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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 49074 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Haeri, Mohammad
- Abstract:
- In today's world we are dealing with many devices and processes with the goal of efficiency and performance improvement. In many processes particularly chemical ones, the goal is to control the output according to its constraints in the way that the performance is economically efficient, such as reducing energy consumption and energy loss and increasing efficiency. In order to control a process with economical goals, an economical cost function is used and after determination of optimal values a controller is used to guide the process so can achieve them. Model predictive control (MPC) is very common in this economic control Due to advantages such as considering the problem constraints. In each sample time the appropriate control signal is computed by an online optimization. For this reason, along with all MPC advantages, high online computation in each sample time is the main disadvantage of this controller. So it is usually used in slow processes such as chemical ones. In economic control the optimal values from cost function are not necessarily constant and can be change by changing the economic parameters over the time. This parameter and reference changes can change the problem constraints and cause more calculations. Therefore in this thesis we use Linear Matrix Inequality (LMI) in MPC with time varying input constraints to create an offline table and so reduce the computation. Finally, we explain the performance of the proposed method by implementing the algorithm on a race car
- Keywords:
- Model Predictive Control ; Linear Inequalities ; Input Constraint ; Economic Model Predictive Control (EMPC) ; Time Varying Constraints
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