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The ability of FPGA to perform massive parallel processing increases the obtainable control loop frequency, reduces the computational latency in the control system [15, 22], makes the controller stand-alone, and operates at high speed [28].
Fuzzy systems are used in an adaptive scheme to approximate the system using a nonlinear model while synergetic control guarantees robustness and the use of a chatter free continuous control law which makes the controller easy to implement.
This strategy automatically makes the controller work properly after simply connecting it to the control architecture, without further intervention from the operator.
The tunable scalar makes the controller more flexible in reducing the upper bound of the control gain.
The backstepping algorithm makes the controller immune to matched and mismatched uncertainties and the sliding mode control provides robustness.
As only output system states are considered, it makes the controller design and system analysis more challenging compared to the full-state feedback control schemes.
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To overcome this problem, a new adaptive controller based on a generalized predictive control (GPC) principle was designed to make the controller more robust.
The custom PC board is battery operated, which enables us to make the controller portable.
A 'get-snapshots message will make the controller return the currently collected data.
Finally, a 'get-custom-snapshots message will make the controller return the currently collected snapshots corresponding to custom-keys.
The number of failed actuator is limited in order to avoid making the controller too conservative.
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