781523101047
Category : TECHNOLOGY & ENGINEERING
Languages : en
Pages : 252
Book Description
The following topics are dealt with: adaptive control; constrained nonlinear systems; disturbance attenuation; robust adaptive economic MPC; and discrete-time systems.
Publisher:
ISBN: 9781523101047
Category : TECHNOLOGY & ENGINEERING
Languages : en
Pages : 252
Book Description
The following topics are dealt with: adaptive control; constrained nonlinear systems; disturbance attenuation; robust adaptive economic MPC; and discrete-time systems.
Adaptive Predictive Control
Author: Abdel-Latif Elshafei
Publisher:
ISBN:
Category :
Languages : en
Pages : 304
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 304
Book Description
Applied Predictive Control
Author: Sunan Huang
Publisher: Springer Science & Business Media
ISBN: 1447137256
Category : Mathematics
Languages : en
Pages : 276
Book Description
This focused treatment includes the fundamentals and some state-of-the-art developments in the field of predictive control. A substantial part of the book addresses application issues in predictive control, providing several interesting case studies for more application-oriented readers.
Publisher: Springer Science & Business Media
ISBN: 1447137256
Category : Mathematics
Languages : en
Pages : 276
Book Description
This focused treatment includes the fundamentals and some state-of-the-art developments in the field of predictive control. A substantial part of the book addresses application issues in predictive control, providing several interesting case studies for more application-oriented readers.
Model Predictive Control in the Process Industry
Author: Eduardo F. Camacho
Publisher: Springer Science & Business Media
ISBN: 1447130081
Category : Technology & Engineering
Languages : en
Pages : 250
Book Description
Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.
Publisher: Springer Science & Business Media
ISBN: 1447130081
Category : Technology & Engineering
Languages : en
Pages : 250
Book Description
Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.
Robust and Adaptive Model Predictive Control of Nonlinear Systems
Author: Martin Guay
Publisher: IET
ISBN: 1849195528
Category : Technology & Engineering
Languages : en
Pages : 269
Book Description
This book offers a novel approach to adaptive control and provides a sound theoretical background to designing robust adaptive control systems with guaranteed transient performance. It focuses on the more typical role of adaptation as a means of coping with uncertainties in the system model.
Publisher: IET
ISBN: 1849195528
Category : Technology & Engineering
Languages : en
Pages : 269
Book Description
This book offers a novel approach to adaptive control and provides a sound theoretical background to designing robust adaptive control systems with guaranteed transient performance. It focuses on the more typical role of adaptation as a means of coping with uncertainties in the system model.
Learning-based Model Predictive Control with closed-loop guarantees
Author: Raffaele Soloperto
Publisher: Logos Verlag Berlin GmbH
ISBN: 383255744X
Category :
Languages : en
Pages : 172
Book Description
The performance of model predictive control (MPC) largely depends on the accuracy of the prediction model and of the constraints the system is subject to. However, obtaining an accurate knowledge of these elements might be expensive in terms of money and resources, if at all possible. In this thesis, we develop novel learning-based MPC frameworks that actively incentivize learning of the underlying system dynamics and of the constraints, while ensuring recursive feasibility, constraint satisfaction, and performance bounds for the closed-loop. In the first part, we focus on the case of inaccurate models, and analyze learning-based MPC schemes that include, in addition to the primary cost, a learning cost that aims at generating informative data by inducing excitation in the system. In particular, we first propose a nonlinear MPC framework that ensures desired performance bounds for the resulting closed-loop, and then we focus on linear systems subject to uncertain parameters and noisy output measurements. In order to ensure that the desired learning phase occurs in closed-loop operations, we then propose an MPC framework that is able to guarantee closed-loop learning of the controlled system. In the last part of the thesis, we investigate the scenario where the system is known but evolves in a partially unknown environment. In such a setup, we focus on a learning-based MPC scheme that incentivizes safe exploration if and only if this might yield to a performance improvement.
Publisher: Logos Verlag Berlin GmbH
ISBN: 383255744X
Category :
Languages : en
Pages : 172
Book Description
The performance of model predictive control (MPC) largely depends on the accuracy of the prediction model and of the constraints the system is subject to. However, obtaining an accurate knowledge of these elements might be expensive in terms of money and resources, if at all possible. In this thesis, we develop novel learning-based MPC frameworks that actively incentivize learning of the underlying system dynamics and of the constraints, while ensuring recursive feasibility, constraint satisfaction, and performance bounds for the closed-loop. In the first part, we focus on the case of inaccurate models, and analyze learning-based MPC schemes that include, in addition to the primary cost, a learning cost that aims at generating informative data by inducing excitation in the system. In particular, we first propose a nonlinear MPC framework that ensures desired performance bounds for the resulting closed-loop, and then we focus on linear systems subject to uncertain parameters and noisy output measurements. In order to ensure that the desired learning phase occurs in closed-loop operations, we then propose an MPC framework that is able to guarantee closed-loop learning of the controlled system. In the last part of the thesis, we investigate the scenario where the system is known but evolves in a partially unknown environment. In such a setup, we focus on a learning-based MPC scheme that incentivizes safe exploration if and only if this might yield to a performance improvement.
Model Predictive Control - Theory and Applications
Author: Constantin Voloşencu
Publisher: BoD – Books on Demand
ISBN: 1803559888
Category : Science
Languages : en
Pages : 152
Book Description
The book presents some recent specialized theoretical and practical works in the field of process control based on the model predictive control (MPC) method. It includes seven chapters that present studies on the application of MPC in various technical processes, such as the atmospheric plasma spray process, permanent magnet synchronous motors, monitoring of the pose of a walking person, monitoring of the heat treatment process of raw materials, discrete event processes, control of passenger vehicles, and natural gas sweetening processes. Chapters include examples and case studies from researchers in the field. This volume provides readers with new solutions and answers to questions related to the emerging applications of MPC and their implementation.
Publisher: BoD – Books on Demand
ISBN: 1803559888
Category : Science
Languages : en
Pages : 152
Book Description
The book presents some recent specialized theoretical and practical works in the field of process control based on the model predictive control (MPC) method. It includes seven chapters that present studies on the application of MPC in various technical processes, such as the atmospheric plasma spray process, permanent magnet synchronous motors, monitoring of the pose of a walking person, monitoring of the heat treatment process of raw materials, discrete event processes, control of passenger vehicles, and natural gas sweetening processes. Chapters include examples and case studies from researchers in the field. This volume provides readers with new solutions and answers to questions related to the emerging applications of MPC and their implementation.