Point-to-Point Iterative Learning Control with Optimal Tracking Time Allocation:A Coordinate Descent Approach
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- 英文论文题名：Point-to-Point Iterative Learning Control with Optimal Tracking Time Allocation:A Coordinate Descent Approach
- 论文作者：Yiyang Chen ; Bing Chu ; Christopher T.Freeman
- 英文论文作者：Yiyang Chen ; Bing Chu ; Christopher T.Freeman ; Electronics and Computer Science ; University of Southampton
- 年：2017
- 作者机构：Electronics and Computer Science,University of Southampton;
- 英文论文关键词：iterative learning control ; optimization ; coordinate descent method
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TP273
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：312k
- 原文格式：D
- 会议级别：全国
摘要
Iterative learning control(ILC) is a high performance control technique for systems operating in a repetitive manner.A novel design methodology is developed in this paper to incorporate optimal tracking time allocation within the point-topoint ILC framework for discrete time systems. This leads to significant performance improvements compared to fixed time points(e.g. energy reduction). An optimization problem is formulated based on the point-to-point tracking requirement and the via-point temporal constraints. A two stage design framework is proposed to solve this problem, yielding an algorithm based on norm optimal ILC and the coordinate descent method, which automatically minimizes control effort while maintaining high performance tracking. The proposed algorithm is implemented on a gantry robot experimental test platform, with results verifying its practical effectiveness in the presence of model uncertainty.
Iterative learning control(ILC) is a high performance control technique for systems operating in a repetitive manner.A novel design methodology is developed in this paper to incorporate optimal tracking time allocation within the point-topoint ILC framework for discrete time systems. This leads to significant performance improvements compared to fixed time points(e.g. energy reduction). An optimization problem is formulated based on the point-to-point tracking requirement and the via-point temporal constraints. A two stage design framework is proposed to solve this problem, yielding an algorithm based on norm optimal ILC and the coordinate descent method, which automatically minimizes control effort while maintaining high performance tracking. The proposed algorithm is implemented on a gantry robot experimental test platform, with results verifying its practical effectiveness in the presence of model uncertainty.
Iterative learning control(ILC) is a high performance control technique for systems operating in a repetitive manner.A novel design methodology is developed in this paper to incorporate optimal tracking time allocation within the point-topoint ILC framework for discrete time systems. This leads to significant performance improvements compared to fixed time points(e.g. energy reduction). An optimization problem is formulated based on the point-to-point tracking requirement and the via-point temporal constraints. A two stage design framework is proposed to solve this problem, yielding an algorithm based on norm optimal ILC and the coordinate descent method, which automatically minimizes control effort while maintaining high performance tracking. The proposed algorithm is implemented on a gantry robot experimental test platform, with results verifying its practical effectiveness in the presence of model uncertainty.
引文
[1]L.Hladowski,K.Galkowski,Z.Cai,E.Rogers,C.T.Freeman,and P.L.Lewin,“Experimentally supported 2D systems based iterative learning control law design for error convergence and performance,”Control Engineering Practice,vol.18,pp.339–348,2010.
[2]M.Norrlof,“An adaptive iterative learning control algorithm with experiments on an industrial robot,”IEEE Transactions on Robotics and Automation,vol.19,no.2,pp.245–251,2002.
[3]X.Yu,Z.Xiong,D.Huang,and Y.Jiang,“Model-based iterative learning control for batch processes using generalized hinging hyperplanes,”Industrial&Engineering Chemistry Research,vol.52,no.4,pp.1627–1634,2013.
[4]J.H.Lee and K.S.Lee,“Iterative learning control applied to batch processes:An overview,”Control Engineering Practice,vol.15,pp.1306–1318,2007.
[5]C.T.Freeman,Control System Design for Electrical Stimulation in Upper Limb Rehabilitation.Springer International Publishing,2016.
[6]D.Bristow,M.Tharayil,and A.Alleyne,“A survey of iterative learning control,”Control Systems,IEEE,vol.26,no.3,pp.96–144,2006.
[7]C.T.Freeman,Z.Cai,E.Rogers,and P.L.Lewin,“Iterative learning control for multiple point-to-point tracking application,”IEEE Transactions on Control Systems Technology,vol.19,no.3,pp.590–600,2011.
[8]D.H.Owens,C.T.Freeman,and T.V.Dinh,“Norm-optimal iterative learning control with intermediate point weighting:theory,algorithms,and experimental evaluation,”IEEE Transactions on Control Systems Technology,vol.21,no.3,pp.999–1007,2013.
[9]T.D.Sona,H.-S.Ahn,and K.L.Moore,“Iterative learning control in optimal tracking problems with specified data points,”Automatica,vol.49,no.5,pp.1465–1472,2013.
[10]C.T.Freeman and Y.Tan,“Iterative learning control with mixed constraints for point-to-point tracking,”IEEE Transactions on Control Systems Technology,vol.21,no.3,pp.604–616,2013.
[11]C.T.Freeman,“Constrained point-to-point iterative learning control with experimental verification,”Control Engineering Practice,vol.20,no.5,pp.489–498,2012.
[12]P.Janssens,G.Pipeleers,M.Diehl,and J.Swevers,“Energy optimal time allocation of a series of point-to-point motions,”IEEE Transactions on Control Systems Technology,vol.22,no.6,pp.2432–2435,2014.
[13]Y.Chen,B.Chu,and C.T.Freeman,“Point-to-point iterative learning control with optimal tracking time allocation,”in 54th IEEE Conference on Decision and Control,Osaka,Japan,2015,pp.6089–6094.
[14]T.H.Cormen,C.E.Leiserson,R.L.Rivest,and C.Steinn,Introduction to Algorithms,3rd ed.Massachusetts Institute of Technology:The MIT Press,2009.
[15]N.Amann,“Optimal algorithms for iterative learning control,”Ph.D.dissertation,University of Exeter,UK,1996.
[2]M.Norrlof,“An adaptive iterative learning control algorithm with experiments on an industrial robot,”IEEE Transactions on Robotics and Automation,vol.19,no.2,pp.245–251,2002.
[3]X.Yu,Z.Xiong,D.Huang,and Y.Jiang,“Model-based iterative learning control for batch processes using generalized hinging hyperplanes,”Industrial&Engineering Chemistry Research,vol.52,no.4,pp.1627–1634,2013.
[4]J.H.Lee and K.S.Lee,“Iterative learning control applied to batch processes:An overview,”Control Engineering Practice,vol.15,pp.1306–1318,2007.
[5]C.T.Freeman,Control System Design for Electrical Stimulation in Upper Limb Rehabilitation.Springer International Publishing,2016.
[6]D.Bristow,M.Tharayil,and A.Alleyne,“A survey of iterative learning control,”Control Systems,IEEE,vol.26,no.3,pp.96–144,2006.
[7]C.T.Freeman,Z.Cai,E.Rogers,and P.L.Lewin,“Iterative learning control for multiple point-to-point tracking application,”IEEE Transactions on Control Systems Technology,vol.19,no.3,pp.590–600,2011.
[8]D.H.Owens,C.T.Freeman,and T.V.Dinh,“Norm-optimal iterative learning control with intermediate point weighting:theory,algorithms,and experimental evaluation,”IEEE Transactions on Control Systems Technology,vol.21,no.3,pp.999–1007,2013.
[9]T.D.Sona,H.-S.Ahn,and K.L.Moore,“Iterative learning control in optimal tracking problems with specified data points,”Automatica,vol.49,no.5,pp.1465–1472,2013.
[10]C.T.Freeman and Y.Tan,“Iterative learning control with mixed constraints for point-to-point tracking,”IEEE Transactions on Control Systems Technology,vol.21,no.3,pp.604–616,2013.
[11]C.T.Freeman,“Constrained point-to-point iterative learning control with experimental verification,”Control Engineering Practice,vol.20,no.5,pp.489–498,2012.
[12]P.Janssens,G.Pipeleers,M.Diehl,and J.Swevers,“Energy optimal time allocation of a series of point-to-point motions,”IEEE Transactions on Control Systems Technology,vol.22,no.6,pp.2432–2435,2014.
[13]Y.Chen,B.Chu,and C.T.Freeman,“Point-to-point iterative learning control with optimal tracking time allocation,”in 54th IEEE Conference on Decision and Control,Osaka,Japan,2015,pp.6089–6094.
[14]T.H.Cormen,C.E.Leiserson,R.L.Rivest,and C.Steinn,Introduction to Algorithms,3rd ed.Massachusetts Institute of Technology:The MIT Press,2009.
[15]N.Amann,“Optimal algorithms for iterative learning control,”Ph.D.dissertation,University of Exeter,UK,1996.