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In order to achieve robustness of the trajectory tracking performance with respect to model errors or unknown external disturbances, the feedforward control is supplemented by a feedback controller in a two degree of freedom design which feeds back the measured displacements at the top of the scanner.
Thus, the effect from unlearnable dynamics on the controlled system can be attenuated solely by a feedback controller design.
The gap spacing is stabilized by a feedback controller (CS100) with three sets of glass reference capacitors and piezoelectric transducers on Zerodur pillars.
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Control theory can provide QoS guarantees by using a feedback controller, that dynamically adjusts the behaviour of the system based on the measured outputs.
This can be overcome by designing a feedback controller, which stabilize the system before identification can takes place.
Motivated by the fast convergence observed, a feedback controller with time-varying gains is applied to the problem of tracking a moving PDF. Monte Carlo simulations validate very well the control for both stabilization and tracking problems.
The attitude maneuver is implemented by the momentum transfer technique, and a feedback controller is designed.
At each step of design, a feedback controller strengthened by nonlinear damping terms to counteract modelling errors is designed to guarantee input-to-state practical stability of the corresponding subsystem, and then parameter adaptions are introduced to reduce the ultimate error bound.
As soon as the specimen begins to swell the micropositioning was moved upward by a feedback control system, processed by PID controller based on algorithm in NI Labview (National Instruments, Texas, USA) which actively maintains the applied preload at its constant value.
Levitation forces generated by each transducer are individually controlled by a state feedback controller with auto-resonant (self-excited) frequency control.
This paper presents a hybrid adaptive fuzzy control (HAFC) design methodology, where the nonlinear system is controlled by a state feedback controller and an adaptive fuzzy controller.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com