105results about How to "Strongly nonlinear" patented technology

The invention relates to a global optimization method of an ultra-low emission multi-pollutant cooperative removal system, which obtains an accurate description of a multi-pollutant generation, migration, conversion and removal process in a multi-device through an accurate modeling of a multi-device multi-pollutant cooperative removal process in an ultra-low emission system. The multi-pollutant emission reduction cost under different load, coal quality, pollutant concentration and operation parameters is evaluated accurately by the global operation cost evaluation method in ultra-low emissionsystem. Minute-level planning and optimization of emission reduction of global pollution reduction devices under different emission targets are realized by global operation optimization method of multi-pollutant multi-objective and multi-operating conditions. Reliable emission reduction and side-by-side control of pollutants are ensured through advanced control methods with low emission and multi-pollutant emission meeting the standards reliably. The invention innovates the modeling, optimization and control method of the ultra-low emission system from the aspects of model, architecture and algorithm, improves the controllability and adjustability of the system, and guides the efficient, reliable and economic operation of the ultra-low emission system.

The invention discloses a failure diagnosis and health evaluation method based on wavelet power, manifold dimension reduction and dynamic time warping, and aims to improve the feature separability of bearing failure, impeller failure and the mixed failures of a centrifugal pump and realize diagnosis and health evaluation of various states. The method comprises the following steps: firstly, decomposing collected vibration signals of the centrifugal pump into 8 wavelet components by applying wavelet packet conversion; extracting wavelet energy of each component to be taken as a failure feature to obtain an eight-dimensional failure feature vector; then conducting dimension reduction on the eight-dimensional feature by applying a manifold learning method to obtain a three-dimensional feature vector with better separability, simplicity and stability; finally, based on the feature vector, measuring the distance of test data and training data by applying a dynamic time normalization method so as to determine the current failure state and realize failure diagnosis of a bearing. The distance value can also reflect the health degree of the current state, can realize evaluation of the health state of the centrifugal pump, and has the excellent practical engineering application value.

The invention discloses a water supply prediction method and system. The method includes: analyzing historical data and establishing a water supply prediction model to obtain the functional relationship between the input layer parameters and the water supply volume output by the output layer; according to the established water supply prediction model and the required Real-time water supply forecasting on the forecast date; the process of analyzing historical data and establishing a water supply forecasting model includes but is not limited to the process of preprocessing the input historical data by using the moving average method, and using the neural network algorithm to determine the network topology of the water supply forecasting model. The water supply forecasting model process is determined according to the preprocessed historical data and the corresponding network topology. The present invention comprehensively adopts the moving average method and the neural network algorithm to predict the water supply volume, has low calculation complexity, has obvious periodicity and strong nonlinearity, has good real-time performance, and can accurately describe the influence of various factors on the water supply volume. The method can accelerate the convergence speed of the neural network model, and can be widely used in the field of water supply analysis.

The invention discloses a four-rotor aircraft attitude control method and controller. For the disadvantage that a four-rotor aircraft system is difficult to establish a precise physical model, the nonlinear dynamic characteristic of the system is described by establishing a RBF-ARX model, which is locally linear and globally nonlinear, by adopting a system identification method; for the characteristic of the model and to satisfy quick response characteristic and relatively high control performance requirements of the system, the model is converted into a non-minimum state space model having anintegration link at first; then, a prediction controller is designed; furthermore, input is parameterized by using a laguerre function; therefore, predictive control of the online optimization variable of the system is reduced; furthermore, a given reference signal can be precisely tracked; and, for the numerical stability problem due to increasing of a prediction time domain, an exponential decay weight is introduced into a target function, so that a closed-loop system has the specified stability. The scheme has the characteristics of being short in online optimization time and steady in numerical value in a relatively large prediction time domain condition, and has relatively high practical value and application prospect.

The present invention is a novel, high resolution, color, three-dimensional (3-D) volumetric display system for dynamic images—the video cube. The video cube consists of an air-tight glass cube filled with a gas mixture and multiple planes of thin wires arranged in alternating orthogonal layers. These wires may be set at voltage potentials capable of producing a glow discharge at the intersection of pairs of wires. Using a computer capable of storing dynamic image data and electronic controllers capable of energizing pairs of wires appropriately at the proper time 3-D dynamic images may be formed from multiple glows between excited wire pairs. The video cube may be used to display complex real-time information from computers and other digital processors with high accuracy for unlimited number of simultaneous unaided observers.

The invention discloses a mesoscale vortex trajectory prediction method. The method comprises the steps of downloading and reading satellite height measurement data, extracting mesoscale vortex characteristic parameters and position information, tracking mesoscale vortexes, establishing a mesoscale vortex trajectory prediction model based on a BP neural network, determining input and output data,training the BP neural network, and inputting the initial positions of the mesoscale vortexes into the trained prediction model for prediction. According to the invention, the BP neural network is used as a prediction model, and the tracked mesoscale vortex position information and the initial ground rotation flow velocity anomaly are used as model inputs, so that the short-term prediction of themesoscale vortex trajectory can be realized. Meanwhile, in the mesoscale vortex tracking process, the minimum distance method and the similarity method are combined, limitation on the mesoscale vortexamplitude is added, the error tracking rate is reduced, the tracking accuracy is guaranteed, and therefore the model prediction precision is improved.

A controller having an auto-tuning function has a manipulated value determination unit that selectively determines a first manipulated value for causing a first change in a controlled value of a controlled object or a second manipulated value for causing a second change opposite to the first change in the controlled value, in accordance with a preset parameter, so that a process value obtained from the controlled object follows a target value, and a tuning unit that alternately outputs the first manipulated value and the second manipulated value in accordance with the process value, and that determines the parameter from a response characteristic obtained through the alternate output. The tuning unit successively changes a magnitude of the first manipulated value each time output is switched during the alternate output of the first manipulated value and the second manipulated value.