Jong-Han Kim - Research Topics

Current

Mission effectiveness analysis and optimization for VTOL aircrafts

funded by Korea Research Institute for Defense Technology Planning and Advancement (2023-2029)

• Mathematical modeling of detections signals for various detection sensors against VTOL aircrafts

• Mission trajectory generation for optimal mission effectiveness and survivability of VTOL aircrafts

Aerial target classification using radar measurements

funded by LIG Nex1 (2023-2024)

• Aerial target dynamic simulation and radar signal modeling

• Deep learning based classifier design for aerial targets

Failure mode analysis for space launchers

funded by Hanwha Aerospace (2023-2024)

• Probabilistic analysis of trajectories of space launchers and scheduled debris

• Failure modes and effects analysis for space launchers

Real-time optimal guidance and control techniques for reusable launchers

funded by Korea Aerospace Research Institute (2023-2027)

• Embedded optimization solvers for real-time powered descent guidance problems

• Performance verification techniques for on-board powered descent guidance algorithms

Optimal orbit transfer and guidance for LEO satellites

funded by SATREC Initiative (2023-2025)

• Optimal low thrust orbit transfer for LEO satellites

• Optimal guidance for LEO satellites

Reentry guidance and control techniques for reusable unmanned space vehicles

funded by Korea Research Institute for Defense Technology Planning and Advancement (2022-2028)

• Optimal reentry guidance and trajectory planning for reusable unmanned space planes

• Precision flight control and control allocation for reusable unmanned space planes

Engagement simulation for close-in weapon systems

funded by LIG Nex1 (2022-2024)

• High fidelity simulation for close-in weapon systems and target anti-ship missiles

• Filtering and aiming algorithms for close-in weapon systems

Optimal mission assignment for multiple mobile robots

funded by Korea Research Institute for Defense Technology Planning and Advancement (2022-2026)

• Optimal mission assignment for mobile robots via mixed integer programming and convex programming on cloud computing environments

• Cloud computing based learning and inference techniques

Guidance, navigation, and control techniques for large divert soft landing of reusable launchers

funded by National Research Foundation of Korea (2022-2025)

• Embedded convex optimization based large divert soft landing techniques for reusable launchers

• Flight demonstration on a TVC controlled methane rocket

Future space exploration and in-situ resource utilization technology research center

funded by National Research Foundation of Korea (2022-2026)

• Precision space navigation and guidance techniques for space exploration

• In-situ water resource utilization for sustainable space exploration

Model based design for fault tolerant control of turbofan engines

funded by Agency for Defense Development (2022-2024)

• Model predictive control techniques for turbofan engines

• Model identification and fault detection techniques for turbofan engines

AI-based collision detection and avoidance algorithms for smart drones

funded by Moasoft (2021-2024)

• Detect and avoid algorithm based on deep learning and reinforcement learning

• Online trajectory design techniques based on artificial intelligence and optimization techniques

Optimal collision-free path planning for multiple vehicles

funded by Korea Aerospace Research Institute (2021-2024)

• Optimal cooperative path planning with collision avoidance

• Meta learning-based path planning via disciplined parametrized programming

Cooperative guidance for theatre missile defense systems

funded by Agency for Defense Development (2020-2026)

• Optimal cooperative guidance for team of interceptors

• Cooperative battle damage assessment and mission planning for team of interceptors

Artificial intelligence for guidance and control of missile systems

funded by Agency for Defense Development (2020-2025)

• Data-driven techniques for control systems analysis and synthesis

• Data-driven techniques for flight performance analysis and prediction

Past

Advanced pilot assistance systems based on deep reinforcement learning

funded by Korea Evaluation Institute of Industrial Technology (2018-2023)

• Collision avoidance techniques based on end-to-end deep reinforcement learning

• Validations on embedded GPUs and flight tests on fixed wing aircrafts

Optimal mission assignment for multiple UAVs

funded by Agency for Defense Development (2021-2022)

• Optimal UAV path planning via convex programming techniques

• Optimal multiple UAVs mission assignment via mixed integer programming

Parallel convex optimization for large-scale machine learning acceleration

funded by National Research Foundation of Korea (2019-2022)

• Developing efficient large-scale convex optimization solvers running on GPUs

• A variety of large-scale convex programming applications, including integrated guidance systems, compressed sensing, inverse problems, and so on.

Re-entry and landing for reusable launch vehicles

funded by Korea Aerospace Research Institute (2019-2021)

• Convex programming for optimal soft landing of reusable launch vehicles

• Actuator allocation via convex programming

Fault detection and reconfigurable flight control systems for passenger aerial vehicles

funded by Korea Aerospace Research Institute (2019-2021)

• Control allocation via online convex programming

• Fault detection and identification via deep neural networks

3D computer generated holography via convex programming

funded by Electronics and Telecommunications Research Institute (2019-2020)

• Computer generated holography by using convex programming with sharpness-enhancing objective functions

Synthetic aperture radar processing based on compressed sensing

funded by Agency for Defense Development (2018-2020)

• Radar imaging quality improvement via compressed sensing

• Large-scale convex programming research

Integrated guidance and control under state constraints

• Constrained integrated guidance and control problems cast as online convex programming

• Handles various constraints on guidance performance, seeker's tracking performance, flight quality, and so on

Machine learning based intelligent guidance techniques

• Online \(\ell_1\)-regularized optimization for optical misalignment cancellation of strap-down seekers.

• Target shape identification using RF signals based on unsupervised learning.

Integrated guidance and control for constrained precision homing

• Finite horizon integrated guidance and control for constrained terminal homing of high performance missile systems.

Guidance and control designs for full-scale missile development programs

• Highly reliable guidance and control design/implementation for several state-of-the-art missile systems development programs.

• The works include classical, optimal, or robust control for highly unstable airframes and high-fidelity flight simulation techniques.

Optimal decentralized control for large-scale networked systems

• Theoretical studies on optimal decentralized control using convex analysis and convex optimization.

• Characterizes convex problems and explicitly solvable problems in optimal control of networked systems under information constraints.

Decentralized control for jet engine systems

• Suboptimal decentralized \(H_2/H_\infty\) control synthesis.

• Convex relaxation and convex approximation of nonconvex optimal control problems.

• Application to jet engine control systems.

Multiscale/stochastic consensus for decentralized estimation

• Multiscale concepts to applied to consensus problems, for scalable distributed estimation.

• Stochastic message passing for convergence acceleration. Application to decentralized estimation problems.

Tactical missile systems integration

• Mission profile design, operational performance/effectiveness analysis.

• Flight performance analysis.

• Engineering level 6-DOF flight dynamics simulation.

Attitude control for small satellites

• Design and experiments for attitude control of flexible satellites.

• Ground test modules development.

Co-evolutionary algorithms for constrained optimization

• Constrained optimization, minimax optimization using evolutionary computation.

• Applications to design problems or control problems.

• Convergence acceleration by using artificial neural network