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Abstract: Based on robust feedback incorporated with iterative learning control scheme, this paper proposes a 2D controller design for a kind of batch process with uncertainties and interval time-varying delay. The batch process is first transformed into a two-dimensional Fornasini—Marchsini (2D-FM) model with a delay varying in a range. Then the design of 2D controller scheme is cast as a robust H ∞ control problem for uncertain 2D systems. Based on the 2D control system theory, a design framework of 2D controller is formulated, which consists of two control actions: a robust feedback control for ensuring the performances over time and a P-type iterative learning control (P-type ILC) for improving the tracking performance from cycle to cycle. The proposed control law can guarantee closed-loop convergence along both the time and the cycle directions to satisfy H ∞ performance. Conditions for the existence of the proposed 2D control design scheme are given in terms of linear matrix inequalities. The minimum H ∞ norm bound is obtained by solving linear objective optimization problems. The generality of the proposed design method is shown by the results converted to constant delay case. Application to injection velocity control demonstrates the effectiveness and advantages of the proposed approach. [Copyright &y& Elsevier]

Highlights: [•] We model a batch process as 2 time dimensional state-space model with varying delays. [•] We proposes a design for the integrated output feedback and iterative learning control (ILC) of batch processes. [•] A sufficient criterion for delay-dependent H ∞ noise attenuation is derived. [•] Application to injection velocity control demonstrates the effectiveness and feasibility of the proposed design method. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of delay-range-dependentiterativelearning reliable guaranteed cost control of a class of batch processeswith uncertainties, state delay and actuator failures, where the maincontribution is in the relevant concept of H∞iterative learning fault-tolerant guaranteed costcontrol based on an equivalent two-dimensional system descriptionof these processes. The H∞iterativelearning reliable guaranteed cost controller (ILRGCC) is formulatedto include a robust extended feedback control for ensuring the performancesover time and an iterative learning control (ILC) for improving thetracking performance from cycle to cycle, such that it can not onlyguarantee the closed-loop convergence along both the time and thecycle directions but also satisfy both the H∞performance index and a cost function preserving upperbounds for all admissible uncertainties and any actuator failures.To achieve the least guaranteed cost for the closed-loop system, aconvex optimization problem with linear matrix inequality (LMI) constraintsis formulated for the design of the optimal guaranteed cost controllersuch that the delay-range-dependent existing condition of the proposedILRGCC design can also be given by LMIs, where the lower and upperdelay bounds only change along time tdirection.An illustrative example of applications to the nozzle packing pressurecontrol in injection molding has been developed to demonstrate theeffectiveness and merits of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: Based on a two-dimensional (2D) Fornasini–Marchsini system description of a batch process in industry, a robust state feedback integrated with an iterative learning reliable control (FILRC) scheme is proposed. The scheme is intended for batch processes with uncertain perturbations and state delay subject to actuator failures, which is dependent on the upper and lower delay bounds of the interval time-varying delay. The relevant concepts of fault-tolerance are introduced. The proposed control law can guarantee closed-loop convergence along both time and cycle directions to satisfy H ∞ performance even with unknown disturbances and actuator failures. By introducing a new 2D Lyapunov–Krasovskii functional candidate and adding a differential inequality without introducing redundant free-weighting matrices to the difference Lyapunov functional for 2D systems possessing two directions, conditions for the existence of the proposed FILRC scheme are established in terms of linear matrix inequalities (LMIs). By solving these LMIs, the FILRC law is explicitly formulated together with an adjustable robust H ∞ performance level. Applications to injection velocity control show that the proposed FILRC achieves the design objectives well. [Copyright &y& Elsevier]

Abstract: A batch process can be treated as a 2-dimentional (2D) system with a time dimension within each batch and a batch dimension from batch to batch. This paper integrates the learning ability of iterative learning control (ILC) into the prediction model of model predictive control (MPC). Based on this integrated model, a 2D dynamic matrix control (2D-DMC) algorithm with a feedback control and an optimal feed-forward control is proposed. The sufficient conditions for exponentially asymptotic and monotonic convergence of the proposed 2D-DMC are established with proof under certain assumptions, in the presence of not only the completely repeatable uncertainties but also the non-repeatable interval uncertainties. The effectiveness of the proposed control scheme is tested through simulation and experimental implementation in the context of injection molding, a typical batch process. The results show that the batch process control performance is significantly improved. [Copyright &y& Elsevier]

Abstract: A robust feedback integrated with iterative learning control (FILC) scheme for batch processes with uncertain perturbations and interval time-varying delay is developed. The batch process is modeled as a two-dimensional (2D) Rosser system with a delay varying in a range. The design of FILC scheme is transformed into a robust control problem of uncertain 2D system. New delay-range-dependent stability criteria and stabilization conditions are derived in terms of linear matrix inequalities (LMIs), which depend on not only the difference between the upper and lower delay bounds but also the upper delay bound of the interval time-varying delay. Parameterized characterizations for stabilizing the controller are given in terms of the feasibility solutions to the LMIs. Applications to injection velocity control show that the proposed FILC achieve the design objectives well. [Copyright &y& Elsevier]

Abstract: In the present work, statistical analysis and online monitoring is presented for handling uneven-length multiphase batch processes. Firstly, the irregular batches are classified into different uneven-length groups according to the changes of underlying characteristics. Then multi-source measurement data can be dealt with, each corresponding to one operation mode. The basic principle is that over different uneven-length groups, despite the uneven-length operation patterns, there are both similarity and dissimilarity to a certain extent among their underlying correlations. By an adequate decomposition, two different subspaces are separated, modeling the group-common and specific information respectively. Their corresponding confidence regions are constructed by searching similar patterns respectively. Accordingly, the online monitoring system is set up, which can track different types of variations closely. This analysis adds a detailed insight into the inherent nature of uneven-length multiphase batch processes. Its feasibility and performance are illustrated by a typical practical case with uneven cycles. [Copyright &y& Elsevier]

As a major polymer processing technique, polymer extrusionis acontinuous process, during which material properties, machine variables,and process variables interact with each other to determine the finalproduct quality. Precise control of key process variables such asbarrel temperatures and melt pressure are crucial to ensure a goodproduct quality in the extrusion process. In this paper, the overallextruder control system is constructed by two independent controlloops, a single-input–single-output (SISO) control of the meltpressure at die output, and a multiinput–multioutput (MIMO)control of the barrel temperatures. The dynamic behaviors of meltpressure and barrel temperatures were analyzed first. The characteristicsof the melt pressure dynamics were as follows: nonlinear and time-varyingwhile the extruder barrel temperatures were nonlinear, slow response,and different zones were highly coupled. Advanced control algorithmswere adopted to control these key variables. Experimental resultsdemonstrate the fast response, near-zero overshoot, and precise trackingperformance of the proposed control strategies. The robustness ofthe entire control system was verified through different operatingconditions including materials and set points. Ultimately the performanceof the entire control system was verified by product quality. Theproduct quality improved significantly with the proposed controller. [ABSTRACT FROM AUTHOR]