General Polynomial Method for Regulator Design

2018 ◽  
pp. 185-192
Author(s):  
László Keviczky ◽  
Ruth Bars ◽  
Jenő Hetthéssy ◽  
Csilla Bányász
Keyword(s):  
Polynomial Method ◽  
General Polynomial

General Polynomial Method to Design Discrete Regulators

2018 ◽  
pp. 261-264
Author(s):  
László Keviczky ◽  
Ruth Bars ◽  
Jenő Hetthéssy ◽  
Csilla Bányász
Keyword(s):  
Polynomial Method ◽  
General Polynomial

General Polynomial Method for Controller Design

2018 ◽  
pp. 343-350
Author(s):  
László Keviczky ◽  
Ruth Bars ◽  
Jenő Hetthéssy ◽  
Csilla Bányász
Keyword(s):  
Controller Design ◽  
Polynomial Method ◽  
General Polynomial

General Polynomial Method for the Design of Discrete-Time Controllers

2018 ◽  
pp. 459-463
Author(s):  
László Keviczky ◽  
Ruth Bars ◽  
Jenő Hetthéssy ◽  
Csilla Bányász
Keyword(s):  
Discrete Time ◽  
Polynomial Method ◽  
General Polynomial

Determination of Stress Intensity Factors for Gradient Stress Fields

1977 ◽  
Vol 99 (3) ◽  
pp. 477-484 ◽  
Author(s):  
J. M. Bloom ◽  
W. A. Van Der Sluys
Keyword(s):  
Stress Intensity ◽  
Crack Length ◽  
Stress Intensity Factors ◽  
Maximum Stress ◽  
Nuclear Industry ◽  
Stress Fields ◽  
Polynomial Method ◽  
Intensity Factors ◽  
Asme Code ◽  
Linear Envelope

This paper evaluates eight different analytical procedures used in determining elastic stress intensity factors for gradient or nonlinear stress fields. From a fracture viewpoint, the main interest in this problem comes from the nuclear industry where the safety of the nuclear system is of concern. A fracture mechanics analysis is then required to demonstrate the vessel integrity under these postulated accident conditions. The geometry chosen for his study is that of a 10-in. thick flawed plate with nonuniform stress distribution through the thickness. Two loading conditions are evaluated, both nonlinear and both defined by polynomials. The assumed cracks are infinitely long surface defects. Eight methods are used to find the stress intensity factor: 1–maximum stress, 2–linear envelope, 3–linearization over the crack length from ASME Code, Section XI, 4–equivalent linear moment from ASME Code, Section III, Appendix G for thermal loadings, 5–integration method from WRC 175, Appendix 4 for thermal loadings, 6–8-node singularity (quarter-point) isoparametric element in conjunction with the displacement method, 7–polynomial method, and 8–semi-infinite edge crack linear distribution over crack. Comparisons are made between all eight procedures with the finding that the methods can be ranked in order of decreasing conservatism and ease of application as follows: 1–maximum stress, 2–linear envelope, 3–linearization over the crack length, 4–polynomial method, and 5–singularity element method. Good agreement is found between the last three of these methods. The remaining three methods produce nonconservative results.

scholarly journals Iterative stability analysis for general polynomial control systems

2021 ◽  
Author(s):  
Bo Xiao ◽  
Hak-Keung Lam ◽  
Zhixiong Zhong
Keyword(s):  
Stability Analysis ◽  
Lyapunov Function ◽  
Control Systems ◽  
Polynomial System ◽  
Stability Conditions ◽  
General Polynomial ◽  
Main Challenge ◽  
Detailed Simulation ◽  
Feasible Solutions ◽  
The Stability

AbstractThe main challenge of the stability analysis for general polynomial control systems is that non-convex terms exist in the stability conditions, which hinders solving the stability conditions numerically. Most approaches in the literature impose constraints on the Lyapunov function candidates or the non-convex related terms to circumvent this problem. Motivated by this difficulty, in this paper, we confront the non-convex problem directly and present an iterative stability analysis to address the long-standing problem in general polynomial control systems. Different from the existing methods, no constraints are imposed on the polynomial Lyapunov function candidates. Therefore, the limitations on the Lyapunov function candidate and non-convex terms are eliminated from the proposed analysis, which makes the proposed method more general than the state-of-the-art. In the proposed approach, the stability for the general polynomial model is analyzed and the original non-convex stability conditions are developed. To solve the non-convex stability conditions through the sum-of-squares programming, the iterative stability analysis is presented. The feasible solutions are verified by the original non-convex stability conditions to guarantee the asymptotic stability of the general polynomial system. The detailed simulation example is provided to verify the effectiveness of the proposed approach. The simulation results show that the proposed approach is more capable to find feasible solutions for the general polynomial control systems when compared with the existing ones.

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