£55.85

Model Predictive Control: Theory, Computation, and Design

Computer Aided Manufacture

Price data last checked 110 day(s) ago - refreshing...

View at Amazon

We'll watch every seller, every day. One email when your price arrives.

It has never been this cheap. We have no record of a lower price.

£56 today · cheaper than every other day in the last 18 months

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 423 days • 423 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 423 days • 1 price levels

Days at Price

Price Analysis

Most common price: £56 (423 days, 100.0%)

Price range: £56 - £56

Price levels: 1 different prices over 423 days

Description

In the eight years since the publication of the first edition, the field of model predictive control (MPC) has seen tremendous progress. First and foremost, the algorithms and high-level software available for solving challenging nonlinear optimal control problems have advanced significantly. For this reason, we have added a new chapter, Chapter 8, Numerical Optimal Control, and coauthor, Professor Moritz M. Diehl. This chapter gives an introduction into methods for the numerical solution of the MPC optimization problem. Numerical optimal control builds on two fields: simulation of differential equations, and numerical optimization. Simulation is often covered in undergraduate courses and is therefore only briefly reviewed. Optimization is treated in much more detail, covering topics such as derivative computations, Hessian approximations, and handling inequalities. Most importantly, the chapter presents some of the many ways that the specific structure of optimal control problems arising in MPC can be exploited algorithmically. We have also added a software release with the second edition of the text. The software enables the solution of all of the examples and exercises in the text requiring numerical calculation. The software is based on the freely available CasADi language, and a high-level set of Octave/MATLAB functions, MPCTools, to serve as an interface to CasADi. These tools have been tested in several MPC short courses to audiences composed of researchers and practitioners. The software can be downloaded from www.chemengr.ucsb.edu/~jbraw/mpc. In Chapter 2, we have added sections covering the following topics: • economic MPC • MPC with discrete actuators We also present a more recent form of suboptimal MPC that is provably robust as well as computationally tractable for online solution of nonconvex MPC problems. In Chapter 3, we have added a discussion of stochastic MPC, which has received considerable recent research attention. In Chapter 4, we have added a new treatment of state estimation with persistent, bounded process and measurement disturbances. We have also removed the discussion of particle filtering. There are two reasons for this removal; first, we wanted to maintain a manageable total length of the text; second, all of the available sampling strategies in particle filtering come up against the acurse of dimensionality, which renders the state estimates inaccurate for dimension higher than about five. The material on particle filtering remains available on the text website. In Chapter 6, we have added a new section for distributed MPC of nonlinear systems. In Chapter 7, we have added the software to compute the critical regions in explicit MPC. Throughout the text, we support the stronger KL-definition of asymptotic stability, in place of the classical definition used in the first edition.

Product Specifications

Format: paperback
ASIN: 0975937782
Category: Books > Subjects > Science, Nature & Maths > Engineering & Technology > Production, Manufacturing & Operational > Computer Aided Manufacture
Domain: Amazon UK
Release Date: 27 September 2024
Listed Since: 27 September 2024

Barcode

No barcode data available

Model Predictive Control: Theory, Computation, and Design

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Birkhauser Stochastic Networked Control Systems Book

Dissipative Systems Analysis and Control: Theory and Applications (Communications and Control Engineering)

Nonlinear Model Predictive Control: Theory and Algorithms (Communications and Control Engineering)

Mathematical Methods in Robust Control of Linear Stochastic Systems: 50 (Mathematical Concepts and Methods in Science and Engineering, 50)

Introduction to Modern Controls: with Illustrations in MATLAB and Python

Model Predictive Control: Classical, Robust and Stochastic (Advanced Textbooks in Control and Signal Processing)

Model Predictive Control: Classical, Robust and Stochastic (Advanced Textbooks in Control and Signal Processing)

Discrete-Time Markov Control Processes: Basic Optimality Criteria: 30 (Stochastic Modelling and Applied Probability, 30)

Control Theory of Infinite-Dimensional Systems: 277 (Operator Theory: Advances and Applications, 277)

Control Theory of Infinite-Dimensional Systems: 277 (Operator Theory: Advances and Applications, 277)

Stability of Dynamical Systems: On the Role of Monotonic and Non-Monotonic Lyapunov Functions (Systems & Control: Foundations & Applications)

Stochastic Processes, Estimation, and Control (Advances in Design and Control)

An Introduction to Optimal Control Theory: The Dynamic Programming Approach: 76 (Texts in Applied Mathematics, 76)

Linear Time Varying Systems and Sampled-data Systems: 265 (Lecture Notes in Control and Information Sciences, 265)

Time Optimal Control of Evolution Equations: 92 (Progress in Nonlinear Differential Equations and Their Applications, 92)

Introduction to Stochastic Control Theory (Volume 70) (Mathematics in Science and Engineering, Volume 70)

Recent Advances in Model Predictive Control: Theory, Algorithms, and Applications: 485 (Lecture Notes in Control and Information Sciences, 485)

Stability, Control and Differential Games: Proceedings of the International Conference “Stability, Control, Differential Games” (SCDG2019) (Lecture ... and Information Sciences - Proceedings)

Developments in Model-Based Optimization and Control: Distributed Control and Industrial Applications: 464 (Lecture Notes in Control and Information Sciences, 464)

Nonlinear System I: Proceedings of the 14th World Congress, International Federation of Automatic Control, Beijing, P.R. China, 5-9 July 1999 (IFAC ... Volumes) (IFAC Proceedings Volumes, Volume F)

Nonlinear Control and Filtering for Stochastic Networked Systems

Mathematical Control Theory for Stochastic Partial Differential Equations: 101 (Probability Theory and Stochastic Modelling, 101)

Modern Control Theory: State Variable Analysis of Linear Systems and Analysis of Nonlinear Systems

Carleman Estimates for Second Order Partial Differential Operators and Applications: A Unified Approach (SpringerBriefs in Mathematics)