scholarly journals A New Adaptive System for Suppression of Transient Wind Disturbance in Large Antennas

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Wei Liang ◽  
Jin Huang ◽  
Jie Zhang
Keyword(s):  
Adaptive System ◽  
Surface Profile ◽  
Time Estimation ◽  
Linear Quadratic Regulator ◽  
Minimum Variance ◽  
Wind Disturbance ◽  
Linear Quadratic ◽  
Tension Distribution ◽  
Vibration State ◽  
Transient Wind

Under transient wind disturbance, vibration deformation of the large antenna surface profile causes deterioration of pointing performance. This paper presents a new adaptive system to suppress unknown transient wind disturbance. First, to monitor the vibration, based on the acceleration measurement and a low-order flexible model considering equivalent identification of forces, the real-time estimation of the vibration state is obtained in an unbiased minimum-variance way. Next, a novel four-cable-actuator mechanism with a circular slide track is proposed for suppressing the vibration, in which the locations of the cable drivers on the slide track are determined according to the attitude of the antenna, and the expected tension distribution of the cables is found by the vibration state and the optimal gain of the linear quadratic regulator (LQR). In the end, the simulation implementation of a 7.3 m antenna under the transient wind disturbance is used to verify the effectiveness of the proposed method.

Calculation of Optimized Movement Trajectories for the Human Forearm

2013 ◽  
Vol 401-403 ◽  
pp. 1347-1352
Author(s):  
Li Li Yang
Keyword(s):  
Discrete Time ◽  
Linear Quadratic Regulator ◽  
Minimum Variance ◽  
Movement Trajectory ◽  
Linear Quadratic ◽  
Variance Model ◽  
Movement Trajectories ◽  
Human Forearm ◽  
Optimal Movement ◽  
Time Linear

Using the minimum variance model, optimal human forearm trajectories formation was investigated using a discrete time linear quadratic regulator. First, the continuous dynamics of the human forearm were established on the basis of the relation between muscle torque and neural control signal, and then we transferred the continuous system dynamics to discrete time notation. Finally we expressed the objective function of minimum variance model using a discrete time linear quadratic regulator and employed Riccati recursion to obtain the optimal movement trajectories of the human forearm. The results of example simulation show that the optimal movement trajectory of the forearm follows a smooth curve, and the speed curve of the hand is single peaked and bell shaped. These are in good agreement with the inherent kinematic properties of optimal movement, and therefore the method is effective for calculating the optimal movement trajectory of the human forearm.

Vehicle Stability Improvement by Active Front Steering Control

2007 ◽  
Author(s):  
Deling Chen ◽  
Chengliang Yin ◽  
Li Chen
Keyword(s):  
Time Estimation ◽  
Linear Quadratic Regulator ◽  
Steering System ◽  
Angle Measurement ◽  
Vehicle Stability ◽  
Steering Control ◽  
Linear Quadratic ◽  
Sideslip Angle ◽  
Feedback Parameter ◽  
Active Front Steering

This paper presents the vehicle stability improvement by active front steering (AFS) control. Firstly, a mathematical model of the steering system incorporating vehicle dynamics is analyzed based on the structure of the AFS system. Then feedback controller with linear quadratic regulator (LQR) optimization is proposed. In the controller, the assisted motor in the system is controlled by the combination of feedforward method and feedback method. And the feedback parameter is the yaw rate together with the sideslip angle. Due to the difficulties associated with the sideslip angle measurement of vehicle, a state observer is designed to provide real time estimation to meet the demands of feedback. In the last, the system is simulated in MATLAB. The results show that the vehicle handling stability is improved with the AFS control, and the effectiveness of the control system is demonstrated.

A Study on Linear Quadratic Regulator with the Desired Low-Pass Property

2013 ◽  
Vol 133 (12) ◽  
pp. 2167-2175 ◽  
Author(s):  
Katsuhiko Fuwa ◽  
Satoshi Murayama ◽  
Tatsuo Narikiyo
Keyword(s):  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Low Pass

scholarly journals Neural Network Based Contact Force Control Algorithm for Walking Robots

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 287
Author(s):  
Byeongjin Kim ◽  
Soohyun Kim
Keyword(s):  
Neural Network ◽  
Contact Force ◽  
Force Control ◽  
Control Algorithm ◽  
Position Control ◽  
Linear Quadratic Regulator ◽  
Walking Robots ◽  
Test Model ◽  
Linear Quadratic ◽  
Contact Force Control

Walking algorithms using push-off improve moving efficiency and disturbance rejection performance. However, the algorithm based on classical contact force control requires an exact model or a Force/Torque sensor. This paper proposes a novel contact force control algorithm based on neural networks. The proposed model is adapted to a linear quadratic regulator for position control and balance. The results demonstrate that this neural network-based model can accurately generate force and effectively reduce errors without requiring a sensor. The effectiveness of the algorithm is assessed with the realistic test model. Compared to the Jacobian-based calculation, our algorithm significantly improves the accuracy of the force control. One step simulation was used to analyze the robustness of the algorithm. In summary, this walking control algorithm generates a push-off force with precision and enables it to reject disturbance rapidly.

scholarly journals Distributed Linear Quadratic Regulator Robust to Communication Dropouts

2020 ◽  
Vol 53 (2) ◽  
pp. 3072-3078
Author(s):  
C. Amo Alonso ◽  
D. Ho ◽  
J.M. Maestre
Keyword(s):  
Linear Quadratic Regulator ◽  
Linear Quadratic
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