Model Predictive Control (MPC) on a Chip Embedded project

Model Predictive Control (MPC) has become an established control technology in the petrochemical
industry. Its use is currently being pioneered in an increasingly wide range of high bandwidth applications, such as
ships, aerospace, road vehicles and “Lab-on-Chip” devices. MPC outperforms other control strategies through its
ability to deal with constraints. This requires on-line optimization, hence computational complexity can become an
issue when applying MPC to complex systems with fast response times or to embedded applications where
computational resource may be a major constraints. We are seeking students with suitable background and interest
to help us realize the vision of ``MPC on a Chip'', which is also an ASTAR research programme.
There are several projects along this line of research:
1. To develop a scalable and modular Matlab/Simulink model of constrained MPC algorithm
2. To develop a C model of (1) based on the interior point method
3. To develop a C model of (1) based on the active set method
4. To implement (2) and (3) on a suitable embedded processor or FPGA platform.
5. To exploit parallelism and/or multiple date width model to achieve area-time efficient FPGA implementation.
Students who wish to be considered for the above projects should have good programming expertise and are
interested in mathematical algorithms. Experiences with embedded control or FPGA would be an advantage.