Control theory is a dynamic field that merges applied mathematics, computer science, and engineering to design efficient automated systems. Driven by mathematical innovations and modern computing power, the discipline has evolved from classical linear theory to encompass complex nonlinear, intelligent, and interdisciplinary systems. This book aims to bridge the gap between rigorous theory and practical application, offering case studies and examples to illustrate the versatility of modern control methods. The volume covers fundamental concepts such as dynamical systems modeling, stability analysis using the Hurwitz criterion, and the design of PID and state-feedback controllers. It also explores contemporary applications, including robust fault-detection strategies for industrial motor drives and risk-assessment methodologies for cybersecurity in industrial control systems. The chapters in this book are the result of extensive research by experts from both academia and industry and present the authors' vision of how contemporary control strategies are dynamically reshaping engineering fields. Intended for graduate students, faculty, researchers, and practicing engineers, this book serves as a valuable resource for deepening understanding of control theory and exploring its modern implementations across diverse engineering sectors.