{"title":"具有均衡约束条件的最优控制问题的非内部点延续方法","authors":"Kangyu Lin, Toshiyuki Ohtsuka","doi":"10.1016/j.automatica.2024.111940","DOIUrl":null,"url":null,"abstract":"<div><div>This study presents a numerical method for the optimal control problem with equilibrium constraints (OCPEC). It is extremely difficult to solve OCPEC owing to the absence of constraint regularity and strictly feasible interior points. To solve OCPEC efficiently, we first relax the discretized OCPEC to recover the constraint regularity and then map its Karush–Kuhn–Tucker (KKT) conditions into a parameterized system of equations. Subsequently, we solve the parameterized system using a novel two-stage solution method called the non-interior-point continuation method. In the first stage, a non-interior-point method is employed to find an initial solution, which solves the parameterized system using Newton’s method and globalizes convergence using a dedicated merit function. In the second stage, a predictor–corrector continuation method is utilized to track the solution trajectory as a function of the parameter, starting at the initial solution. The proposed method regularizes the KKT matrix and does not enforce iterates to remain in the feasible interior, which mitigates the numerical difficulties in solving OCPEC. Convergence properties are analyzed under certain assumptions. Numerical experiments demonstrate that the proposed method can solve OCPEC while demanding remarkably less computation time than the interior-point method.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"171 ","pages":"Article 111940"},"PeriodicalIF":4.8000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A non-interior-point continuation method for the optimal control problem with equilibrium constraints\",\"authors\":\"Kangyu Lin, Toshiyuki Ohtsuka\",\"doi\":\"10.1016/j.automatica.2024.111940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study presents a numerical method for the optimal control problem with equilibrium constraints (OCPEC). It is extremely difficult to solve OCPEC owing to the absence of constraint regularity and strictly feasible interior points. To solve OCPEC efficiently, we first relax the discretized OCPEC to recover the constraint regularity and then map its Karush–Kuhn–Tucker (KKT) conditions into a parameterized system of equations. Subsequently, we solve the parameterized system using a novel two-stage solution method called the non-interior-point continuation method. In the first stage, a non-interior-point method is employed to find an initial solution, which solves the parameterized system using Newton’s method and globalizes convergence using a dedicated merit function. In the second stage, a predictor–corrector continuation method is utilized to track the solution trajectory as a function of the parameter, starting at the initial solution. The proposed method regularizes the KKT matrix and does not enforce iterates to remain in the feasible interior, which mitigates the numerical difficulties in solving OCPEC. Convergence properties are analyzed under certain assumptions. Numerical experiments demonstrate that the proposed method can solve OCPEC while demanding remarkably less computation time than the interior-point method.</div></div>\",\"PeriodicalId\":55413,\"journal\":{\"name\":\"Automatica\",\"volume\":\"171 \",\"pages\":\"Article 111940\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Automatica\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0005109824004345\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automatica","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0005109824004345","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
A non-interior-point continuation method for the optimal control problem with equilibrium constraints
This study presents a numerical method for the optimal control problem with equilibrium constraints (OCPEC). It is extremely difficult to solve OCPEC owing to the absence of constraint regularity and strictly feasible interior points. To solve OCPEC efficiently, we first relax the discretized OCPEC to recover the constraint regularity and then map its Karush–Kuhn–Tucker (KKT) conditions into a parameterized system of equations. Subsequently, we solve the parameterized system using a novel two-stage solution method called the non-interior-point continuation method. In the first stage, a non-interior-point method is employed to find an initial solution, which solves the parameterized system using Newton’s method and globalizes convergence using a dedicated merit function. In the second stage, a predictor–corrector continuation method is utilized to track the solution trajectory as a function of the parameter, starting at the initial solution. The proposed method regularizes the KKT matrix and does not enforce iterates to remain in the feasible interior, which mitigates the numerical difficulties in solving OCPEC. Convergence properties are analyzed under certain assumptions. Numerical experiments demonstrate that the proposed method can solve OCPEC while demanding remarkably less computation time than the interior-point method.
期刊介绍:
Automatica is a leading archival publication in the field of systems and control. The field encompasses today a broad set of areas and topics, and is thriving not only within itself but also in terms of its impact on other fields, such as communications, computers, biology, energy and economics. Since its inception in 1963, Automatica has kept abreast with the evolution of the field over the years, and has emerged as a leading publication driving the trends in the field.
After being founded in 1963, Automatica became a journal of the International Federation of Automatic Control (IFAC) in 1969. It features a characteristic blend of theoretical and applied papers of archival, lasting value, reporting cutting edge research results by authors across the globe. It features articles in distinct categories, including regular, brief and survey papers, technical communiqués, correspondence items, as well as reviews on published books of interest to the readership. It occasionally publishes special issues on emerging new topics or established mature topics of interest to a broad audience.
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