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The architecture of the controller is based on event-based decoupled solutions for the set-point following and the load disturbance rejection tasks.
The controller is based on the hierarchical control strategy.
The feedback signal selection for the controller is based on an input/output controllability metric specific to output feedback.
To reduce the vibration effect, based on an external disturbance model with consideration of dynamics of the piezoelectric actuator, adaptive vibration control experimental system designed, where the controller is based on Youla-Kucera parametrization and right coprime factorization.
The controller is based on the Model Predictive Control (MPC) concept.
The controller is based on a neuro-fuzzy structure with critic-based leaning structure.
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The computation of the controllers is based on a dynamic programming approach.
The controllers are based on simple algorithms (nonlinear P-control, simple prediction models) which can be implemented in standard programmable logic controllers (PLCs).
The controllers are based on discrete time varying l∞ theory for periodic/almost periodic linear systems.
The controllers are based on various configurations of the closed loop system.
The design of the intelligent controller is based on the optimal control theory, the adaptive neural network system, and the robust control technique.
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