Abstract:
Multi-Parametric programming provides a complete map of solutions of an optimization problem as a function of, unknown but bounded, parameters in the model, in a computationally efficient manner, without exhaustively enumerating the entire parameter space. In a Modelbased Predictive Control (MPC) framework, multi-parametric programming can be used to obtain the governing control laws – the optimal control variables as an explicit function of the state variables. The main advantage of this approach is that it reduces repetitive on-line control and optimization to simple function evaluations, which can be implemented on simple computational hardware, such as a microchip, thereby opening avenues for many applications in chemical, energy, automotive, and biomedical equipment, devices and systems.
In this presentation, we will provide a historical progress report, ‘the Road to Ithaca’, of the key developments in multi-parametric programming and control. We will also describe a number of key application areas, where this technology has shown a lot of potential and discuss key challenges and directions for future research as well as address the question of the suitability of explicit/ multi-parametric control as part of the advanced model-based control technology portfolio of the future.