People at the LACIS perform research on the general area of systems and control with focus areas including i) adaptive and robust control of safety-critical systems, ii) distributed estimation and control of networked multiagent systems, and iii) resilient and secure robotics, autonomous vehicles, human-in-the-loop systems, cyber-physical systems; and large-scale modular systems. In particular, our research is motivated by the challenges relevant to academia, government, and industry and directed towards many significant emerging applications that like at the heart of science and engineering. The governing characteristics of our research are rigorous theoretical treatment combined with breadth of applicability to real world problems. For example, we have emphasized, where possible, both numerical high-fidelity simulation and experimental validation of the new theoretical discoveries we have developed. The theoretical results that we developed to date have been implemented to identify and control robotic systems, aerospace systems, mechanical systems, electrical systems, and automation systems. We strongly believe that theoretical study and experimentation provide guidelines for each other and are indispensable ingredients in new real-world technologies.
Since LACIS is an interdisciplinary research laboratory, the LACIS Director Dr. Tansel Yucelen and his students often collaborate with researchers and professionals around the globe including but not limited to the people from Air Force Research Laboratory, Army Research Laboratory, Bilkent University, Colorado School of Mines, ControlX, Delft University of Technology, Embry-Riddle Aeronautical University, Georgia Institute of Technology, Gulfstream Aerospace Corporation, Istanbul Technical University, Lockheed Martin, Massachusetts Institute of Technology, Missouri University of Science and Technology, NASA, NodeIn, Oak Ridge National Laboratory, Southern Illinois University, Technical University of Munich, Textron Aviation, Tokyo Institute of Technology, University of Alabama, University of Arizona, University of Illinois at Urbana Champaign, University of Kansas, University of South Florida, University of Texas at Arlington, University of Perugia, West Virginia University, Wichita State University, and Worcester Polytechnic Institute (alphabetical).
Detailed Research Areas
Theory: Adaptive control; Computational methods; Constrained control; Convex optimization; Cooperative control; Decentralized control; Delay systems; Distributed control; Disturbance rejection; Estimation; Finite-time control; Fixed-architecture controller synthesis; Fuzzy control; Game theory; H2/Hoo control; Hybrid systems; Linear matrix inequalities; Linear systems; Learning; Modeling; Multiobjective control synthesis; Networked control systems; Neural networks; Nonlinear systems; Optimal control; Performance analysis; Resilient (nonfragile) control; Robust control; Robustness analysis; Saturation (amplitude, rate, quantization) control; Stability analysis; Time-varying systems; Uncertain systems (alphabetical).
Application: Active noise control; Active vibration control; Aerospace systems; Automation; Autonomy; Autonomous vehicles; Complex systems; Cyber-physical systems; Electrical systems; Flexible structures; Flight control systems and autopilots; Human-in-the-loop systems; Human-machine interaction; Interconnected systems; Isolation technology; Large-scale systems; Mechanical systems; Mechanical systems; Modular systems; Multiagent networks; Power systems; Real-time systems; Robotics; Sensor networks; Smart structure control; Unmanned systems (alphabetical).
Distributed 2D/3D Formation Control for Cooperative Engagement under Constraints and Uncertainty (Air Force Research Laboratory, 2022-2023).
Developing Embedded Distributed Electric Propulsion Control System for Electric Vertical Takeoff and Landing (eVTOL) / Urban Air Mobility (UAM) Vehicles (Air Force Research Laboratory SBIR Phase II through ControlX, 2021-2023).
Developing Embedded Distributed Electric Propulsion Control System for Electric Vertical Takeoff and Landing (eVTOL) / Urban Air Mobility (UAM) Vehicles (Air Force Research Laboratory SBIR Phase I through OptoXense, 2020-2021).
Cooperative Estimation and Control for Autonomous Unmanned Aerial Vehicles (Air Force Research Laboratory, 2019-2022).
Distributed Intelligent Robust Control Technologies (Air Force Research Laboratory SBIR Phase II through OptoXense, 2019-2021).
Distributed Intelligent Robust Control Technologies (Air Force Research Laboratory SBIR Phase I through OptoXense, 2018-2019).
Graduate Student Travel Support Request for the IFAC Conference on Cyber-Physical & Human Systems (National Science Foundation, 2018-2019).
Optimal Adaptive Control Architecture Development for TBCC Engines Integrated with MIPCC Systems (Defense Advanced Research Projects Agency SBIR Phase II through OptoXense and ControlX, 2018-2023).
Verification and Validation of Adaptive Hypersonic Vehicle Control Algorithms (Air Force Research Laboratory, 2017-2019).
Multiagent Coordination over Prescribed Time Intervals: System-Theoretic Foundations and Distributed Control (Army Research Office, 2017-2018).
Developing an Adaptive TVC System for High-G Propulsion Control in Missile Interceptors (Missile Defense Agency SBIR Phase I through OptoXense, 2017-2018).
Optimal Adaptive Control Architecture Development for TBCC Engines Integrated with MIPCC Systems (Defense Advanced Research Projects Agency SBIR Phase I through OptoXense, 2017-2018).
System-Theoretic Principles and Decentralized Sensor Network and Control Algorithms for Dynamic Data-Driven Situational Awareness and Response (Air Force Office of Scientific Research, 2017-2018).
Collaborative Research: Resilient Decentralized Estimation and Control for Cooperative Rigid Body Multivehicle Systems (National Science Foundation, 2016-2019).
Control Systems Webinars: Reaching Broader Control Systems Community Around the Globe (IEEE Control Systems Society, 2016-2017).
Learning Algorithms for Preserving Safe Flight Envelope under Adverse Aircraft Conditions (National Aeronautics and Space Administration, 2015-2018).
Active Wing Shaping Control for Morphing Aircraft (National Aeronautics and Space Administration, 2015-2018).
Autonomous Multivehicle Systems for Real-Time Situational Awareness in Adverse Environments (Oak Ridge Associated Universities Ralph E. Powe Junior Faculty Enhancement Award, 2015-2016).
Verification and Validation of Adaptive Systems for Hypersonic Vehicles (Air Force Research Laboratory, 2015-2015).
Adaptive Hypersonic Vehicle Control for Robust and Certifiable Performance (Air Force Research Laboratory, 2014-2014).
Resilient Multiagent Control in Adverse Environments (University of Missouri Research Board, 2014-2016).
Research Grants and Contracts
With the studies we have initiated, our research grants and contracts total $3.4M. Based on our solid theoretical and research background and accomplishments, we will continue to productively perform high-quality scholarly research, mentor undergraduate and graduate students, fund research expenditures, and share the created knowledge in top internationally-recognized journals and conferences. In addition to our research areas listed above, we also have a great passion and excitement to explore new and novel research directions and application areas to continuously expand ourselves.
Follow us on Twitter for recently received research grants and contracts!
B. Sarsilmaz, T. Yucelen, and T. Oswald, “Distributed control of multiagent systems with heterogeneity in synchronization roles,” United States Patent 11,562,269 (2023).
D. Tran, T. Yucelen, and B. Sarsilmaz, “Distributed process state and input estimation for heterogeneous active/passive sensor networks,” United States Patent 11,402,243 (2022).
B. Sarsilmaz and T. Yucelen, “Control of multiagent systems with local and global objectives,” United States Patent 11,129,236 (2021).
K. M. Dogan, B. C. Gruenwald, T. Yucelen, and J. A. Muse, “An adaptive architecture for controlling uncertain systems with unmodeled dynamics,” United States Patent 11,106,183 (2021).
B. C. Gruenwald, T. Yucelen, K. M. Dogan, and J. A. Muse, “An adaptive control mechanism for uncertain systems with actuator dynamics,” United States Patent 11,079,737 (2021).
B. Sarsilmaz and T. Yucelen, “A distributed control mechanism for heterogeneous multiagent systems with unknown leaders,” United States Patent 10,983,532 (2021).
T. Yucelen and D. Tran, “Tools and methods for distributed spatial control of swarms via multiplex information networks,” United States Patent 10,645,156 (2020).
T. Yucelen, Y. Yildiz, and R. Sipahi, “Systems and methods for computing stability limits of human-in-the-loop adaptive control architectures,” United States Patent 10,618,525 (2020).
T. Yucelen, K. Kim, and A. J. Calise, “Systems and methods for derivative-free output feedback adaptive control,” United States Patent 8,996,195 (2015).
K. Kim, T. Yucelen, and A. J. Calise, “Systems and methods for parameter dependent Riccati equation approaches to adaptive control,” United States Patent 9,058,028 (2015).