The main aim of the project is design of effective and advances methods of process control and study of optimal process operation. We will aim our attention mainly to processes with heat and mass transfer. These processes are inherently complex, exhibit nonlinearities and hybrid behaviour that has consequences in control quality and performance. Optimal control will include dynamic optimisation in continuous and discrete domains as a tool for qualitative analysis at upper process control level. Repeated dynamic optimisation at the lower lever yields algorithms of predictive control. This will result in characterisation of optimal operation regimes and controllers optimising processes and large units composed from them. Also important will be software implementation of proposed solutions, available to a larger community in open source code as well as verification in laboratory conditions.
The aim of the proposed project is to investigate and design new methods in the area of automation and control in process industries to increase profitability, stability, and competitiveness. We will focus on study of processes that are not operated in steady-state. Their control is example of optimal operation on multiple levels. We will study vertical integration between upper and lower levels, safety of communication between levels, reduction of complexity and increase of intelligence (smartness) of the basic process control level.
Goals for the first phase, 2016-2017: Analysis and proposal of solution
- Analysis and design of mathematical models for description of processes of chemical technologies.
- Analysis of optimality of operation for separation processes.
- Possibilities of complexity reduction of MPC.
- Development of interface of MPT for export of optimal controllers to embedded devices(PLC, FPGA).
Goals for the second phase, 2017-2019: Development of methods
- Robust predictive control of processes using Lyapunov functions.
- Complexity reduction in number of regions of explicit MPC.
- Explicit MPC for systems with a larger number of states.
- Development of methods for optimal control of separation processes.
- Horizontal and vertical integration of processes and controllers.
Goals for the third phase, 2019-2020: Validation and applications of methods
- Reduction of suboptimality of the optimal control at the lower level.
- Implementation of new methods of optima control with reduces memory and computational complexity.
- Development and addition of software tools for analysis, synthesis, and implementation of optimal control.
- Development and verification of intelligent devices for heat transfer processes.
- Applications of optimal control methods in process control.