Özet:
In recent years, emission regulations of the countries have been tightened with the increase in the number of cars. Nevertheless, reducing the emissions of diesel engines is a difficult technical issue. Since the Diesel Engine Air Path (DEAP) is a MIMO system with 2 actuators, EGR valve and VGT valve, and 2 outputs, manifold absolute pressure (MAP) and air mass flow (MAF), control of this system with SISO PID controllers requires an iterative fine-tuning process for controller parameters due to coupled effect of VGT and EGR on MAP and MAF. The main objective of this thesis is the Model Predictive Control (MPC) of MIMO Diesel Engine Air Path system. MPC is a well-known technique in the literature with its many applications on MIMO systems. Existing results show that MPC can satify the desired settling time, zero steady-state error, and overshoot criteria for both outputs MAP and MAF. However, the effect of actuator delay that considerably affects system performance, is not addressed sufficiently. In this thesis, MPC of DEAP is extended with a delay term added to actuators EGR and VGT on the plant model. A linear state-space model of the plant is obtained by using the System Identification techniques and the states of the identified model are extended due to delay term. It is shown that MPC performs better when the delay is taken into account in the algorithm. Another contribution of this thesis is that SISO PID controllers are optimized by Particle Swarm Optimization (PSO) method. The PID gains found by Ziegler-Nichols (ZN) method are taken as the initial points of the PSO and it is shown that PSO improves the PID controller performance for the MIMO system.
