Books

This book offers an introduction to the historical and philosophical dimensions of control systems. It provides an overview of key milestones in the development of control theory—from its early origins in antiquity to the major advances of the twentieth century. Alongside this historical account, the book presents philosophical perspectives that illuminate how foundational concepts in control theory have evolved. Drawing on insights from the philosophy of science and historical analysis, it also examines paradigm shifts within control systems engineering.

Designed for students and researchers interested in the intellectual roots of control systems, the book offers a fresh and contextualized view of the field’s progression. It focuses on conceptual understanding rather than mathematical detail, making it accessible to readers from both engineering and the history and philosophy of science. Given the scarcity of specialized literature in this interdisciplinary area, the references included here represent core resources for further study.

Model-based approaches to control systems design have long dominated the control systems design methodologies. However, most models require substantial prior or assumed information regarding the plant’s structure and internal dynamics. The data-driven paradigm in control systems design, which has proliferated rapidly in recent decades, requires only observed input-output data from plants, making it more flexible and broadly applicable.

An Introduction to Data-Driven Control Systems provides a foundational overview of data-driven control systems methodologies. It presents key concepts and theories in an accessible way, without the need for the complex mathematics typically associated with technical publications in the field, and raises the important issues involved in applying these approaches. The result is a highly readable introduction to what promises to become the dominant control systems design paradigm.

Control of multivariable industrial plants and processes has been a challenging and fascinating task for researchers in this field. The analysis and design methodologies for multivariable plants can be categorized as centralized and decentralized design strategies. Despite the remarkable theoretical achievements in centralized multiva- able control, decentralized control is still widely used in many industrial plants. This trend in the beginning of the third millennium is still there and it will be with us for the foreseeable future. This is mainly because of the easy implementation, main- nance, tuning, and robust behavior in the face of fault and model uncertainties, which is reported with the vast number of running decentralized controllers in the industry. The main steps involved in employing decentralized controllers can be summarized as follows: • Control objectives formulation and plant modeling. • Control structure selection. • Controller design. • Simulation or pilot plant experiments and Implementation. Nearly all the textbooks on multivariable control theory deal only with the control system analysis and design. The important concept of control structure selection which is a key prerequisite for a successful industrial control strategy is almost unnoticed. Structure selection involves the following two main steps: • Inputs and outputs selection. • Control configuration selection or the input-output pairing problem. This book focuses on control configuration selection or the input-output pairing problem, which is defined as the procedure of selecting the appropriate input and output pair for the design of SISO (or block) controllers.

Analysis and Design of Multivariable Control Systems

History of Control Engineering

Modern Control Engineering

Modern Control Systems

Advanced Engineering Mathematics

Signal and Systems

An Introduction to Research and Engineering Ethics

Digital Control Systems

Power Systems Stability and Control

Process Control Systems

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