APMTH 158 - Introduction to Optimal Control and Estimation Learning Course

[APMTH 158 - Introduction to Optimal Control and Estimation Learning Course] Introduction to Optimal Control and Estimation (APMTH 158) provides a comprehensive overview of optimal control theory and estimation techniques used in engineering, economics, and related fields. The course covers fundamental concepts such as dynamic optimization, control strategies, and state estimation. Students will learn about the principles of optimal control, including the calculus of variations, Pontryagin’s maximum principle, and dynamic programming. Estimation methods such as Kalman filters and Bayesian approaches are also explored, with a focus on their application in real-world scenarios like autonomous systems and signal processing. Through theoretical insights and practical problem-solving exercises, students will gain the skills needed to design and implement control systems and estimation algorithms that optimize performance and accuracy in complex dynamic environments. This Learning Course is a platform that helps students to study and learn. The platform provides all the required material for the students to study. The material includes Study guide, Exam Questions & Answers, Study Notes and other resources that are useful for the students. It also gives information about the upcoming exams so that students can prepare themselves accordingly.