Guest lecture: Hyeongjun Park - New Mexico State University, Las Cruces, USA Education Ph.D. Aerospace Engineering, University of Michigan, Ann Arbor, MI, USA 2014 Thesis: Real-time Predictive Control of Constrained Nonlinear Systems Using the IPA-SQP Approach M.S. Aerospace Engineering, Seoul National University, Korea 2008 Thesis: Development of a Prototype Nanosatellite, SNUBYUL-I B.S. Mechanical and Aerospace Engineering, Seoul National University, Korea 2003 Research Interests Development, numerical simulation, experimental ground testing, and in-orbit demonstration of guidance, navigation, and control (GN&C) approaches for robotic space systems 1. Dynamics, guidance, navigation, and control of orbiting robotic spacecraft missions - Obstacle avoidance maneuvers for spacecraft rendezvous and docking in on-orbit servicing, assembly, and active debris removal missions using multiple satellites - Precise attitude control of small satellites using reaction wheels and magnetorquers 2. Autonomy of space systems with robotic manipulation capability - Development of GN&C algorithms for robust and stable maneuvering - In-orbit assembly and space cargo-carrying using multiple spacecraft with robotic arms 3. Real-time trajectory optimization and control for re-entry/hypersonic vehicles - Development of robust guidance and control algorithms - Onboard real-time software development 4. Laboratory experimentation of prototyping onboard spacecraft software and hardware - Hardware-in-the-loop simulations using air-bearing test platforms - 3U and 6U CubeSat development and ground testing - Miniaturized electromagnetic docking mechanism design 5. Mission design, in-orbit demonstration, and experimentation (robotic space missions) - Space cargo carrying by robots in the International Space Station (NASA Astrobee Robots) - Distributed space telescope systems using multiple small satellites (VISORS, VTXO) - CubeSat rendezvous and docking (SAS-SAT)

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Introduction to nonlinear systems and optimal control theory and its mathematical foundations. Includes equilibrium finding, phase plane analysis, Lyapunov stability theorems, feedback linearization, Pontryagin’s maximum principle, necessary conditions and sufficient conditions for optimality, and optimal control problems in mechanical and aerospace engineering. Learning Goals: Outcome 1: Analyze the stability and performance properties of nonlinear systems and design nonlinear feedback control systems; Outcome 2: Use optimal control theory and numerical optimization methods to solve engineering problems; Outcome 3: Design and simulate nonlinear and optimal control systems for mechanical and aerospace engineering applications. Topic Covered: Phase plane analysis, Lyapunov stability theorems, feedback linearization, calculus of variations, Pontryagin’s maximum principle, necessary conditions and sufficient conditions for optimality, continuous-time optimal control problems, and numerical optimization methods. Recommended Texts and Materials [1] D. Kirk, Optimal Control Theory, An Introduction, Dover Publication, Inc. 1970 (required) [2] H. Khalil, Nonlinear Systems, 3rd Edition, Pearson, 2001

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P.D.2-2 - Giugno