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Bio
My main area of research is the development of theory and methods for model predictive control (MPC) to handle nonlinearities and uncertainties in a systematic fashion. MPC is the most widely implemented advanced control technique in industry, because it deals with constraints, nonlinearities and uncertainties in a systematic and optimal manner. In MPC, a sequence of optimal control and estimation problems need to be solved in real-time – this requires orders of magnitude more computational resources than most other control methods. My interest is in the development of novel structure-exploiting numerical optimization methods and computer architectures for solving nonlinear optimal control and estimation problems with uncertainties in real-time. This allows engineers to solve new problems that are beyond the reach of current methods and computers.
I am also interested in developing new multi-objective optimization methods for the co-design of the overall closed-loop system. If one includes the parameters of the computer and physical system as part of the design variables, then it is possible to achieve significantly better performance than by just concentrating on the controller design. Mathematical optimization allows one to take a systematic approach to co-design in order to reduce design time and cost. I am therefore also interested in the development of novel multi-objective optimization methods for exploring how the parameters of an optimization-based control algorithm, computer architecture and physical design need to be traded off to satisfy performance specifications.
I have a joint appointment in the Department of Electrical & Electronic Engineering and the Department of Aeronautics. My theoretical research is therefore motivated by a wide variety of problems in the design of aerospace, renewable energy and information systems. Applications include scheduling of computation and communication in aerial and mobile robotic networks, aerodynamic drag reduction over aerofoils, gust and load alleviation in wind turbine blades and space launch and re-entry vehicles.
I am also interested in developing new multi-objective optimization methods for the co-design of the overall closed-loop system. If one includes the parameters of the computer and physical system as part of the design variables, then it is possible to achieve significantly better performance than by just concentrating on the controller design. Mathematical optimization allows one to take a systematic approach to co-design in order to reduce design time and cost. I am therefore also interested in the development of novel multi-objective optimization methods for exploring how the parameters of an optimization-based control algorithm, computer architecture and physical design need to be traded off to satisfy performance specifications.
I have a joint appointment in the Department of Electrical & Electronic Engineering and the Department of Aeronautics. My theoretical research is therefore motivated by a wide variety of problems in the design of aerospace, renewable energy and information systems. Applications include scheduling of computation and communication in aerial and mobile robotic networks, aerodynamic drag reduction over aerofoils, gust and load alleviation in wind turbine blades and space launch and re-entry vehicles.
Research Interests
Papers共 242 篇Author StatisticsCo-AuthorSimilar Experts
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CoRR (2024)
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CoRR (2024)
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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROLno. 2 (2024): 1370-1396
JOURNAL OF FLUID MECHANICS (2024)
IFAC PAPERSONLINEno. 2 (2023): 4840-4845
IFAC PAPERSONLINEno. 2 (2023): 1229-1234
arXiv (Cornell University)no. 4 (2023): 2592-2598
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