Wei Zhao, Mohit Bhola, Morten K. Ebbesen, Torben Ole Andersen
When a hydraulic cylinder connects two chambers directly to one or two hydraulic pumps driven by electric servo motors without any control valve in between, it can be called a motor-controlled hydraulic cylinder (MCC). Unlike valve-controlled cylinders, MCCs have no valve throttling, which significantly increases the energy efficiency. Among different MCC topologies, the two-motor-two-pump (2M2P) MCC has several advantages, such as cylinder pressure control and no mode switch oscillations. However, due to state coupling when controlling both piston position and minimum cylinder chamber pressure, the 2M2P MCC is a multi-input-multi-output (MIMO) system that usually requires advanced MIMO controller analysis and design. This paper presents a control algorithm for a 2M2P MCC with the minimum cylinder pressure control and passive load-holding function. This control algorithm is tested on a single-boom crane characterized by overrunning loads. It is designed based on the analysis of the system characteristics, requiring no MIMO controller analysis and design. A non-linear model of a single-boom crane driven by the proposed 2M2P MCC is created in MATLAB/Simulink and experimentally validated. Feedback controllers are designed and verified via simulations to realize position control, minimum cylinder pressure control, and load-holding under standstill command. For a given load and speed profile, the hydraulic system efficiency during pumping and motoring mode is 55-60 % and 20-25 %, respectively. The system’s overall efficiency can be enhanced with electrical regenerative drives, which feeds the generated power from potential energy to the grid or battery and reused in the next working cycle. The experimental results presented in this paper verifies the efficacy of the proposed control algorithm and demonstrates its superior performance in achieving the desired system response under various operating conditions.
{"title":"A Novel Control Design for Realizing Passive Load-Holding Function on a Two-Motor-Two-Pump Motor-Controlled Hydraulic Cylinder","authors":"Wei Zhao, Mohit Bhola, Morten K. Ebbesen, Torben Ole Andersen","doi":"10.4173/mic.2023.3.3","DOIUrl":"https://doi.org/10.4173/mic.2023.3.3","url":null,"abstract":"When a hydraulic cylinder connects two chambers directly to one or two hydraulic pumps driven by electric servo motors without any control valve in between, it can be called a motor-controlled hydraulic cylinder (MCC). Unlike valve-controlled cylinders, MCCs have no valve throttling, which significantly increases the energy efficiency. Among different MCC topologies, the two-motor-two-pump (2M2P) MCC has several advantages, such as cylinder pressure control and no mode switch oscillations. However, due to state coupling when controlling both piston position and minimum cylinder chamber pressure, the 2M2P MCC is a multi-input-multi-output (MIMO) system that usually requires advanced MIMO controller analysis and design. This paper presents a control algorithm for a 2M2P MCC with the minimum cylinder pressure control and passive load-holding function. This control algorithm is tested on a single-boom crane characterized by overrunning loads. It is designed based on the analysis of the system characteristics, requiring no MIMO controller analysis and design. A non-linear model of a single-boom crane driven by the proposed 2M2P MCC is created in MATLAB/Simulink and experimentally validated. Feedback controllers are designed and verified via simulations to realize position control, minimum cylinder pressure control, and load-holding under standstill command. For a given load and speed profile, the hydraulic system efficiency during pumping and motoring mode is 55-60 % and 20-25 %, respectively. The system’s overall efficiency can be enhanced with electrical regenerative drives, which feeds the generated power from potential energy to the grid or battery and reused in the next working cycle. The experimental results presented in this paper verifies the efficacy of the proposed control algorithm and demonstrates its superior performance in achieving the desired system response under various operating conditions.","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135838289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Schäle, Martin Fodstad Stølen, Erik Kyrkjebø
{"title":"Programming Fine Manufacturing Tasks on Collaborative Robots: A Case Study on Industrial Gluing","authors":"Daniel Schäle, Martin Fodstad Stølen, Erik Kyrkjebø","doi":"10.4173/mic.2023.4.1","DOIUrl":"https://doi.org/10.4173/mic.2023.4.1","url":null,"abstract":"","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134982831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thomas Farsakoglou, Henrik C. Pedersen, Morten K. Ebbesen, Torben Ole Andersen
{"title":"Improving Energy Efficiency and Response Time of an Offshore Winch Drive with Digital Displacement Motors","authors":"Thomas Farsakoglou, Henrik C. Pedersen, Morten K. Ebbesen, Torben Ole Andersen","doi":"10.4173/mic.2023.3.2","DOIUrl":"https://doi.org/10.4173/mic.2023.3.2","url":null,"abstract":"","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135749253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Animals and other organisms in wild populations may adjust to climate change by means of plasticity and evolution, and it is an important task to find the contributions from each of these effects. Attempts to solve this disentanglement problem by use of best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) methods, as borrowed from the field of domestic breeding, have been criticized because of errors in the variances of the predicted random effects. A primary purpose of this article is to show how the problem can be solved by use of BLUP in a prediction error method (PEM), borrowed from the well-established engineering system identification discipline. The PEM approach is first to collect environmental input data u t and mean phenotypic output data y t , as well as individual phenotypic and fitness data, for consecutive generations from t = 1 to T . A reaction norm model of the evolutionary system is then used to find predictions (cid:98) y t , and the parameters in this model, together with environmental reference values and initial state variables, are finally tuned such that (cid:80) Tt =1 (cid:16) y t − (cid:98) y t (cid:17) 2 is minimized. The main contribution is the use a dynamical BLUP model in a BLUP/PEM method for parameter estimation and mean reaction norm trait predictions. The model is dynamical in the sense that the incidence matrix in an underlying linear mixed model, as well as the corresponding residual covariance matrix, are functions of time. For comparisons, a selection gradient prediction model as presented in Ergon (2022a,b) is also used in a GRAD/PEM method. The advantages of the BLUP/PEM method are that it can utilize genetic relationship information, and that it produces better estimates of environmental reference values. The treatment is limited to multiple-input single-output (MISO) systems. Generations are assumed to be non-overlapping. Simulation examples show that BLUP/PEM may find good estimates of environmental reference values and initial state variables, as well as good mean reaction norm trait predictions. Details for use of additional fixed effects, as well as appropriate methods for model validation remain to be worked out.
{"title":"Microevolutionary system identification and climate response predictions by use of BLUP prediction error method","authors":"Rolf Ergon","doi":"10.4173/mic.2023.3.1","DOIUrl":"https://doi.org/10.4173/mic.2023.3.1","url":null,"abstract":"Animals and other organisms in wild populations may adjust to climate change by means of plasticity and evolution, and it is an important task to find the contributions from each of these effects. Attempts to solve this disentanglement problem by use of best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) methods, as borrowed from the field of domestic breeding, have been criticized because of errors in the variances of the predicted random effects. A primary purpose of this article is to show how the problem can be solved by use of BLUP in a prediction error method (PEM), borrowed from the well-established engineering system identification discipline. The PEM approach is first to collect environmental input data u t and mean phenotypic output data y t , as well as individual phenotypic and fitness data, for consecutive generations from t = 1 to T . A reaction norm model of the evolutionary system is then used to find predictions (cid:98) y t , and the parameters in this model, together with environmental reference values and initial state variables, are finally tuned such that (cid:80) Tt =1 (cid:16) y t − (cid:98) y t (cid:17) 2 is minimized. The main contribution is the use a dynamical BLUP model in a BLUP/PEM method for parameter estimation and mean reaction norm trait predictions. The model is dynamical in the sense that the incidence matrix in an underlying linear mixed model, as well as the corresponding residual covariance matrix, are functions of time. For comparisons, a selection gradient prediction model as presented in Ergon (2022a,b) is also used in a GRAD/PEM method. The advantages of the BLUP/PEM method are that it can utilize genetic relationship information, and that it produces better estimates of environmental reference values. The treatment is limited to multiple-input single-output (MISO) systems. Generations are assumed to be non-overlapping. Simulation examples show that BLUP/PEM may find good estimates of environmental reference values and initial state variables, as well as good mean reaction norm trait predictions. Details for use of additional fixed effects, as well as appropriate methods for model validation remain to be worked out.","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135502219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1007/978-3-031-26504-4_46
Peter Greistorfer, Rostislav Staněk, V. Maniezzo
{"title":"A Tabu Search Matheuristic for the Generalized Quadratic Assignment Problem","authors":"Peter Greistorfer, Rostislav Staněk, V. Maniezzo","doi":"10.1007/978-3-031-26504-4_46","DOIUrl":"https://doi.org/10.1007/978-3-031-26504-4_46","url":null,"abstract":"","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"13 1","pages":"544-553"},"PeriodicalIF":1.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80446946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1007/978-3-031-26504-4_31
Daniel Cuellar-Usaquén, Camilo Gomez, M. Ulmer, D. Álvarez-Martínez
{"title":"Decision Support for Agri-Food Supply Chains in the E-Commerce Era: The Inbound Inventory Routing Problem with Perishable Products","authors":"Daniel Cuellar-Usaquén, Camilo Gomez, M. Ulmer, D. Álvarez-Martínez","doi":"10.1007/978-3-031-26504-4_31","DOIUrl":"https://doi.org/10.1007/978-3-031-26504-4_31","url":null,"abstract":"","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"1 1","pages":"436-448"},"PeriodicalIF":1.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79079881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1007/978-3-031-26504-4_9
Thé Van Luong, É. Taillard
{"title":"Unsupervised Machine Learning for the Quadratic Assignment Problem","authors":"Thé Van Luong, É. Taillard","doi":"10.1007/978-3-031-26504-4_9","DOIUrl":"https://doi.org/10.1007/978-3-031-26504-4_9","url":null,"abstract":"","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"83 1","pages":"118-132"},"PeriodicalIF":1.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78215662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1007/978-3-031-26504-4_2
P. Festa, F. Guerriero, M. G. Resende, Edoardo Scalzo
{"title":"A BRKGA with Implicit Path-Relinking for the Vehicle Routing Problem with Occasional Drivers and Time Windows","authors":"P. Festa, F. Guerriero, M. G. Resende, Edoardo Scalzo","doi":"10.1007/978-3-031-26504-4_2","DOIUrl":"https://doi.org/10.1007/978-3-031-26504-4_2","url":null,"abstract":"","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"2014 1","pages":"17-29"},"PeriodicalIF":1.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73891186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1007/978-3-031-26504-4_44
Javier Yuste, Eduardo G. Pardo, A. Duarte
{"title":"Variable Neighborhood Descent for Software Quality Optimization","authors":"Javier Yuste, Eduardo G. Pardo, A. Duarte","doi":"10.1007/978-3-031-26504-4_44","DOIUrl":"https://doi.org/10.1007/978-3-031-26504-4_44","url":null,"abstract":"","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"15 1","pages":"531-536"},"PeriodicalIF":1.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74986080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1007/978-3-031-26504-4_18
N. Aslimani, E. Talbi, R. Ellaia
{"title":"Tchebycheff Fractal Decomposition Algorithm for Bi-objective Optimization Problems","authors":"N. Aslimani, E. Talbi, R. Ellaia","doi":"10.1007/978-3-031-26504-4_18","DOIUrl":"https://doi.org/10.1007/978-3-031-26504-4_18","url":null,"abstract":"","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"18 1","pages":"246-259"},"PeriodicalIF":1.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80039413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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