01508nas a2200169   4500008004100000245007900041210006900120260000800189300001200197490000700209520094700216100001401163700001501177700002101192700001501213856011001228       2016                        eng d00aRecursive orthogonal least square based soft sensor for batch distillation0 aRecursive orthogonal least square based soft sensor for batch di  cSEP  a241-2630 v113 aA multiple-input and multiple-output (MIMO) model, namely Recursive Orthogonal Least Square (ROLS) based radial basis function (RBF) is developed to estimate product compositions in a batch distillation process from temperature measurements. The process data is generated by simulating the differential equations of the batch distillation process, changing the initial feed composition and boiluprate from batch to batch. Moreover, the reflux ratio is also randomly varied within each batch to represent the exact dynamics of the batch distillation. Temperature and distillate composition is correlated by the RBF trained by ROLS algorithm. A Single RBF network estimate the quality of products in real-time. The results show that ROLS based estimator give correct composition estimations for a batch distillation process. The robustness of the ROLS algorithm and low computational requirement makes the estimator attractive for on-line use. 1 aMehta, S.1 aRamani, H.1 aYelgatte, N., N.1 aRahman, I.  uhttps://library.ncl.res.in/content/recursive-orthogonal-least-square-based-soft-sensor-batch-distillation01333nas a2200133   4500008004100000245009000041210006900131260000800200520082600208100001501034700001501049700001501064856012001079       2018                        eng d00aRecursive orthogonal least squares based adaptive control of a polymerisation reactor0 aRecursive orthogonal least squares based adaptive control of a p  cNOV3 aA Nonlinear Internal Model Control (NIMC) scheme, based on a recursively updated Radial Basis Function Network (RBFN), is applied to control the nonlinear Polymerisation process. Recursive Orthogonal Least Squares (ROLS) algorithm recursively updates the weighting matrix of RBFN in real time, such that modelling errors are minimised. In addition to the ROLS based adaptive IMC, a non-adaptive IMC, based on the fixed Orthogonal Least Squares (OLS) algorithm and a normal PID controller are also applied to control the polymerisation process. The simulated results show the effectiveness of the ROLS based controller in terms of response time to step changes and disturbance rejection capabilities over the classical PID controller and the fixed OLS based IMC. Also, the proposed algorithm fits well in the IMC framework1 aTiwari, S.1 aSawant, P.1 aRahman, I.  uhttps://library.ncl.res.in/content/recursive-orthogonal-least-squares-based-adaptive-control-polymerisation-reactor