scholarly journals Stability Analysis and Variational Integrator for Real-Time Formation Based on Potential Field

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Shengqing Yang ◽  
Jianqiao Yu
Keyword(s):  
Stability Analysis ◽  
Nonlinear System ◽  
Dynamic System ◽  
Real Time ◽  
Potential Field ◽  
Lagrange Equation ◽  
System Stability ◽  
Damping Force ◽  
Variational Integrator ◽  
Error Dynamic

This paper investigates a framework of real-time formation of autonomous vehicles by using potential field and variational integrator. Real-time formation requires vehicles to have coordinated motion and efficient computation. Interactions described by potential field can meet the former requirement which results in a nonlinear system. Stability analysis of such nonlinear system is difficult. Our methodology of stability analysis is discussed in error dynamic system. Transformation of coordinates from inertial frame to body frame can help the stability analysis focus on the structure instead of particular coordinates. Then, the Jacobian of reduced system can be calculated. It can be proved that the formation is stable at the equilibrium point of error dynamic system with the effect of damping force. For consideration of calculation, variational integrator is introduced. It is equivalent to solving algebraic equations. Forced Euler-Lagrange equation in discrete expression is used to construct a forced variational integrator for vehicles in potential field and obstacle environment. By applying forced variational integrator on computation of vehicles' motion, real-time formation of vehicles in obstacle environment can be implemented. Algorithm based on forced variational integrator is designed for a leader-follower formation.

scholarly journals Nonlinear/Linear Switched Control of Inverted Pendulum System: Stability Analysis and Real-Time Implementation

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Amira Tiga ◽  
Chekib Ghorbel ◽  
Naceur Benhadj Braiek
Keyword(s):  
Stability Analysis ◽  
Real Time ◽  
State Feedback ◽  
Inverted Pendulum ◽  
System Stability ◽  
Control Synthesis ◽  
Vertical Position ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Linear State

This paper treats the problems of stability analysis and control synthesis of the switched inverted pendulum system with nonlinear/linear controllers. The proposed control strategy consists of switching between backstepping and linear state feedback controllers on swing-up and stabilization zones, respectively. First, the backstepping controller is implemented to guarantee the rapid convergence of the pendulum to the desired rod angle from the vertical position. Next, the state feedback is employed to stabilize and maintain the system on the upright position inherently unstable. Based on the quadratic Lyapunov approach, the switching between the two zones is analyzed in order to determine a sufficient domain in which the stability of the desired equilibrium point is justified. A real-time experimentation shows a reduction of 84% of the samples below the classical scheme when using only the backstepping control in the entire operating region. Furthermore, the reduction percentage has become 92% in comparison with the composite linear/linear controller.

Experience with dynamic system monitors to enhance system stability analysis

1992 ◽  
Vol 7 (2) ◽  
pp. 693-701 ◽  
Author(s):  
H.K. Clark ◽  
R.K. Gupta ◽  
C. Loutan ◽  
D.R. Sutphin
Keyword(s):  
Stability Analysis ◽  
Dynamic System ◽  
System Stability ◽  
System Stability Analysis

Updating real‐time flood forecasts via the dynamic system response curve method

2015 ◽  
Vol 51 (7) ◽  
pp. 5128-5144 ◽  
Author(s):  
Wei Si ◽  
Weimin Bao ◽  
Hoshin V. Gupta
Keyword(s):  
Dynamic System ◽  
Real Time ◽  
Response Curve ◽  
System Response ◽  
Curve Method

scholarly journals Machine Learning-Assisted Measurement Device-Independent Quantum Key Distribution on Reference Frame Calibration

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1242
Author(s):  
Sihao Zhang ◽  
Jingyang Liu ◽  
Guigen Zeng ◽  
Chunhui Zhang ◽  
Xingyu Zhou ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Reference Frame ◽  
Quantum Key Distribution ◽  
Short Term Memory ◽  
Key Distribution ◽  
Transmission Efficiency ◽  
System Stability ◽  
Measurement Device ◽  
Measurement Device Independent

In most of the realistic measurement device-independent quantum key distribution (MDI-QKD) systems, efficient, real-time feedback controls are required to maintain system stability when facing disturbance from either external environment or imperfect internal components. Traditionally, people either use a “scanning-and-transmitting” program or insert an extra device to make a phase reference frame calibration for a stable high-visibility interference, resulting in higher system complexity and lower transmission efficiency. In this work, we build a machine learning-assisted MDI-QKD system, where a machine learning model—the long short-term memory (LSTM) network—is for the first time to apply onto the MDI-QKD system for reference frame calibrations. In this machine learning-assisted MDI-QKD system, one can predict out the phase drift between the two users in advance, and actively perform real-time phase compensations, dramatically increasing the key transmission efficiency. Furthermore, we carry out corresponding experimental demonstration over 100 km and 250 km commercial standard single-mode fibers, verifying the effectiveness of the approach.

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