A general methodology to design open loop controllers for nonlinear, dynamic, continuous systems is presented and applied to control a single flexible link (SFL). In this application, the partial differential equation...
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A general methodology to design open loop controllers for nonlinear, dynamic, continuous systems is presented and applied to control a single flexible link (SFL). In this application, the partial differential equations that describe the beam system are first analyzed via the finite element method (FEM) and Newmark integration method. Two open loop control inputs to achieve specified system performance criteria are then computed by posing and solving inverse dynamics problems. These analyses use nonlinear programming (NLP) algorithms and analytical gradients that are computed by the direct sensitivity method. The open loop control is verified experimentally. Closed loop controller synthesis for linear time invariant (LTI) and linear time varying systems (LTV) is relatively well understood. To apply this knowledge base to the control of the SFL, the nonlinear finite element plant model is linearized and recast in standard state space form.
The aim of the present paper is to find an optimum speed control hump geometric design by using the sequential quadratic programming method. Theoretical investigation of the dynamic behavior of the driver body compone...
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The aim of the present paper is to find an optimum speed control hump geometric design by using the sequential quadratic programming method. Theoretical investigation of the dynamic behavior of the driver body components and the vehicle due to crossing speed control humps is presented. The vehicle - driver system represented as a mathematical model consists of 12 degrees of freedom (DOF). Seven DOFs are used for the human body model in the heave mode and the rest are for the vehicle body, suspension system and tires. An optimum design method for the hump geometry is proposed to reduce the excessive shocks experienced by drivers when crossing the hump below the speed limit, while being unpleasant when going over the speed limit. The pleasant or unpleasant ride, or what is called comfort criteria (CC), is modeled by calculating the driver's head acceleration. In this regard, the geometry of the hump will be controlled to match an optimum practical shape that can be implemented economically. Three types of humps are discussed and evaluated in the optimization technique. These humps are Watts, flat-topped and polynomial humps. For Watts and flat-topped humps, different rise and return profiles which are used as design variables, are sinusoidal, harmonic, cycloidal, circular and modified harmonic. The global design was selected from 42 optimal designs which are found by combining different rise/return profiles for the three types of humps. The effect of special cases such as symmetrical roads, design limitations, CC, critical speed ( CS) and system parametric variations on the optimal design of speed control humps are presented at the end of this paper.
Conditions are given for the viability and the weak convergence of an inexact, relaxed proximal point algorithm for finding a common zero of countably many cohypomonotone operators in a Hilbert space. In turn, new con...
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Conditions are given for the viability and the weak convergence of an inexact, relaxed proximal point algorithm for finding a common zero of countably many cohypomonotone operators in a Hilbert space. In turn, new convergence results are obtained for an extended version of the proximal method of multipliers in nonlinear programming.
A number of filled functions was proposed recently. This paper presents a new perspective of the filled functions: their barrier attribute. More filled functions can be constructed according to this new interpretation...
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A number of filled functions was proposed recently. This paper presents a new perspective of the filled functions: their barrier attribute. More filled functions can be constructed according to this new interpretation. Two of them are with finite barriers while the remains are with infinite barriers. (C) 2003 Elsevier Inc. All rights reserved.
The filled function method is an effective approach to find the global minimizer. Two of the recently proposed filled functions are L(X) and L-2(X). Having observed that the second term in L(X) or L-2(X) may result in...
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The filled function method is an effective approach to find the global minimizer. Two of the recently proposed filled functions are L(X) and L-2(X). Having observed that the second term in L(X) or L-2(X) may result in undesirable computational behaviors, in this paper we propose a new function L-3(X). Having also realized that the essence of the mitigation is to eliminate the discontinuity, we propose another new function L-4(X)Both theoretical analysis and numerical testing results are presented. (C) 2003 Elsevier Inc. All rights reserved.
Optimal power flow (OPF) is one of the main functions of power generation operation and control. It determines the optimal setting of generating units. It is therefore of great importance to solve this problem as quic...
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Optimal power flow (OPF) is one of the main functions of power generation operation and control. It determines the optimal setting of generating units. It is therefore of great importance to solve this problem as quickly and accurately as possible. This paper presents the solution of the OPF using genetic algorithm technique. This paper proposes a new methodology for solving OPF. This methodology is divided into two parts. The first part employs the genetic algorithm (GA) to obtain a feasible solution subject to desired load convergence, while the other part employs GA to obtain the optimal solution. The main goal of this paper is to verify the viability of using genetic algorithm to solve the OPF problem simultaneously composed by the load flow and the economic dispatch problem. Six buses system are used to highlight the goodness of this solution technique. (C) 2003 Elsevier Inc. All rights reserved.
We consider the dynamic optimization of chemical processes with changes in the number of equilibrium phases. Recent work has shown that transitions in the number of phases can be modeled as a mathematical program with...
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We consider the dynamic optimization of chemical processes with changes in the number of equilibrium phases. Recent work has shown that transitions in the number of phases can be modeled as a mathematical program with equilibrium constraints (MPEC). This study generalizes the MPEC to consider dynamic characteristics. In particular, we describe a simultaneous discretization and solution strategy for dynamic optimization problems with complementarity constraints. These discretized problems are then solved with IPOPT-C, a recently developed barrier method for MPEC problems. Our approach is applied to two distillation examples. In the first, we consider the optimal startup of a binary batch distillation problem. In the second, we consider the dynamic operation of a cryogenic column for the separation of natural gas liquids. Both cases demonstrate the effectiveness of the approach on large scale MPEC problems. (C) 2004 Published by Elsevier Ltd.
Case-control studies are primary study designs used in genetic association studies. Sasieni (Biometrics 1997, 53, 1253-1261) pointed out that the allelic chi-square test used in genetic association studies is invalid ...
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Case-control studies are primary study designs used in genetic association studies. Sasieni (Biometrics 1997, 53, 1253-1261) pointed out that the allelic chi-square test used in genetic association studies is invalid when Hardy-Weinberg equilibrium (HWE) is violated in a combined population. It is important to know how much type I error rate is deviated from the nominal level under violated HWE. We examine bounds of type I error rate of the allelic chi-square test. We also investigate power of the goodness-of-fit test for HWE which can be used as a guideline for selecting an appropriate test between the allelic chi-square test and the modified allelic chi-square test, the latter of which was proposed for cases of violated HWE. In small samples, power is not large enough to detect the Wright's inbreeding model of small values of inbreeding coefficient. Therefore, when the null hypothesis of HWE is barely accepted, the modified test should be considered as an alternative method.
Applications of nonlinear optimization problems with many degrees of freedom have become more common in the process industries, especially in the area of process operations. However, most widely used nonlinear program...
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Applications of nonlinear optimization problems with many degrees of freedom have become more common in the process industries, especially in the area of process operations. However, most widely used nonlinear programming (NLP) solvers are designed for the efficient solution of problems with few degrees of freedom. Here we consider a new NLP algorithm, IPOPT, designed for many degrees of freedom and many potentially active constraint sets. The IPOPT algorithm follows a primal-dual interior point approach, and its robustness, improved convergence, and computational speed compared to those of other popular NLP algorithms will be analyzed. To demonstrate its effectiveness on process applications, we consider large gasoline blending and data reconciliation problems, both of which contain nonlinear mass balance constraints and process properties. Results on this computational comparison show significant benefits from the IPOPT algorithm.
Conventional behavioral models such as Cournot to analyze generator behavior do not reflect many of the complexities of advanced electricity markets. Dispatch and pricing in a number of advanced pool-based electricity...
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Conventional behavioral models such as Cournot to analyze generator behavior do not reflect many of the complexities of advanced electricity markets. Dispatch and pricing in a number of advanced pool-based electricity markets worldwide explicitly recognize the co-optimization of ancillary services as well as transmission constraints. This paper discusses the development of, and experiments with, a multimarket Cournot model that deals with co-optimization of multiple commodities namely, energy and various classes of ancillary services and deals with transmission constraints that separate these commodity markets spatially. We also discuss the multimarket extension of the Cournot model to deal with bilateral contracts (for energy). A nonlinear programming formulation of the proposed model and the analysis of nodal prices are presented followed by a detailed set of experiments using a simple three-node system. The model is expected to add to understanding of complex interactions between energy and ancillary services markets, and further the impact transmission capacity limits may have on exercise of market power of each of these markets.
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