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Each controller includes a PI feedback part and a feed-forward compensation part for the disturbances by using a disturbance observer (DOB).
[16] developed a sensor-less force control for industrial robots, that was applied to a peg-in-hole assembly task by using a disturbance observer that estimates disturbance torques at each robot's joints.
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Firstly, the unknown elements including uncertainties and external disturbance are estimated by using a fuzzy disturbance observer which does not need a priori information of these unknown dynamics.
The impact of such phenomena on the robustness of the servo is evaluated by using experimental data, and an H∞ controller is designed to reduce the coupling effect, by using a suitable disturbance model into the problem formulation.
Such a problem is solved by using a distributed active anti-disturbance cooperative control scheme, which combines sliding-mode control (SMC) and disturbance observer based control (DOBC) approaches together.
A disturbance counteracting control law is synthesized by using a Luenberger observer incorporating the structure and disturbance dynamics.
In the autonomous method, a repetitive torque disturbance (by using a reaction wheel) is exerted to the stabilized satellite, the cold-gas thrusters are then applied in an on-board control system to stabilize the satellite attitude.
First, a new sliding mode controller is designed to ensure the asymptotic convergence of the attitude and angular velocity tracking errors against external disturbances and inertia uncertainties by using a modified differentiator to estimate the total disturbances.
In order to solve the problem of stability control for biped robots, the concept of stability training is proposed by using a training platform to exert random disturbance with amplitude limitation on robots that are to be trained.
State estimation is achieved by using a Kalman filter and appending modeled disturbances as augmented states to the original system model.
We will show that for a class of uncertain nonlinear systems with bounded disturbances, by using an appropriately designed adaptive neural controller, the disturbances are attenuated and the system output tracks a periodic orbit in finite time.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com