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multi-parametric programming-based energy control strategy for parallel hybrid heavy-duty truck

INTERNATIONAL JOURNAL OF HEAVY VEHICLE SYSTEMS 2016年第3期23卷 244-263页

作者： Agostoni, Stefano Cheli, Federico Mapelli, Ferdinando Luigi Chen Tao Tarsitano, Davide Luo Yugong Tang Yuhuan Politecn Milan Dept Mech Engn Via Masa 1 I-20161 Milan Italy Tsinghua Univ Dept Automot Engn Beijing 100084 Peoples R China

This paper develops an energy control strategy based on a multi-parametric programming control algorithm for a parallel hybrid heavy-duty truck. First, based on the non-linear characteristics and multiple working modes of the heavy-duty truck, a set of piecewise linear models including longitudinal dynamics, engine and electric motor are established and synthesised to a mixed logical dynamic (MLD) model. Then, an objective function for achieving the best fuel economy is formulated and the optimal control law is analytically calculated using a multi-parametric programming algorithm. Finally, the simulation of the hybrid heavy-duty truck model is conducted under UDDSHDV drive cycle and the result shows that the multi-parametric programming energy control strategy can effectively improve fuel economy compared to the traditional heavy-duty truck simulation model with the same engine.

关键词： parallel hybrid heavy-duty truck energy control strategy multi-parametric programming mixed logical dynamic (MLD) model

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multi-parametric programming Approach for Data Link of UAS Based on State Machine

Multi-parametric Programming Approach for Data Link of UAS B...

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International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration

作者： Huang Wenqian Ding Wenrui Liu Chunhui Beihang Univ Inst Unmanned Aerial Vehicle Beijing Peoples R China

ISBN: (纸本)9781467383127

With the huge development of Unmanned Aerial Vehicle (UAV) in both military and civilian applications, the Unmanned Aircraft Systems (UAS) are required to adapt to complex environment and various missions. The adaptation technologies for UAS include adaptive modulation method, adaptive coding method, adaptive antenna diversity or power and adaptive parametric of data link. In this paper, we proposed a multi-parametric programming approach for data link of communication system in UAV based on state machine. We also present the state transition design for the state machine and describe the transition in detail according to different parameters of data link. In addition, the implementation of the state machine is presented.

关键词： UAV data link adaptation multi-parametric programming state machine

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A multi-parametric programming Based Analytic Method to Compute Consumer Offer Curve for Reserves

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Journal of Modern Power Systems and Clean Energy 2022年第2期10卷 542-546页

作者： Weiye Zheng David J.Hill Wenchuan Wu the School of Electrical Power Engineering South China University of TechnologyGuangzhouChina the Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina the Department of Electrical Engineering Tsinghua UniversityBeijingChina

Abstract-An analytic method is proposed to compute the price-reserve offer curve at the consumer level in hierarchical direct load *** convexification of the consumer reserve provision is examined,and the analytic expression of the optimal solution within each critical region is ***,based on multi-parametric programming,a combinatorial enumeration method in conjunction with efficient reduction and pruning strategy is proposed to compute the optimal response of consumers in the whole price *** tests along with an application example in the bi-level aggregator pricing problem demonstrate the merit of this method.

关键词： Direct load control multi-parametric programming price-reserve offer curve analytic solution

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A branch-and-bound multi-parametric programming approach for non-convex multilevel optimization with polyhedral constraints

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JOURNAL OF GLOBAL OPTIMIZATION 2016年第4期64卷 745-764页

作者： Kassa, Abay Molla Kassa, Semu Mitiku Univ Addis Ababa Dept Chem & Bio Engn Addis Ababa Inst Technol POB 385 Addis Ababa Ethiopia Univ Addis Ababa Dept Math POB 1176 Addis Ababa Ethiopia

In this paper we develop a general but smooth global optimization strategy for nonlinear multilevel programming problems with polyhedral constraints. At each decision level successive convex relaxations are applied over the non-convex terms in combination with a multi-parametric programming approach. The proposed algorithm reaches the approximate global optimum in a finite number of steps through the successive subdivision of the optimization variables that contribute to the non-convexity of the problem and partitioning of the parameter space. The method is implemented and tested for a variety of bilevel, trilevel and fifth level problems which have non-convexity formulation at their inner levels.

关键词： multilevel optimization multi-parametric programming Convex relaxation

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On multi-parametric programming and its applications in process systems engineering

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2016年 116卷 61-82页

作者： Oberdieck, Richard Diangelakis, Nikolaos A. Nascu, Ioana Papathanasiou, Maria M. Sun, Muxin Auraamidou, Styliani Pistikopoulos, Efstratios N. Imperial Coll London Dept Chem Engn London England Texas A&M Univ Dept Chem Engn College Stn TX 77843 USA

In multi-parametric programming, an optimization problem is solved for a range and as a function of multiple parameters. In this review, we discuss the main developments of multi-parametric programming over the last two decades from a theoretical, algorithmic and application perspective. In addition, we provide an opinionated view of the future research directions in multi-parametric programming. (C) 2016 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： multi-parametric programming multi-parametric mixed-integer programming multi-parametric dynamic optimization

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Adjustable robust optimization through multi-parametric programming

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OPTIMIZATION LETTERS 2020年第4期14卷 873-887页

作者： Avraamidou, Styliani Pistikopoulos, Efstratios N. Texas A&M Univ Texas A&M Energy Inst College Stn TX 77843 USA

Adjustable robust optimization (ARO) involves recourse decisions (i.e. reactive actions after the realization of the uncertainty, 'wait-and-see') as functions of the uncertainty, typically posed in a two-stage stochastic setting. Solving the general ARO problems is challenging, therefore ways to reduce the computational effort have been proposed, with the most popular being the affine decision rules, where 'wait-and-see' decisions are approximated as affine adjustments of the uncertainty. In this work we propose a novel method for the derivation of generalized affine decision rules for linear mixed-integer ARO problems through multi-parametric programming, that lead to the exact and global solution of the ARO problem. The problem is treated as a multi-level programming problem and it is then solved using a novel algorithm for the exact and global solution of multi-level mixed-integer linear programming problems. The main idea behind the proposed approach is to solve the lower optimization level of the ARO problem parametrically, by considering 'here-and-now' variables and uncertainties as parameters. This will result in a set of affine decision rules for the 'wait-and-see' variables as a function of 'here-and-now' variables and uncertainties for their entire feasible space. A set of illustrative numerical examples are provided to demonstrate the potential of the proposed novel approach.

关键词： Adjustable robust optimization multi-parametric programming Tri-level programming

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From multi-parametric programming theory to MPC-on-a-chip multi-scale systems applications

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COMPUTERS & CHEMICAL ENGINEERING 2012年 47卷 57-66页

作者： Pistikopoulos, Efstratios N. Univ London Imperial Coll Sci Technol & Med Dept Chem Engn Ctr Proc Syst Engn London SW7 2AZ England

An overview of multi-parametric programming and control is presented with emphasis on historical milestones, novel developments in the theory of multi-parametric programming and explicit MPC as well as their application to the design of advanced controller for complex multi-scale systems. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： multi-parametric programming Explicit/multi-parametric MPC MPC-on-a-chip Fast MPC multi-scale applications

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Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

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AUTOMATICA 2011年第8期47卷 1638-1645页

作者： Kouramasa, K. I. Faisca, N. P. Panos, C. Pistikopoulos, E. N. Univ London Imperial Coll Sci Technol & Med Dept Chem Engn Ctr Proc Syst Engn London SW7 2AZ England AspenTech Reading RG2 6DT Berks England

This work presents a new algorithm for solving the explicit/multi-parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Explicit Model Predictive Control Model Predictive Control multi-parametric control multi-parametric programming Dynamic programming

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Sliding Mode Predictive Control of a Magnetic Levitation System Employing multi-parametric programming

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IEEE LATIN AMERICA TRANSACTIONS 2017年第2期15卷 239-248页

作者： Assis, P. A. Q. Galvao, R. K. H. ITA Sao Paulo Brazil ITA Div Engn Eletron Sao Paulo Brazil

This paper is concerned with the application of sliding mode predictive control (SMPC) on a laboratory-scale magnetic levitation system. The main contribution consists of the use of multi-parametric programming to reduce the computational workload required for real-time implementation. For comparison, a conventional sliding mode controller was also employed. The task consisted of tracking a reference signal in the presence of control rate constraints. In this scenario, the sliding mode controller was not able to maintain closed-loop stability, whereas the SMPC controller successfully performed the tracking task, with proper satisfaction of the constraints.

关键词： Model Predictive Control Sliding Mode Control Sliding Mode Predictive Control multi-parametric programming Magnetic Levitation

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Decentralized Dynamic Economic Dispatch for Integrated Transmission and Active Distribution Networks Using multi-parametric programming

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IEEE TRANSACTIONS ON SMART GRID 2018年第5期9卷 4983-4993页

作者： Lin, Chenhui Wu, Wenchuan Chen, Xin Zheng, Weiye Tsinghua Univ Dept Elect Engn State Key Lab Power Syst Beijing 100084 Peoples R China

As large scale distributed energy resources are integrated into distribution networks, coordinated dynamic economic dispatch (DED) for integrated transmission and distribution networks is becoming essential. In this paper, we describe a transmission and distribution network coordinated DED model and propose an efficient decentralized method to solve this problem using multi-parametric quadratic programming In the proposed method, only boundary variables are exchanged between transmission and distribution networks so that the privacy between different operators can he guaranteed. A revised procedure is developed based on the characteristics of the distribution network problem, which can significantly accelerate the iteration. An effective method for dealing with degeneracy in multi-parametric programming is also proposed. Numerical tests demonstrate that the proposed method can achieve a global optimal solution and that the coordinated DED method can provide additional economic benefits compared with the isolated economic dispatch method. Furthermore, the computational performance of the proposed method is far superior to some popular decentralized methods in terms of both iteration number and computation time.

关键词： Decentralized optimization dynamic economic dispatch integrated transmission and distribution network multi-parametric programming

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