Abstract: The invention relates to a method for transferring a pourable medium (10) from a first vessel (12) into a second vessel (14), by means of a robot arm (16), wherein a movement 118) of the robot arm (16) can be controlled by at least one movement parameter (BP), including, inter alia, the following method steps: d) determining the mass of the medium (10) transferred into the second vessel (14) as an actual filling mass (IFM), and also the variation over time of the actual filling mass (IFM) of the medium (30; as an actual mass flow (IMS), by means of a balance 124), c) calculating a correcting mass flow (StMS) as a correcting variable (26) of a first control circuit (28) while taking into account the actual filling mass (FM) and the intended filling mass (SFM), f) using the correcting variable (26) of die first control circuit (28) as a reference variable (30) of a second control circuit (32) for the purpose that the calculated correcting mass flow (StMS) is used as the intended mass flow (SMS), g) calculating

Abstract: System and method for training a support vector machine (SVM) with process constraints. A model (primal or dual formulation) implemented with an SVM and representing a plant or process with one or more known attributes is provided. One or more process constraints that correspond to the one or more known attributes are specified, and the model trained subject to the one or more process constraints. The model includes one or more inputs and one or more outputs, as well as one or more gains, each a respective partial derivative of an output with respect to a respective input. The process constraints may include any of: one or more gain constraints, each corresponding to a respective gain; one or more Nth order gain constraints; one or more input constraints; and/or one or more output constraints. The trained model may then be used to control or manage the plant or process.

Abstract: System and method for training a support vector machine (SVM) with process constraints. A model (primal or dual formulation) implemented with an SVM and representing a plant or process with one or more known attributes is provided. One or more process constraints that correspond to the one or more known attributes are specified, and the model trained subject to the one or more process constraints. The model includes one or more inputs and one or more outputs, as well as one or more gains, each a respective partial derivative of an output with respect to a respective input. The process constraints may include any of: one or more gain constraints, each corresponding to a respective gain; one or more Nth order gain constraints; one or more input constraints; and/or one or more output constraints. The trained model may then be used to control or manage the plant or process.

Abstract: System and method for optimizing polymer production scheduling. The system includes an input, operable to receive optimization input information, a model of a polymer production system including one or more transition models representing transition behavior of the polymer production system, an optimizer, operable to execute the model using the received optimization input information to generate an optimized polymer production schedule, e.g., by solving an objective function subject to constraints, e.g., to minimize/maximize costs/profits and/or to minimize order times, and an output, operable to output the generated optimized polymer production schedule, wherein the optimized polymer production schedule is usable to manage polymer production with a polymer production system.