295 results about "Plant models" patented technology

A disk drive is disclosed comprising a voice coil motor (VCM) driven in a PWM mode using model reference current feedback. The PWM circuitry and VCM form a plant transfer function which varies with changes to the plant characteristics, such as the resistance of the voice coil fluctuating with temperature drift. A plant model having a model transfer function generates an estimated state of the VCM in response to a detected current flowing through the voice coil. A correction block, responsive to the detected current, adjusts PWM timing signals so that the plant transfer function substantially matches the model transfer function.

A mobile station and methods are disclosed for diagnosing and modeling site specific effluent treatment facility requirements to arrive at a treatment regimen and/or proposed commercial plant model idealized for the particular water/site requirements. The station includes a mobile platform having power intake, effluent intake and fluid outflow facilities and first and second suites of selectably actuatable effluent pre-treatment apparatus. An effluent polishing treatment array is housed at the station and includes at least one of nanofiltration, reverse osmosis and ion-exchange stages. A suite of selectively actuatable post-treatment apparatus is housed at the station. Controls are connected at the station for process control, monitoring and data accumulation. A plurality of improved water treatment technologies is also disclosed. The modeling methods include steps for analyzing raw effluent to be treated, providing a field of raw effluent condition entry values and a field of treated effluent condition goals entry values, and utilizing said fields to determine an initial treatment model including a selection of, and use parameters for, treatment technologies from the plurality of down-scaled treatment technologies at the facility, the model dynamically and continuously modifiable during treatment modeling.

A mobile station and methods are disclosed for diagnosing and modeling site specific effluent treatment facility requirements to arrive at a treatment regimen and/or proposed commercial plant model idealized for the particular water/site requirements. The station includes a mobile platform having power intake, effluent intake and fluid outflow facilities and first and second suites of selectably actuatable effluent pre-treatment apparatus. An effluent polishing treatment array is housed at the station and includes at least one of nanofiltration, reverse osmosis and ion-exchange stages. A suite of selectively actuatable post-treatment apparatus are housed at the station. Controls are connected at the station for process control, monitoring and data accumulation. A plurality of improved water treatment technologies are also disclosed.

An industrial system configuration platform facilitates automation of an industrial system. The industrial system configuration platform comprises a representation of the industrial system and a configuration component that automatically configures at least a portion of the industrial system based at least in part upon metadata that describes the representation. A physical device can be automatically configured based at least in part upon the metadata, and a database can be generated and structured based at least in part upon the metadata. The industrial system configuration platform further enables an industrial process to be implemented based at least in part upon the metadata.

A system that facilitates generation of a unique identifier comprises a random number generator. A unique identifier creator receives a number generated by the random number generator and object instance data associated with an object. The unique identifier creator utilizes the object instance data and the random number to generate a unique identifier for an object associated with the object instance data.

A Soft Computing (SC) optimizer for designing a Knowledge Base (KB) to be used in a control system for controlling a motorcycle is described. In one embodiment, a simulation model of the motorcycle and rider control is used. In one embodiment, the simulation model includes a feedforward rider model. The SC optimizer includes a fuzzy inference engine based on a Fuzzy Neural Network (FNN). The SC Optimizer provides Fuzzy Inference System (FIS) structure selection, FIS structure optimization method selection, and teaching signal selection and generation. The user selects a fuzzy model, including one or more of: the number of input and/or output variables; the type of fuzzy inference; and the preliminary type of membership functions. A Genetic Algorithm (GA) is used to optimize linguistic variable parameters and the input-output training patterns. A GA is also used to optimize the rule base, using the fuzzy model, optimal linguistic variable parameters, and a teaching signal. The GA produces a near-optimal FNN. The near-optimal FNN can be improved using classical derivative-based optimization procedures. The FIS structure found by the GA is optimized with a fitness function based on a response of the actual plant model of the controlled plant. The SC optimizer produces a robust KB that is typically smaller that the KB produced by prior art methods.

A control method for optimizing a turndown operation for a power plant having a plurality of generating units. The plurality of generating units each may include either an on-condition or an off-condition during a selected operating period. The method may include: defining competing operating modes, wherein the competing operating modes include different possible combinations regarding which of the plurality of generating units have the on-condition and which have the off-condition during the selected operating period; defining multiple cases for each of the competing operating modes, wherein the multiple cases include varying a value of an operating parameter; receiving performance objectives that include a cost function; receiving an ambient conditions forecast; for the multiple cases of the competing operating modes, simulating the turndown operation with a power plant model given the value of the operating parameter and the ambient conditions forecast; evaluating a simulation result pursuant to the cost function so to select therefrom a preferred case.

A six degree-of-freedom trajectory linearization controller (TLC) architecture (30) for a fixed-wing aircraft (46) is set forth. The TLC architecture (30) calculates nominal force and moment commands by dynamic inversion of the nonlinear equations of motion. A linear time-varying (LTV) tracking error regulator provides exponential stability of the tracking error dynamics and robustness to model uncertainty and error. The basic control loop includes a closed-loop, LTV stabilizing controller (12), a pseudo-inverse plant model (14), and a nonlinear plant model(16). Four of the basic control loops (34, 36, 40, 42) are nested to form the TLC architecture (30).

Systems and methods that facilitate messaging capabilities within a plant (e.g., a unified plant model—UPM) via employing a message engine that normalizes messaging of various messaging protocols and formats, wherein various systems of such plant can map to the message engine; and provide a consistent interface where events are sent/received consistently across such system. Such messaging engines can facilitate communication (e.g., via preferred channels) to other services/products, wherein the configuration and management of messaging is consistent across the system.

The invention provides a three-dimensional framework fast extraction method based on branch feathers, which comprises the following steps: firstly, automatically extracting root points and tip end points of a tree type voxel model; then, carrying out seed point distance conversion on the root points and the tip end points of the voxel model; automatically judging the branching feathers and optimizing cutting surfaces according to the growth strategy of regions from the root points or the tip end points; decomposing an object into meaningful components with reasonable delimitation between components; and finally, extracting voxel component frameworks and connecting the voxel component frameworks into a structural framework of the object. The framework fast extraction method based on branch feathers is fast and effectively, and the structural integral frameworks maintain topological structures of the original voxel model, and can not generate fracture and redundant complicated branches. The actual plant model construction is carried out on the basis of the framework, the actual scanning data can be processed, and the invention has the anti-noise capability and has high reconstruction accuracy. The test on a plurality of data sets proves that the invention is applicable to bodies with annular structures and can process surface voxel models and solid voxel models.

A system for handling a production disturbance/opportunity event includes a network having data processing units running a MES software for controlling/monitoring a production process operating production components. A production modeler defines a plant model of the production process, and a production scheduler generates an executable production schedule for the execution of operating procedures for the production components. A production executor executes the production process following the generated executable production schedule, and a production disturbance/opportunity event identifier detects a production disturbance event and identifies a production opportunity event which allows to maintain an efficiency of the production process at least as close as possible to an efficiency given by the executable production schedule as originally generated by the production scheduler. The production scheduler re-calculates an amended executable production schedule incorporating the identified production opportunity event, and the production executor executes the production process now following the re-calculated executable production schedule.

Systems and methods for leveraging a preliminary plant model to create a detailed physical plant model are presented. The system stores instances of component primitives, and can utilize stored geometries of the component primitives to identify a plurality of physical components to form a physical plant model. The physical plant model can realize at least a portion of the component runs based on equations and mapping definitions that establish relationships among the geometries of the equipment and piping. The components of the physical plant model can be mapped to catalog items based on the geometries of the components. After translation, a bill of materials listing the physical plant model components can be produced.

A control device of a compressor includes a valve control unit configured to control an anti-surge valve that returns fluid in a discharge side of the compressor to a suction side of the compressor in accordance with a control parameter, a simulation unit configured to simulate operational status of the compressor in a plant in accordance with a plant model and the control parameter of the plant to which the compressor is installed, and a control parameter adjusting unit configured to adjust the control parameter in accordance with a result of the simulation.

A controller design for switching between m linear multivariable controllers each of whom stabilizes a linear plant has been presented. A Youla-Kucera factorization was exploited in the interest of obtaining a closed-loop system that is exponentially stable for any switching signal σ(t) in the absence of plant model uncertainty. Robustness to practical model uncertainty was also considered and lower and upper bounds on the tolerable magnitude of unstructured additive plant uncertainty were presented. Numerical example demonstrated that the two controller degrees of freedom in the proposed controller design could be used to separately modify the closed-loop steady-state (with respect to σ(t)) performance and the switching transients.

The invention provides a wheat pollution-free high yield cultivation method and belongs to the technical field of agricultural production. The method includes reasonably selecting a production base with appropriate environmental conditions and ecological conditions, selecting and using fine breeds and carefully choosing seeds and seed coatings by methods of mechanical screening and the like, fertilizing soil fertility by using straw covering no-tillage soil fertilizing technology to improve soil, utilizing a planted model of double six-feet reserved rows to improve yield per unit area, selecting an appropriate seeding time, seeding rate and seeding method, scientifically fertilizing, utilizing a disease, insect pest and weed damage comprehensive control technology, harvesting wheat timely, and storing, transporting and processing harvested wheat. According to the method, the hygienic quality standard of the wheat can be effectively improved, rural incomes are increased, the market competitiveness is enhanced, and also the method has a fundamentally realistic significance for improving farmland ecological environment and quality safety of the pollution-free wheat production and guarantying agricultural sustainable development and customer fitness, and the method has good popularizing and applying values.

The invention provides a semantic segmentation and point cloud processing combined plant recognition and model construction method. The method comprises the following steps: 1, generating an orthoimage according to a landscape image obtained by oblique photography; 2, training a deep learning network, and performing semantic segmentation on the orthoimage by a neural network to identify a plant region; 3, generating a point cloud corresponding to the image, and realizing coordinate correspondence between point cloud data and the orthoimage through coordinate system conversion; 4, segmenting the point cloud data to obtain a plant area point cloud; 5, in combination with oblique photography images and point cloud data, plant species are further recognized through k-means point cloud clustering, target detection and other methods; 6, establishing a plant model library; 7, processing the point cloud of the plant area, determining parameters including plant types, positions, sizes and the like, and importing a plant model to replace the point cloud; and 8, converting the plant model into a required format. According to the invention, efficient and accurate recognition of plant species and construction of a three-dimensional plant scene with a sense of reality can be realized.

The invention discloses a plant three-dimensional reconstruction method and system based on depth map repair. The method comprises the following steps: obtaining a plurality of views; obtaining a depth map corresponding to each view, and recording the depth map as a first depth map; repairing a cavity area in the first depth map, and dynamically adjusting the size of a filtering window in a repairing algorithm by using super-pixel block label information; performing filtering processing on the repaired first depth map to obtain a second depth map; carrying out fusion processing on the second depth map to obtain a plant dense point cloud model; and extracting a plant three-dimensional surface from the dense point cloud model by using a surface reconstruction algorithm to complete the reconstruction of the plant three-dimensional model. The method is simple to operate and low in cost. The size of the filtering window is dynamically adjusted by using the boundary information of the super-pixel block, so that pixels which do not belong to the same depth area do not participate in filtering calculation, the occurrence of errors is reduced, plant dense point clouds are more dense, and afinally reconstructed plant model is more accurate and complete.

The invention discloses a wind power plant simulation testing platform and a testing method thereof. The platform comprises an upper computer, a wind power plant simulation machine and a wind power plant managing system prototype machine which are connected in a communication mode. The upper computer is used for setting and monitoring the whole testing process, the wind power plant simulation machine is used for simulating the operation state of a whole wind power plant, the wind power plant managing system prototype machine is used for fast achieving a true wind power plant managing system to be tested. The testing method comprises the steps of establishing a wind power plant model, configuring the wind power plant simulation machine and the wind power plant managing system prototype machine, setting a testing working condition and a model parameter, monitoring the testing process, processing the testing result and carrying out the analysis and evaluation. The wind power plant simulation testing platform and the testing method have the advantages that the research, development and test on software and hardware of the wind power plant managing system can be achieved in a laboratory, the development cycle of the system is shorted, the development cost of the system is reduced, the spot working conditions such as faults and the extreme working conditions can be reproduced, and the later upgrading and maintaining cost is reduced.

Nonlinear functions (table and map) of a temperature estimation model are corrected based on outputs from a temperature sensor. An electronic control system calculates, for a plant model constructed to calculate an estimated temperature value of the plant, an estimated temperature value using a correlation model between a first parameter regarding the plant and a second parameter regarding the plant model. This control system controls the temperature of the plant based on the calculated estimated temperature value of the plant. The control system also defines a plurality of functions (Wi) in a range of a plurality of the first parameters for the correlation model, calculates correction coefficients (Kli, Kci) that adjust the height of the plurality of functions based on the output of the temperature sensor and the calculated estimated temperature value of the plant, and corrects the correlation model by the plurality of functions (Wi) and correction coefficients (Kli, Kci).

In a temperature control system of a plant such as an engine exhaust system, there are provided a catalyst heat model calculating a temperature estimated value of the plant, a temperature sensor model inputting the calculated value to calculate an output estimated value of a temperature sensor, a temperature controller controlling the plant temperature based on the estimated value, and a model parameter corrector correcting the plant model parameter so as to minimize error between the temperature sensor output and the calculated output estimated value. With this, even in the case where the temperature sensor has a large response lag, the temperature estimated value can nevertheless be corrected with high accuracy, without, for example, causing severe overshooting.

The invention discloses a method for constructing a transparent mine and particularly relates to a method for constructing a three-dimensional transparent mine with highly integrated data of upper andlower topography, construction, equipment, stratum, mining environment, monitoring and the like of mine wells. The method includes constructing a full-automatic model building rule base, a topology association rule base, a dynamic matching method base and an equipment model base; constructing a basic database; constructing an initial irregular triangular network geological model and a three-dimensional roadway, equipment, mining environment, an earth surface plant model; drawing an envisaged section line; performing plane-profile corresponding analysis and dynamic adjustment; modifying the plane, so that the profile changes, and modifying the profile, so that the plane changes; performing partial updating and reconfiguring the irregular triangular network geological model. According to the method for constructing the three-dimensional transparent mine, the transparent mine comprising well up-and-down full environmental models such as the self-adaptive three-dimensional geological model and the equipment model can be formed, the design is reasonable, the constructed three-dimensional model can be dynamically partially updated, and the method has good promotion value.