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The DSM controller has a hierarchical control architecture, wherein there is a central controller (CC) and numerous local controllers (LCs).
Results show that the H2 controller has a better attitude control performance over the H∞ controller and PI controller itself.
Closer analysis revealed that the MPC controller has a tighter XD control, while the proposed controller was tighter in β control.
Moreover, the feedback controller has a definite structure, thus facilitating the iteration of control modeling and control synthesis to reach a sound design.
The validation results demonstrated that the proposed H∞ robust controller has a superior robustness and an enhanced control performance.
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.
It can be seen from Figs. 5, 6, 7 that the control system with the developed finite-time adaptive neural controller has a smaller tracking error.
According to the numerical simulation results it can be concluded that the proposed hybrid controller has a suitable and efficient performance for maneuver control and suppressing the transverse vibrations of the structure.
The proposed fuzzy controller has a simple and intuitively understandable structure, and executes the three controls entirely in parallel.
The new controller has a feature that it only uses the state variable for control and does not require the target equilibrium point in the feedback path.
The derived controller has a modular structure consisting of an input-to-state stabilizing (ISS) control module and a passive parameter identifier.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com