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The Νanoflex ™ 4-IFC Controller utilizes pressure to control the valves in the chips and load samples and gene expression assay reagents into the reaction chambers.
The Nanoflex™ 4-IFC Controller utilizes pressure to control the valves in the chips and load samples and genotyping assay reagents into the reaction chambers.
Then the proposed controller utilizes an adaptive scheme and an auxiliary control law to deal with the uncertain environmental constraint, disturbances, and robotic modeling uncertainties.
The proposed controller utilizes the robust and adaptive nature of fuzzy logic control (FLC) and simple structure of PI controller to effectively improve the dynamic performance of the GIC during uncertainties.
The low-level controller utilizes a non-linear vehicle model in order to compute the vehicle control inputs required to execute the planned manoeuvre.
The proposed controller utilizes only local measurements and has no requirement for the bounds of interconnections in the power system.
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A preview feed-forward controller utilizing the desired cutting force is designed to improve the transient response of the CNC control system.
An output feedback Lyapunov-based model predictive controller, utilizing an appropriately designed state observer (to estimate the unmeasured states), is formulated and its stability region explicitly characterized.
In this paper, a novel FPGA (Field Programmable Gate Array) based motion controller utilizing its high-speed parallel computing power is proposed to realize the Cox de Boor algorithm for second and higher degrees NURBS interpolation.
Imaging was performed on a multimode atomic force microscope with a Nanoscope IIIA or Nanoscope V controller utilizing a fluid cell (all from Bruker, Santa Barbara, CA).
Advanced control strategies and communication are integrated within the embedded controllers utilized for automotive control applications.
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