scholarly journals Lyapunov’s theorem for continuous frames

2018 ◽  
Vol 146 (9) ◽  
pp. 3825-3838 ◽  
Author(s):  
Marcin Bownik
Keyword(s):  
Lyapunov’S Theorem ◽  
Continuous Frames

scholarly journals Robust Sensorless Model-Predictive Torque Flux Control for High-Performance Induction Motor Drives

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 403
Author(s):  
Ahmed G. Mahmoud A. Aziz ◽  
Hegazy Rez ◽  
Ahmed A. Zaki Diab
Keyword(s):  
Induction Motor ◽  
High Performance ◽  
Core Loss ◽  
Parameters Estimation ◽  
Torque Control ◽  
Flux Control ◽  
Control Approach ◽  
Light Load ◽  
Wide Range ◽  
Lyapunov’S Theorem

This paper introduces a novel sensorless model-predictive torque-flux control (MPTFC) for two-level inverter-fed induction motor (IM) drives to overcome the high torque ripples issue, which is evidently presented in model-predictive torque control (MPTC). The suggested control approach will be based on a novel modification for the adaptive full-order-observer (AFOO). Moreover, the motor is modeled considering core losses and a compensation term of core loss applied to the suggested observer. In order to mitigate the machine losses, particularly at low speed and light load operations, the loss minimization criterion (LMC) is suggested. A comprehensive comparative analysis between the performance of IM drive under conventional MPTC, and those of the proposed MPTFC approaches (without and with consideration of the LMC) has been carried out to confirm the efficiency of the proposed MPTFC drive. Based on MATLAB® and Simulink® from MathWorks® (2018a, Natick, MA 01760-2098 USA) simulation results, the suggested sensorless system can operate at very low speeds and has the better dynamic and steady-state performance. Moreover, a comparison in detail of MPTC and the proposed MPTFC techniques regarding torque, current, and fluxes ripples is performed. The stability of the modified adaptive closed-loop observer for speed, flux and parameters estimation methodology is proven for a wide range of speeds via Lyapunov’s theorem.

Closure to “Elasti-Plastic Analysis of Continuous Frames and Beams”

1959 ◽  
Vol 85 (9) ◽  
pp. 83-86
Author(s):  
Lawrence P. Johnson ◽  
Herbert A. Sawyer
Keyword(s):  
Plastic Analysis ◽  
Continuous Frames

Closure to “Seismic and Cyclonic Response of Continuous Frames”

1975 ◽  
Vol 101 (7) ◽  
pp. 1606-1608
Author(s):  
Gerald M. Smith ◽  
George C. Ernst ◽  
Mahendra Maheshwari
Keyword(s):  
Continuous Frames

Minimum Weight Plastic Design of Continuous Frames

1964 ◽  
Vol 90 (3) ◽  
pp. 39-52
Author(s):  
Donald A. Sawyer ◽  
Linton E. Grinter
Keyword(s):  
Minimum Weight ◽  
Plastic Design ◽  
Continuous Frames

scholarly journals Survey Analysis of Robust and Real-Time Multi-Lane and Single Lane Detection in Indian Highway Scenarios

2021 ◽  
Vol 309 ◽  
pp. 01117
Author(s):  
A. Sai Hanuman ◽  
G. Prasanna Kumar
Keyword(s):  
Neural Network ◽  
System Integration ◽  
Large Scale ◽  
Feature Learning ◽  
Semantic Segmentation ◽  
Lane Detection ◽  
Learning Approaches ◽  
Survey Analysis ◽  
Lane Recognition ◽  
Continuous Frames

Studies on lane detection Lane identification methods, integration, and evaluation strategies square measure all examined. The system integration approaches for building a lot of strong detection systems are then evaluated and analyzed, taking into account the inherent limits of camera-based lane detecting systems. Present deep learning approaches to lane detection are inherently CNN's semantic segmentation network the results of the segmentation of the roadways and the segmentation of the lane markers are fused using a fusion method. By manipulating a huge number of frames from a continuous driving environment, we examine lane detection, and we propose a hybrid deep architecture that combines the convolution neural network (CNN) and the continuous neural network (CNN) (RNN). Because of the extensive information background and the high cost of camera equipment, a substantial number of existing results concentrate on vision-based lane recognition systems. Extensive tests on two large-scale datasets show that the planned technique outperforms rivals' lane detection strategies, particularly in challenging settings. A CNN block in particular isolates information from each frame before sending the CNN choices of several continuous frames with time-series qualities to the RNN block for feature learning and lane prediction.

Discussion of “Minimum Weight Plastic Design of Continuous Frames”

1964 ◽  
Vol 90 (5) ◽  
pp. 459-461
Author(s):  
Jacques Heyman ◽  
William Prager
Keyword(s):  
Minimum Weight ◽  
Plastic Design ◽  
Continuous Frames

Discussion of “Minimum Weight Plastic Design of Continuous Frames”

1965 ◽  
Vol 91 (1) ◽  
pp. 167-169
Author(s):  
R.H. Wood
Keyword(s):  
Minimum Weight ◽  
Plastic Design ◽  
Continuous Frames

Discussion of “Seismic and Cyclonic Response of Continuous Frames”

1975 ◽  
Vol 101 (1) ◽  
pp. 331-335
Author(s):  
Robert Park
Keyword(s):  
Continuous Frames

Steady-State Forced Vibration of Continuous Frames

1953 ◽  
Vol 118 (1) ◽  
pp. 794-814
Author(s):  
C. T. G. Looney
Keyword(s):  
Steady State ◽  
Forced Vibration ◽  
Continuous Frames
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