Abstract: Systems, apparatuses, methods, and computer program products are disclosed for generating a single-index model (SIM) tree. An example method includes receiving a data set and a maximum tree depth. The example method further includes screening a set of variables from the data set to form split variables. The method may include, while maximum tree depth has not been reached, (i) generating a fast SIM estimation for nodes of a tree level, (ii) for each node, selecting a split point and split variable based on the fast SIM estimation, (iii) based on the selected split points and split variables, generating nodes for a next tree level, each including a subset of data, and (iv) repeating steps (i), (ii), and (iii). The method may include fitting a SIM for each leaf node at maximum tree depth based on a subset of the data set represented by the leaf node.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for generating a single-index model (SIM) tree. An example method includes receiving a data set and a maximum tree depth. The example method further includes screening a set of variables from the data set to form split variables. The method may include, while maximum tree depth has not been reached, (i) generating a fast SIM estimation for nodes of a tree level, (ii) for each node, selecting a split point and split variable based on the fast SIM estimation, (iii) based on the selected split points and split variables, generating nodes for a next tree level, each including a subset of data, and (iv) repeating steps (i), (ii), and (iii). The method may include fitting a SIM for each leaf node at maximum tree depth based on a subset of the data set represented by the leaf node.

Abstract: A method for constructing an active magnetic bearing controller based on a look-up table method includes: building finite element models of an active magnetic bearing to obtain two universal Kriging prediction models in X-axis and Y-axis directions about actual suspension forces being in association with actual displacement eccentricities and actual control currents in the X-axis and Y-axis directions of the active magnetic bearing based on a universal Kriging model; creating two model state tables in the X-axis and Y-axis directions about the actual suspension forces being in association with the actual displacement eccentricities and the actual control currents to construct two look-up table modules with the two built-in model state tables, respectively; and constructing an active magnetic bearing controller by using two fuzzy adaptive PID controllers, two amplifier modules in the X-axis and Y-axis directions, the two look-up table modules, and two measurement modules in the X-axis and Y-axis directions.

Abstract: A method for constructing an active magnetic bearing controller based on a look-up table method includes: building finite element models of an active magnetic bearing to obtain two universal Kriging prediction models in X-axis and Y-axis directions about actual suspension forces being in association with actual displacement eccentricities and actual control currents in the X-axis and Y-axis directions of the active magnetic bearing based on a universal Kriging model; creating two model state tables in the X-axis and Y-axis directions about the actual suspension forces being in association with the actual displacement eccentricities and the actual control currents to construct two look-up table modules with the two built-in model state tables, respectively; and constructing an active magnetic bearing controller by using two fuzzy adaptive PID controllers, two amplifier modules in the X-axis and Y-axis directions, the two look-up table modules, and two measurement modules in the X-axis and Y-axis directions.