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2nd International Conference on Distributed Computing and High Performance Computing (DCHPC)

作者： Mazarei, Mohammad Mehdi Behroozpoor, Ali Asghar Kamyad, Ali Vahidian Islamic Azad Univ Bushehr Branch Dept Sci Bushehr Iran Ferdowsi Univ Mashad Dept Appl Math Mashhad Iran

ISBN: (纸本)9781665496728

In the real applied optimization problems, we usually face nonlinear fuzzy programming problems (FNLPPs). This paper focuses on a class of fuzzy quadratic programming problems (FQPPs) in which all of technical coefficients and constraint inequalities are fuzzy ones. Initially, some definitions of fuzzy mathematics are introduced and then, we discuss on fuzzy quadratic programming problems and introduce a new approach to find the approximate solution to these problems. Finally, we introduce some numerical examples to show the efficiency of the proposed approach.

关键词： Fuzzy quadratic programming problem Piecewise linearization

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On inexact quadratic programming problems involving mixed terms with an application to tea industry

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 156卷

作者： Mahajan, Sumati Gupta, S. K. Punjab Engn Coll Dept Appl Sci Chandigarh 160012 India Indian Inst Technol Dept Math Roorkee 247667 Uttar Pradesh India

Inexact quadratic programming (IQP) is designed to handle impreciseness in data/modelling parameters of quadratic programming (QP). The nature of IQP often leads to procedural and applicability problems. The existing studies on IQP have not incorporated the terms of the type x(i)x(j), i not equal j in the formulation of IQP problem (or IQPP), thereby limiting its scope of applications to specific types of problems only. The paper presents an extension of the past efforts by including such terms and hence, gives wider scope of its applications. Two methodologies viz. Duality approach and Modified method to solve the generalized IQPP are suggested. In addition, it has been shown that the Modified method significantly increases the computational efficiency by reducing the involved variables and constraints. Finally, an application of IQP is demonstrated by citing a realistic problem from an area of product mix and production planning, particularly in the tea industry.

关键词： Inexact parameters quadratic programming problem Duality approach Modified method Convex optimization

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Some properties of solution sets to nonconvex quadratic programming problems

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OPTIMIZATION 2007年第3期56卷 369-383页

作者： Phu, H. X. Inst Math Hanoi Vietnam

This article deals with some properties of the global minimizer set G(Q), the local minimizer set L-Q, and the stationary point set S-Q to the quadratic programming problem (Q) of minimizing the function f(x) =(1/2)x(T)Ax + b(T)x on the polyhedron D = {x is an element of R-n vertical bar C(i)x >= d(i), i is an element of I}, where A is an element of R-nxn, b is an element of R-n, d is an element of R-m, C-i(T) is an element of R-n, i is an element of I = {1, 2, ..., m}. In particular, we investigate the intersection of these solution sets with faces (D) over bar (J) = {x is an element of R-n vertical bar C(i)x >= d(i) for i is an element of J, C(i)x >= d(i) for i is an element of I\J} and pseudofaces D-J = {x is an element of R-n vertical bar C(i)x >= d(i) for i is an element of J, C(i)x = d(i) for i is an element of I\J}, where J subset of I. Some selected results are the following. If G(Q) boolean AND D-J not equal 0 then G(Q) boolean AND D-J and G(Q) boolean AND (D) over bar (J) are relatively affine in the following sense: G(Q) boolean AND D-J = aff(G(Q) boolean AND D-J) boolean AND D-J and G(Q) boolean AND (D) over bar (J) = aff(G(Q) boolean AND (D) over bar (J)) boolean AND D. If L-Q boolean AND D-J not equal 0 then L-Q boolean AND D-J is open relative to aff(L-Q boolean AND (D) over bar (J)) boolean AND D-J, L-Q boolean AND (D) over bar (J) is open relative to aff(L-Q boolean AND (D) over bar (J)) boolean AND D-J and L-Q boolean AND (D) over bar (J) are convex. If G(Q) boolean AND D-J not equal 0 then each stationary point (in particular, each local minimizer) in (D) over bar (J) is a global minimizer. If x(0) is an element of L-Q boolean AND D-J, x(1) is an element of S-Q boolean AND (D) over bar (J), and x(0) not equal x(1), then [x(0), x(1)) subset of L-Q boolean AND D-J subset of L-Q. Let B-m,B-n and C-m,C-n denote the maximal number of nonempty faces and the maximal cardinality of an antichain of nonempty faces of a polyhedron defined as intersection of

关键词： quadratic programming problem solution set global minimizer set local minimizer set stationary point set Kuhn-Tucker point

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Optimising the combined source and channel coding of a discrete communication system

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IEE PROCEEDINGS-COMMUNICATIONS 2005年第3期152卷 282-287页

作者： Miri, A Hons, E Khandani, AK Univ Ottawa Sch Informat Technol & Engn Ottawa ON K1N 6N5 Canada Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

The problem of optimising the structure of the encoder/decoder pair in a discrete communication system, with an additive distortion measure, is formulated in terms of a quadratic programming (QP) problem. This new formulation benefits from the following special features: it optimises the joint effects of the source/channel coding on the end-to-end distortion;and the encoder and the decoder structures are not restricted to being the inverse of each other. A method which obtains an epsilon-minimiser approximation of an optimum point of a general QP problem is discussed. Some simulation results based on this method are also given.

关键词： combined source-channel coding optimisation optimisation quadratic programming encoder/decoder pair additive distortion measure end-to-end distortion discrete communication system Optimisation techniques distortion QP problem optimum point Codes quadratic programming problem combined source-channel coding vector quantisation ɛ-minimiser approximation

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Dual possibilistic regression analysis using support vector networks

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FUZZY SETS AND SYSTEMS 2020年 387卷 1-34页

作者： Hao, Pei-Yi Natl Kaohsiung Univ Sci & Technol Dept Informat Management 415 Chien Kung Rd Kaohsiung 807 Taiwan

This study proposes a novel and efficient dual regression model for possibilistic regression analysis that incorporates the principles of support vector machine (SVM) theory. The dual regression model, which comprises an upper model and a lower model, approximates the observed fuzzy phenomena from the outside and inside directions, respectively, such that the inclusion relationship between those two models holds. The proposed dual regression model better explains the inherent vagueness that exists in a given dataset. It provides the outer and inner bounds for the estimated vagueness region, and allows an estimation of the degree of confidence in the predicted fuzzy output. Using the principles for a twin support vector machine (TSVM), the upper- and lower models are estimated by solving two smaller SVM-type quadratic programming problems (QPPs), instead of a single larger QPP. This strategy significantly increases the learning speed for the proposed algorithm. The structural risk minimization principle of SVM makes the proposed method to yield better generalization ability. The kernel function method offers a model-independent framework for the proposed dual regression model. This paper focuses on the class of radial kernels, which enables the proposed method to conquer the problem of increasing spreads. The radial kernel also gives the proposed method a unified framework that allows both crisp and fuzzy inputs. The experimental results verify the effectiveness and efficiency of the proposed method. In comparison with previous SVM-based dual regression model, the proposed approach significantly improves the sparsity, prediction speed, and training speed. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Fuzzy regression analysis Dual regression models Trapezoid fuzzy numbers Support vector machines Support vector regression machines quadratic programming problem

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Nonlinear temperature regulation of solar collectors with a fast adaptive polytopic LPV MPC formulation

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SOLAR ENERGY 2020年 209卷 214-225页

作者： Pipino, Hugo A. Morato, Marcelo M. Bernardi, Emanuel Adam, Eduardo J. Normey-Rico, Julio E. Univ Tecnol Nacl Appl Control & Embedded Syst Res Grp AC&ES RG San Francisco Argentina Univ Fed Santa Catarina Dept Automacao & Sistemas Renewable Energy Res Grp GPER Florianopolis SC Brazil Univ Nacl Litoral Fac Ingn Quim Santa Fe Argentina

Temperature control in solar collectors is a nonlinear problem: the dynamics of temperature rise vary according to the fluid flowing through the collector and to the temperature gradient along the collector area. In this way, this work investigates the formulation of a Model Predictive Control (MPC) application developed within a Linear Parameter Varying (LPV) formalism, which serves as a model of the solar collector process. The proposed system is an adaptive MPC, developed with terminal set constraints and considering the scheduling polytope of the model. At each instant, two quadratic programming (QPs) programs are solved: the first considers a backward horizon of N steps to find a virtual model-process tuning variable that defines the best LTI prediction model, considering the vertices of the polytopic system;then, the second QP uses this LTI model to optimize performances along a forward horizon of N steps. The paper ends with a realistic solar collector simulation results, comparing the proposed MPC to other techniques from the literature (linear MPC and robust tube-MPC). Discussions regarding the results, the design procedure and the computational effort for the three methods are presented. It is shown how the proposed MPC design is able to outrank these other standard methods in terms of reference tracking and disturbance rejection.

关键词： Model predictive control Linear parameter varying systems quadratic programming problem Tube MPC Solar collector

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Cooperative Game Theory-Based Optimal Angular Momentum Management of Hybrid Attitude Control Actuator

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IEEE ACCESS 2019年 7卷 6853-6865页

作者： Wu, Yunhua Zheng, Mohong He, Mengjie Zhang, Dawei He, Wei Hua, Bing Chen, Zhiming Wang, Feng Nanjing Univ Aeronaut & Astronaut Sch Astronaut Nanjing 210016 Jiangsu Peoples R China Harbin Inst Technol Sch Astronaut Harbin 150010 Heilongjiang Peoples R China CAST Inst Spacecraft Syst Engn Beijing 100094 Peoples R China Shanghai Electromech Engn Inst Shanghai 201109 Peoples R China

The next-generation space missions, such as the space moving target tracking mission and the agile attitude maneuvering mission and so on, propose a high requirement on spacecraft attitude control system. For such missions, hybrid attitude control actuators consisting of control moment gyro and reaction wheel, which can not only offer large control torque but also achieve high control precision, is the best alternative choice. For this hybrid actuator system, the angular momentum management is vital. To handle the momentum management problem, an optimal angular momentum strategy based on cooperative game theory is proposed. The cooperative game model is constructed according to the quadratic programming problem to achieve the minimization of control moment gyro gimbal angular speed and reaction wheel angular acceleration. The proposed cooperative game theory steering logic has overcome the control moment gyro singular problem and reaction wheel saturation problem of the hybrid system. In addition, the energy cost of the hybrid actuator system is reduced. Five groups of simulation scenarios are carried out to demonstrate the effectiveness of the proposed steering logic.

关键词： Agile attitude control hybrid actuator cooperative game theory quadratic programming problem angular momentum management

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Two-parameter Kautz network-based LTV-MPC for non-linear standalone micro-grid control

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IET RENEWABLE POWER GENERATION 2020年第12期14卷 2221-2231页

作者： Puvvula, Vidyasagar Verma, Pranjal Pragya Kesanakurthy, Shanti Swarup Indian Inst Technol Dept Elect Engn Chennai Tamil Nadu India

This study proposes a novel linear time-variant model predictive controller (LTV-MPC) for the centralised control of non-linear standalone micro-grids. At each sample, within the prediction horizon, LTV-MPC linearises the non-linear micro-grid model around the state and input reference trajectories resulting in a linear time-variant (LTV) model. The LTV model is used for predicting the forced response of the micro-grid. The natural response is predicted by solving the non-linear model along the state and input reference trajectories. An optimal control problem for the LTV-MPC is formulated using the complete predicted response, which is a quadratic programming problem instead of a non-convex non-linear programming problem. The quadratic programming problem is solved online at each sample to generate the optimal control trajectories within the control horizon. The study recommends the use of two-parameter orthonormal Kautz networks in the LTV-MPC design for the control trajectories approximation. The approximation drastically reduces the number of optimising variables in the optimal control problem without compromising LTV-MPC performance. A standalone eight bus micro-grid with one synchronous distributed generator (DG) and one photovoltaic-DG is considered for the analysis. The LTV-MPC performance is assessed for the different load disturbance and source intermittency scenarios. The results are compared with the existing MPC designs.

关键词： distributed power generation predictive control optimal control time-varying systems quadratic programming approximation theory linear systems linear programming nonlinear control systems parameter Kautz network-based LTV-MPC nonlinear standalone microgrid control linear time-variant model centralised control nonlinear standalone microgrids prediction horizon microgrid model LTV model forced response natural response nonlinear model input reference trajectories optimal control problem complete predicted response quadratic programming problem nonconvex nonlinear programming problem optimal control trajectories control horizon two-parameter orthonormal Kautz networks LTV-MPC design control trajectories approximation LTV-MPC performance standalone eight bus microgrid MPC designs

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Constrained generalised minimum variance controller design using projection-based recurrent neural network

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IET CONTROL THEORY AND APPLICATIONS 2017年第2期11卷 143-154页

作者： Toshani, Hamid Farrokhi, Mohammad Alipouri, Yousef Iran Univ Sci & Technol Sch Elect Engn Farjam St Tehran 16846 Iran

In this study, a generalised minimum variance control (GMVC) method using the projection-based recurrent neural network (PRNN) is proposed to minimise the error variance in the output of the non-linear plant. One the main drawbacks of the conventional GMVC approaches is the lack of a systematic procedure to deal with the input constraints. In this study, the PRNN is employed for incorporating the input constraints to the minimum variance index. This network is based on the optimality conditions of a constrained problem and is designed using projection theorem. To formulate the proposed approach, by considering an ARMAX model of the system and converting the cost function to a quadratic programming problem, the dynamics and output equations of the PRNN is obtained. The stability and global convergence of the PRNN is analytically shown. Moreover, suitable conditions for the weighting matrices of the cost function are determined to ensure the closed-loop stability. The proposed control method is applied to the non-linear quadruple tank and a comparative analysis between MVC, GMVC and the proposed approach is performed.

关键词： control system synthesis recurrent neural nets neurocontrollers nonlinear control systems optimal control quadratic programming matrix algebra convergence closed loop systems stability constrained generalised minimum variance controller design GMVC method projection-based recurrent neural network PRNN error variance minimisation nonlinear plant systematic procedure minimum variance index optimality conditions ARMAX model cost function quadratic programming problem weighting matrices closed-loop stability nonlinear quadruple tank comparative analysis global convergence

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A structural information-based twin-hypersphere support vector machine classifier

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2017年第1期8卷 295-308页

作者： Peng, Xinjun Kong, Lingyan Chen, Dongjing Shanghai Normal Univ Dept Math Shanghai 200234 Peoples R China Sci Comp Key Lab Shanghai Univ Shanghai 200234 Peoples R China

Twin-hypersphere support vector machine (THSVM) for binary pattern recognition aims at generating two hyperspheres in the feature space such that each hypersphere contains as many as possible samples in one class and is as far as possible from the other one. THSVM has a fast learning speed since it solves two small sized support vector machine (SVM)-type quadratic programming problems (QPPs). However, it only simply considers the prior class-based structural information in the optimization problems. In this paper, a structural information-based THSVM (STHSVM) classifier for binary classification is presented. This proposed STHSVM focuses on the cluster-based structural information of the corresponding class in each optimization problem, which is vital for designing a good classifier in different real-world problems. In addition, it also leads to a fast learning speed since this STHSVM solves a series of smaller-sized QPPs compared with THSVM. Experimental results demonstrate that STHSVM is superior in generalization performance to other classifiers.

关键词： Binary classification quadratic programming problem Twin-hypersphere support vector machine Structural information

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