{"title":"A priori and a posteriori error estimates of finite‐element approximations for elliptic optimal control problem with measure data","authors":"Pratibha Shakya, R. K. Sinha","doi":"10.1002/oca.2476","DOIUrl":null,"url":null,"abstract":"We analyze both a priori and a posteriori error analysis of finite‐element method for elliptic optimal control problems with measure data in a bounded convex domain in Rd (d = 2or3). The solution of the state equation of such type of problems exhibits low regularity due to the presence of measure data, which introduces some difficulties for both theory and numerics of the finite‐element method. We first prove the existence, uniqueness, and regularity of the solution to the optimal control problem. To discretize the control problem, we use continuous piecewise linear elements for the approximations of the state and co‐state variables, whereas piecewise constant functions are used for the control variable. We derive a priori error estimates of order O(h2−d2) for the state, co‐state, and control variables in the L2‐norm. Further, global a posteriori upper bounds for the state, co‐state, and control variables in the L2‐norm are established. Moreover, local lower bounds for the errors in the state and co‐state variables and a global lower bound for the error in the control variable are obtained in the case of two space dimensions (d = 2). Numerical experiments are provided, which support our theoretical results.","PeriodicalId":54672,"journal":{"name":"Optimal Control Applications & Methods","volume":"40 1","pages":"241 - 264"},"PeriodicalIF":2.0000,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/oca.2476","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optimal Control Applications & Methods","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1002/oca.2476","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 3
Abstract
We analyze both a priori and a posteriori error analysis of finite‐element method for elliptic optimal control problems with measure data in a bounded convex domain in Rd (d = 2or3). The solution of the state equation of such type of problems exhibits low regularity due to the presence of measure data, which introduces some difficulties for both theory and numerics of the finite‐element method. We first prove the existence, uniqueness, and regularity of the solution to the optimal control problem. To discretize the control problem, we use continuous piecewise linear elements for the approximations of the state and co‐state variables, whereas piecewise constant functions are used for the control variable. We derive a priori error estimates of order O(h2−d2) for the state, co‐state, and control variables in the L2‐norm. Further, global a posteriori upper bounds for the state, co‐state, and control variables in the L2‐norm are established. Moreover, local lower bounds for the errors in the state and co‐state variables and a global lower bound for the error in the control variable are obtained in the case of two space dimensions (d = 2). Numerical experiments are provided, which support our theoretical results.
期刊介绍:
Optimal Control Applications & Methods provides a forum for papers on the full range of optimal and optimization based control theory and related control design methods. The aim is to encourage new developments in control theory and design methodologies that will lead to real advances in control applications. Papers are also encouraged on the development, comparison and testing of computational algorithms for solving optimal control and optimization problems. The scope also includes papers on optimal estimation and filtering methods which have control related applications. Finally, it will provide a focus for interesting optimal control design studies and report real applications experience covering problems in implementation and robustness.