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Simple models are necessary for real time control purposes.
The proposed method can be used for real time control applications.
This method is expected to work well for real time control of an operating HVAC system.
Fusion tokamaks are complex devices requiring many diagnostics for real time control of the plasma and off-line physical analysis.
Therefore, the proposed control strategy requires low computational effort, which makes it well suited for real time control applications.
This article focuses on the design and implementation of model-based control strategies for real time control of crystal size distribution (CSD) in semi batch crystallization processes.
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The obtained regulation signals are sent back to aggregators or device controllers for real-time control.
The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum.
This paper presents the design and implementation of a neural fuzzy controller suitable for real-time control of an autonomous mobile robot.
This coincides with the design objective of the control performance standards (CPS) which were established to improve the long-term performance of an automatic generation controller (AGC) used for real-time control of interconnected power systems.
The theoretical and experimental results indicate that the implemented fuzzy logic controller has a high performance for real-time control over a wide range of operating conditions.
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