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"This versatile book teaches control system design using H∞infty techniques that are simple and compatible with classical control, yet powerful enough to quickly allow the solution of physically meaningful problems. The authors begin by teaching how to formulate control system design problems as mathematical optimization problems and then discuss the theory and numerics for these optimization problems. Their approach is simple and direct, and since the book is modular, the parts on theory can be read independently of the design parts and vice versa, allowing readers to enjoy the book on many levels.The development of H∞infty engineering was one of the main accomplishments of control in the 1980s. However, until now, there has not been a publication suitable for teaching the topic at the undergraduate level. This book fills that gap by teaching control system design using H∞infty techniques at a level within reach of the typical engineering and mathematics student. It also contains a readable account of recent developments and mathematical connections.The authors treat control design problems in a physically correct way. They present a small set of specific rules that the reader can apply to convert a particular design problem to the fundamental optimization problem of H∞infty control. This precisely formulated mathematics problem can then be solved on a computer. The book introduces the control software package OPTDesign, which allows the reader to easily reproduce the calculations done in the solved examples and even try variations on them. The description of how to convert an engineering problem to a form suitable for CAD is simpler than in other books."

"One of the main accomplishments of control in the 1980s was the development of H∞ techniques. This book teaches control system design using H∞ methods. Students will find this book easy to use because it is conceptually simple. They will find it useful because of the widespread appeal of classical frequency domain methods.Classical control has always been presented as trial and error applied to specific cases; Helton and Merino provide a much more precise approach. This has the tremendous advantage of converting an engineering problem to one that can be put directly into a mathematical optimization package.After completing this course, students will be familiar with how engineering specs are coded as precise mathematical constraints."

"H∞ control originated from an effort to codify classical control methods, where one shapes frequency response functions for linear systems to meet certain objectives. H∞ control underwent tremendous development in the 1980s and made considerable strides toward systematizing classical control. This book addresses the next major issue of how this extends to nonlinear systems.At the core of nonlinear control theory lie two partial differential equations (PDEs). One is a first-order evolution equation called the information state equation, which constitutes the dynamics of the controller. One can view this equation as a nonlinear dynamical system. Much of this volume is concerned with basic properties of this system, such as the nature of trajectories, stability, and, most important, how it leads to a general solution of the nonlinear H∞ control problem.The second PDE actually builds on a classical type of partial differential inequality (PDI) called a Bellman-Isaacs inequality. While the information state PDE determines the dynamics of the controller, the PDI determines the output of the controller. The authors explore the system theoretic significance of the PDI and present its gross structure. These equations are only a few years old and their study is an expanding area of research.This book also emphasizes the theory effecting computer solvability of the information state equation, which at the outset looks numerically intractable, but which surprisingly is in many cases tractable. For example, the theory shows that careful initialization has a major influence on computer solvability.The authors keep the book self-contained by using the appendices to help explain certain prerequisite material. The reader should have a basic knowledge of control theory, real analysis and differential equations, nonlinear operator theory, and nonlinear PDEs."

"This monograph presents a unified mathematical framework for a wide range of problems in estimation and control. The authors discuss the two most commonly used methodologies: the stochastic H2 approach and the deterministic (worst-case) H� approach. Despite the fundamental differences in the philosophies of these two approaches, the authors have discovered that, if indefinite metric spaces are considered, they can be treated in the same way and are essentially the same."

"Turbo expander TE dan Model Predictive Control MPC diusulkan untuk digunakan pada unit depropanizer untuk meningkatkan recovery propana dan memperbaiki kinerja pengendalian di unit tersebut. Model yang digunakan dalam MPC adalah model first-order plus dead time FOPDT, yang diuji kinerja pengendaliannya menggunakan pengujian perubahan set point SP dan gangguan, dengan ukuran kinerjanya menggunakan integral of absolute error IAE. Hasilnya menunjukkan bahwa penggunaan TE pada depropanizer mampu meningkatkan recovery propana sebesar 8,44 dari 82,11 menjadi 90,55. Sedangkan untuk struktur pengendalian, digunakan pengendalian tekanan pada TE menggunakan pengendali proportional-integral, PI, pengendalian komposisi propana pada aliran distilat menggunakan MPC dan pengendalian tekanan kolom depropanizer menggunakan MPC. Setelah melakukan pengujian perubahan SP didapatkan bahwa kinerja pengendali MPC pada pengendali komposisi dan pengendali tekanan depropanizer dapat memperbaiki kinerja pengendali PI sebesar 1,62 dan 93,40. Sedangkan pada pengujian terjadinya gangguan didapatkan bahwa kinerja pengenali MPC pada pengendali komposisi dan pengendali tekanan depropanizer dapat memperbaiki kinerja pengendali PI sebesar 60,54 dan 6-,21 sehingga pengendali MPC lebih baik dibandingkan pengendali PI untuk digunakan pada pengendali komposisi dan pengendali tekanan pada depropanizer yang menggunakan Turbo Expander.

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Turbo expander TE and Model Predictive Control MPC is suggested for depropanizer unit to increase propane recovery and improve control performance of the unit. The model used in the MPC is first order plus dead time FOPDT, which tested the performance of the control using set point and disturbance change test with measurement of the performance using integral of absolute error IAE. As a result, use of TE in the depropanizer able to increase recovery of propane of 8,44 from 82.11 to 90.55. As for the control structure, pressure control is use on the TE using proportional integral control, composition control in the distillate flow using MPC, and pressure control in depropanizer column using MPC.

After doing SP changed test, the result showed performance of MPC controller at composition control and pressure control in depropanizer can improve performance compared by PI controller of 1.62 and 93.40. and then for disturbance rejection test, the result showed the MPC controller perfromance can improve PI controller performance at composition control and pressure control in depropanizer is able to improve PI controller performance by 60.54 and 60.21. So that, MPC controller is better than PI controller if it use at composition controller and pressure controller in depropanizer unit with Turbo Expander."