Design LQG/LTR Controller for Higher Order Systems Based on the Reduction Model

The dimension of the power systems model may easily reach the order of thousands of state variable in applications such as dynamic simulation, control, etc. So the model reduction is a very important topic in power community. The cost and complication of the controller increases as the system order goes high. This problem can be overcome if a good reduced-order model is available for the original higher-order system and if it is possible to design a controller using a lower-order model, which will stabilize the original higher-order system when placed in the closed loop. The linear quadratic Gaussian/Loop transfer Recovery (LQG/LTR) controller is a robust and stable control which is a systematic method with a view of engineering. In the present work, based on modified particle swarm optimization (MPSO), a simple method for finding reduced order models for multi input multi output (MIMO) large scale systems is investigated. Depended on the linear reducing equations design a robust controller using LQG/LTR technique for the system. The main feature of the proposed technique is that it is applicable to all systems and not limited to only stable or strictly proper systems. Therefore, it is most suitable for power systems. LQG/LTR guarantees both good robustness and performance.