Optimal Control Fundamentals

In today's complex engineering and scientific landscapes, designing systems that operate at peak performance and efficiency is paramount. This course provides a foundational understanding of optimal control, enabling you to formulate and solve problems that seek to minimize cost or maximize performance in dynamic systems. What you'll learn: Understand the fundamental definitions and historical context of optimal control theory. Apply the Calculus of Variations to derive basic optimal control solutions. Master Pontryagin's Maximum Principle for determining optimal control laws in constrained systems. Explore Dynamic Programming and the Hamilton-Jacobi-Bellman equation for sequential decision-making. Analyze various types of optimal control problems, including those with terminal constraints. Grasp the relevance and application of optimal control in modern autonomous systems and artificial intelligence. The course begins with essential terminology and foundational concepts, then systematically builds expertise through core theoretical frameworks and practical problem-solving approaches. This course is designed for beginners in engineering, mathematics, computer science, and related fields who want to understand how to optimize system performance. No prior knowledge of optimal control is required. Begin your journey into the powerful field of optimal control and unlock new possibilities in system design.