[ { "id": "authors:8qa3g-ndw41", "collection": "authors", "collection_id": "8qa3g-ndw41", "cite_using_url": "https://resolver.caltech.edu/CaltechCDSTR:1993.012", "type": "monograph", "title": "Robust Control Structure Selection", "author": [ { "family_name": "Lee", "given_name": "Jay H.", "clpid": "Lee-J-H" }, { "family_name": "Braatz", "given_name": "Richard D.", "clpid": "Braatz-R-D" }, { "family_name": "Morari", "given_name": "Manfred", "clpid": "Morari-M" }, { "family_name": "Packard", "given_name": "Andrew", "clpid": "Packard-A" } ], "abstract": "Screening tools for control structure selection in the presence of model/plant mismatch are developed in the context of the Structured Singular Value (\u03bc) theory. The developed screening tools are designed to aid engineers in the elimination of undesirable control structure candidates for which a robustly performing controller does not exist. Through application on a multicomponent distillation column, it is demonstrated that the developed screening tools can be effective in choosing an appropriate control structure while previously existing methods such as the Condition Number Criterion can lead to erroneous results.", "publisher": "California Institute of Technology", "publication_date": "1993-06-21" }, { "id": "authors:2zdma-ddb77", "collection": "authors", "collection_id": "2zdma-ddb77", "cite_using_url": "https://resolver.caltech.edu/CaltechCDSTR:1993.009", "type": "monograph", "title": "Stability and Performance Analysis of Systems Under Constraints", "author": [ { "family_name": "Braatz", "given_name": "Richard D.", "clpid": "Braatz-R-D" }, { "family_name": "Morari", "given_name": "Manfred", "clpid": "Morari-M" } ], "abstract": "All real world control systems must deal with actuator and state constraints. Standard conic sector bounded nonlinearity stability theory provides methods for analyzing the stability and performance of systems under constraints, but it is well-known that these conditions can be very conservative. A method is developed to reduce conservatism in the analysis of constraints by representing them as nonlinear real parametric uncertainty.", "publisher": "California Institute of Technology", "publication_date": "1993-06-17" }, { "id": "authors:mexyy-rcd09", "collection": "authors", "collection_id": "mexyy-rcd09", "cite_using_url": "https://resolver.caltech.edu/CaltechCDSTR:1993.010", "type": "monograph", "title": "Robust Loopshaping for Process Control", "author": [ { "family_name": "Braatz", "given_name": "Richard Dean", "clpid": "Braatz-R-D" } ], "abstract": "Strong trends in chemical engineering and plant operation have made the control of processes increasingly difficult and have driven the process industry's demand for improved control techniques. Improved control leads to savings in resources, smaller downtimes, improved safety, and reduced pollution. Though the need for improved process control is clear, advanced control methodologies have had only limited acceptance and application in industrial practice. The reason for this gap between control theory and practice is that existing control methodologies do not adequately address all of the following control system requirements and problems associated with control design: \n\n* The controller must be insensitive to plant/model mismatch, and perform well under unmeasured or poorly modeled disturbances. \n\n* The controlled system must perform well under state or actuator constraints. \n\n* The controlled system must be safe, reliable, and easy to maintain. \n\n* Controllers are commonly required to be decentralized. \n\n* Actuators and sensors must be selected before the controller can be designed. \n\n* Inputs and outputs must be paired before the design of a decentralized controller. \n\nA framework is presented to address these control requirements/problems in a general, unified manner. The approach will be demonstrated on adhesive coating processes and distillation columns.", "publisher": "California Institute of Technology", "publication_date": "1993-06-17" }, { "id": "authors:yy8es-83493", "collection": "authors", "collection_id": "yy8es-83493", "cite_using_url": "https://resolver.caltech.edu/CaltechCDSTR:1993.005", "type": "monograph", "title": "Computational Complexity of \u03bc Calculation", "author": [ { "family_name": "Braatz", "given_name": "Richard D.", "clpid": "Braatz-R-D" }, { "family_name": "Young", "given_name": "Peter M.", "clpid": "Young-P-M" }, { "family_name": "Doyle", "given_name": "John C.", "orcid": "0000-0002-1828-2486", "clpid": "Doyle-J-C" }, { "family_name": "Morari", "given_name": "Manfred", "clpid": "Morari-M" } ], "abstract": "The structured singular value \u03bc measures the robustness of uncertain systems. Numerous researchers over the last decade have worked on developing efficient methods for computing \u03bc. This paper considers the complexity of calculating \u03bc with general mixed real/complex uncertainty in the framework of combinatorial complexity theory. In particular, it is proved that the \u03bc recognition problem with either pure real or mixed real/complex uncertainty is NP-hard. This strongly suggests that it is futile to pursue exact methods for calculating \u03bc of general systems with pure real or mixed uncertainty for other than small problems.", "publisher": "California Institute of Technology", "publication_date": "1993-02-16" }, { "id": "authors:94qmz-vz212", "collection": "authors", "collection_id": "94qmz-vz212", "cite_using_url": "https://resolver.caltech.edu/CaltechCDSTR:1992.004", "type": "monograph", "title": "Avery Final Report: Identification and Cross-Directional Control of Coating Processes", "author": [ { "family_name": "Braatz", "given_name": "Richard D.", "clpid": "Braatz-R-D" }, { "family_name": "Tyler", "given_name": "Matthew L.", "clpid": "Tyler-M-L" }, { "family_name": "Morari", "given_name": "Manfred", "clpid": "Morari-M" } ], "abstract": "Coating refers to the covering of a solid with a uniform layer of liquid. Of special industrial interest is the cross-directional control of coating processes, where the cross-direction refers to the direction perpendicular to the substrate movement. The objective of the controller is to maintain a uniform coating under unmeasured process disturbances. \n\nAssumptions that are relevant to coating processes found in industry are used to develop a model for control design. We show how to identify the model from input-output data. This model is used to derive a model predictive controller to maintain flat profiles of coating across the substrate by varying the liquid flows along the cross direction. \n\nThe model predictive controller computes the control action which minimizes the predicted deviation in cross-directional uniformity. The predictor combines the estimate obtained from the model with the measurement of the cross-directional uniformity to obtain a prediction for the next time step. A filter is used to obtain robustness to model error and insensitivity to measurement noise. The tuning of the noise filter and different methods for handling actuator constraints are studied in detail. The three different constraint-handling methods studied are: the weighting of actuator movements in the objective function, explicitly adding constraints to the control algorithm, i.e. constrained model predictive control, and scaling infeasible control actions calculated from an unconstrained control law to be feasible. \n\nActuator constraints, measurement noise, model uncertainty, and the plant condition number are investigated to determine which of these limit the achievable closed loop performance. From knowledge of how these limitations affect the performance we find how the plant could be modified to improve the process uniformity. Also, because identification of model parameters is time-consuming and costly, we study how accurate the identification must be to achieve a given level of performance. \n\nThe theory developed throughout the paper is rigorously verified though simulations and experiments on a pilot plant. The effect of interactions on the closed loop performance is shown to be negligible for this pilot plant. The measurement noise and the actuator constraints are shown to have the largest effect on closed loop performance.", "publisher": "California Institute of Technology", "publication_date": "1992" } ]