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Based on the observed velocities of neighboring vehicles, distributed output-feedback containment controllers are devised, under which the containment can be achieved regardless of model uncertainty, unknown ocean disturbances, and unmeasured velocity information.
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To cope with the uncertainties arising from free-flyer's kinematics, dynamics and surface stiffness and position, an adaptive Jacobian controller is devised.
A full state feedback controller is devised and the gains are scheduled on measured speed and pressures, together with approximated volumetric flow.
Based on the dynamic fuzzy neural network (DFNN) modeling, an adaptive backstepping controller is devised, which works through structure and parameter-learning phases for adaptation.
The proposed controller uses a set of inner-loop gains to provide stability using classical techniques, whereas a gain self-scheduled H∞ outer-loop controller is devised to guarantee a specific level of robust stability and performance for the time-varying dynamics.
A switching type controller consisting of two control modes are devised: a PID-type fuzzy controller consisting of a PI-type and a PD-type fuzzy controller, and a conventional PID.
On the basis of the Lyapunov stability theory, the controllers and corresponding parameter update rule are devised to make the states of two identical Liu chaotic systems with unknown parameter synchronized.
Linear matrix inequality based methods are devised for designing static state feedback gain-scheduled controllers with either an H∞ or quadratic regulator-type performance.
A number of stability-preserving fault accommodation strategies are devised, including updating the post-fault models, adjusting the controllers' parameters, or a combination of both.
In particular, two indices are devised so that the advantage of using a feedforward compensator with respect to the use of a feedback controller only is quantified.
Questions are devised beforehand.
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CEO of Professional Science Editing for Scientists @ prosciediting.com