Showing results for "Nonlinear Model Based Process Control Rashid M Ansari German"

Nonlinear Model-Based Control: Using First-Principles Models in Process ControlFirst-principles models (engineering models) are used in industry for process design, troubleshooting, training, online analysis and supervisory optimization. The author's vision is to use them for control.Why? They effectively handle nonlinearity, nonstationary behavior and interacting variables with just one tuning coefficient per controlled variable (CV). Using optimi...

This book presents recent theoretical findings on Sliding Mode Control (SMC) issues for various classes of complex nonlinear systems based on Takagi-Sugeno (T-S) fuzzy models. Research results and controller design methods on SMC of complex nonlinear systems through T-S fuzzy models are presented and show how the methods can be used in various practical systems, such as control of nonlinear gas absorption, water stream heating, and air-drying process in some chemical production systems.

This book introduces nonlinear control systems for control engineering and science to graduate, undergraduate students and researchers; it targets control engineering students who do not like to do not have time to derive and prove mathematical results for nonlinear control systems. It can be serve as a text book for nonlinear control systems, especially for feedback linearization techniques which is a common approach in controlling nonlinear systems. The development of computer software f...

This book provides a systematic and in-depth introduction to distributed optimal adaptive cooperative control for multiagent systems from a theoretical perspective. The major research topics include: adaptive neural networks-based control schemes under multiconstraints, adaptive optimal control, event-triggered adaptive optimal control and data-based reinforcement learning control. The comprehensive and systematic treatment of adaptive optimal control in multiagent systems is one of the ma...

This book provides scalable, effective and real-world-compatible methods and algorithms for the control and extended estimation of uncertain nonlinear systems against a backdrop of often-unconventional problems. The author provides advice on choosing which solution is most relevant to the desired control objectives, the nature of present uncertainties and the impact on closed-loop performance.The book introduces its key paradigms step by step and then presents the family of candida...

This book proposes an integrated design method for intelligent adaptive controllers to overcome the negative effects of various constraints on nonlinear systems and nonlinear multiagent systems in practical applications. The book rigorously provides problem analysis, controller design, and stability theory. In addition, numerous simulation examples are given to demonstrate the validity of the corresponding intelligent control methods, and the simulation results are illustrated in detail wi...

Nonlinear Process Modeling in Chemical and Particle Systems delivers a comprehensive guide to the analysis and application of nonlinear models in chemical engineering. Addressing the growing demand for simulation-driven design, process optimization, and sustainable innovation, the book integrates nonlinear ordinary and partial differential equations with real-world chemical and particle system applications. Readers are introduced to fundamental principles of nonlinear transport, reaction k...

This book aims to develop systematic design methodologies to model-based nonlinear control of aeroengines, focusing on (1) modelling of aeroengine systems—both component-level and identification-based models will be extensively studied and compared; and (2) advanced nonlinear control designs—set-point control, transient control and limit-protection control approaches will all be investigated. The model-based design has been one of the pivotal technologies to advanced control and health man...

A systematic computer-aided approach provides a versatile setting for the control engineer to overcome the complications of controller design for highly nonlinear systems. Computer-aided Nonlinear Control System Design provides such an approach based on the use of describing functions. The text deals with a large class of nonlinear systems without restrictions on the system order, the number of inputs and/or outputs or the number, type or arrangement of nonlinear terms. The strongly softwa...

Written and edited by a team of experts in the field, this exciting new volume presents the cutting-edge techniques, latest trends, and state-of-the-art practical applications in linear and nonlinear system modeling.Mathematical modeling of control systems is, essentially, extracting the essence of practical problems into systematic mathematical language. In system modeling, mathematical expression deals with modeling and its applications. It is characterized that ...

Formal methods is a field of computer science that emphasizes the use of rigorous mathematical techniques for verification and design of hardware and software systems. Analysis and design of nonlinear control design plays an important role across many disciplines of engineering and applied sciences, ranging from the control of an aircraft engine to the design of genetic circuits in synthetic biology.While linear control is a well-established subject, analysis and design of nonlinea...

This book provides an overview of the nonlinear model predictive control (NMPC) concept for application to innovative combustion engines. Readers can use this book to become more expert in advanced combustion engine control and to develop and implement their own NMPC algorithms to solve challenging control tasks in the field. The significance of the advantages and relevancy for practice is demonstrated by real-world engine and vehicle application examples.The author provides an ove...