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Also, with the right choice of control strategy by embedding micro-scale controller, this study shows that more complex controller algorithms might not be necessary.
More complex controller can also be used here to closely mimic the synchronous generator with excitation and torque dynamics [43].
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The key finding is that controllers with simplified control models and fewer exogenous inputs can perform almost as well as more complex controllers.
While more complex controllers such as MPC could potentially lead to improved performances considering more design variables, complex models and extensive commissioning, this study illustrates that simpler control strategies such as RBC2 can also lead to satisfying results.
Moreover our controller is compared with other more complex control techniques as predictive control and robust H∞ controllers, exhibiting better or similar performances than these.
Gradually, they move to more complex concepts and controller design.
The network architecture also becomes more complex since a centralized controller is needed to perform handover control for each UE.
Although the FOPID controller is more effective compared to the traditional PID controller, it is more complex to optimize the parameters of this controller for a pump turbine governing system (PTGS).
Other interactive experiences use more complex hardware, including hand controllers and body-tracking sensors, to simulate such activities as painting and mini-golf.
Recently, control engineers and theorist have developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants.
However, in exchange, the design of the dynamic output feedback controller is more complex and difficult.
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