Optimization problems arise in many engineering discipline, from production process, manufacturing, and robotics. In this course, the students learn to formulate optimization problems and solve these through appropriate algorithms and software, e.g., Matlab. Typical problems include the Karush-Kuhn-Tucker (KKT) conditions and global/local conditions. Key optimization classes of problems including linear programming (LP), quadratic programming (QP) and nonlinear programming (NP). The course includes advanced control of dynamic systems with emphasis on Model Predictive Control (MPC). MPC can be used for UAVs collision avoidance and trajectory tracking, also for autonomous car.