50results about How to "Suppress uncertainty" patented technology

The invention relates to a self-adaptive index time varying slip form posture control method of a reentry flight vehicle, belonging to the technical field of flight vehicles. The method comprises the steps of firstly establishing a posture motion equation in a mode that a powerless reentry flight vehicle model is used as an object; secondly modifying the equation into the mode of an MIMO (Multiple Input Multiple Output) affine non-linear system, further applying a feedback linearization principle to carry out linearization processing so as to obtain a three-channel linearization model of pitching, rolling and yawing; aiming at the obtained linearization system, designing a modified self-adaptive index time varying slip form controller; and subsequently obtaining a control moment instruction for the posture control of the reentry flight vehicle, and inputting the control moment instruction into the reentry flight vehicle so as to control the posture. By combining the index time varying slip form control with a self-adaptive method, the problem of excessive adaptation of switch gain in the self-adaptive slip form control is solved to a certain extent, the uncertainty of system parameters and the influence of external disturbance can be suppressed effectively, and the precise posture control is realized.

The invention relates to an optical integral sliding-mode attitude control method of a reentry vehicle and a controller, and belongs to the technical field of vehicle control. The optical-integral sliding-mode attitude control method comprises the following steps of: firstly designing an SDRE (State-dependent Riccati Equation) nominal attitude control law according to a nominal model of the vehicle, and enabling the performance of a nominal system to meet the proposed optimal indexes; then considering the uncertainty of the system, designing an integral sliding-mode control law on the basis of the SDRE nominal attitude control law, enabling the system to have robustness while meeting the performance index requirement; and in order to weaken the buffeting, introducing a design idea of a second-order sliding mode and enabling the output of the controller to be smoother. The attitude controller designed by the invention not only can guarantee the expected indexes, but also has better robustness.

The method of the present invention comprises acquiring input data of both aircraft performance characteristics and atmospheric data, and defining trajectory parameters to which the aircraft trajectory must be subjected, the method further comprising defining aircraft trajectory parameters; acquiring a plurality of atmospheric forecast ensembles; calculating a predicted trajectory from each atmospheric forecast of an atmospheric forecast ensemble, said predicted trajectory having associated information regarding a certain figure of merit of the aircraft trajectory, wherein an ensemble of predicted trajectories is obtained from each atmospheric forecast ensemble, each predicted trajectory of the ensemble of predicted trajectories having an associated probability derived from the probability of each atmospheric forecast within an atmospheric forecast ensemble; the system of the present disclosure comprising all the necessary equipment to carry out the method of the present disclosure.

The invention discloses a trajectory tracking method for an under-actuated unpiloted ship controlled based on a limited backstepping method, and the method comprises the steps: (1), model building: building a three-freedom-degree kinetic and dynamic model of the under-actuated water surface unpiloted ship in an inertial coordinate system; (2), distance control design: giving an expected trajectory, calculating a position virtual control law through a position error, further deducing the actual input control law with the output constraint for controlling the longitudinal speed through the virtual control law, and carrying out the estimation and compensation of the external interference through a neural network, so as to reduce the distance difference between the unpiloted ship and a reference trajectory; (3), angle control design: calculating an angle error, calculating an angle virtual control law, further deducing the actual input control law with the output constraint for controllingyawing angular speed through the virtual control law, and carrying out the estimation and compensation of the external interference through the neural network, so as to reduce the angle difference between the unpiloted ship and the reference trajectory.

The invention discloses a multi-energy system collaborative scheduling method and device based on electric car access, and relates to the field of smart power grids. The method includes the steps of dividing electric car clusters according to statistical data of the time of the electric car accessing to a power grid and the time leaving the power grid, obtaining a current scheduling model of electric car clustering according to probability density and charging demand information of each electric car cluster accessing to and leaving the power grid in a corresponding period to build a multi-energy system cooperative scheduling model, using a multi-group balanced collaborative search algorithm to obtain energy supply cost and an optimal charge and discharge strategy with the lowest pollutantemission, and charging and discharging each electric car cluster. The method and device can reduce the energy supply cost, reduce the pollutants, improve the operation status of the multi-energy system, and prevent unnecessary faults from occurring; meanwhile, in a process of optimizing a charging and discharging mode, energy storage scheduling in the smart power grid is also optimized to suppressthe uncertainty of the smart power grid and reduce the construction cost of the smart power grid.

The invention relates to a batch automated testing method for a navigation terminal receiver. The batch automated testing method mainly aims at batch navigation receiver testing tasks and quick batch test for batch production of the navigation terminal receiver. Without involvement of an operator or many operators, the batch automated testing method has the advantages of high accuracy, consistency, efficiency and low cost and the like and is mainly applied to analog simulation generation technique of satellite navigation signals, bussing technique, assembly line based testing technique, sampling technique and database storage technique and automatic generation technique of test result report forms.

The invention relates to an energy-storage scheduling method and device for an intelligent power grid, and the method comprises the steps: obtaining a power generator uncertainty model, a load uncertainty model and an electric car charging uncertainty model in the intelligent power grid, wherein the intelligent power grid comprises a wind power generator, an energy storage apparatus, and an electric car charging station; carrying out the stochastic load flow calculation of the intelligent power grid through employing a two-point estimation method based on a fourth-order Gram-Charlier series expansion equation, carrying out the random sampling of a stochastic load flow calculation result, and obtaining an expected load flow distribution; determining a constraint condition according to the expected load flow distribution, solving a pre-built target function through employing a particle swarm optimization algorithm based on a segmented inertia decreasing weight, and obtaining an optimal energy storage scheme meeting the constraint condition; and carrying out the scheduling of the energy storage device according to the optimal energy storage scheme. The method can effectively inhibit the uncertainty of the intelligent power grid, and enables the intelligent power grid to operate safely and stably.

The invention provides an unmanned aerial vehicle robust attitude control method and device, and an electronic device and relates to the automation control technology field. The method comprises the following steps of acquiring the current state data and the current desired attitude angle of an unmanned aerial vehicle; determining the attitude control input of the unmanned aerial vehicle based oncurrent state data, the current desired attitude angle, and a pre-designed robust attitude controller, wherein the robust attitude controller includes a feedforward controller and an H2 controller designed based on the attitude error model of quaternion representation, and a robust compensator; and according to the attitude control input, controlling the flight attitude of the unmanned aerial vehicle. The feedforward controller and the H2 controller designed based on the attitude error model of quaternion representation can complete flight mode conversion under the condition that coordinate systems are not switched; and the robust compensator can simultaneously restrain the influenced of parameter uncertainty, nonlinearity, coupling dynamics and external disturbances in a whole frequency range, and the tracking performance and the robustness of the unmanned aerial vehicle are improved.

The invention provides a TS-RBF fuzzy neural network robust fusion algorithm applied to infrared flame recognition, belonging to the field of infrared flame recognition technology. The concrete process is as follows: collecting the time-domain signal data of different flames and interference sources, and preprocessing them to obtain the frequency-domain signal data; extracting the characteristic information from the waveform data in time domain and frequency domain, obtaining the characteristic vector of the sample, and composing the sample set; dividing the sample set is divided into a training set, a verification set and a test set; building a TS-RBF fuzzy neural network; setting the initial parameters of fuzzy neural network and using the training set to train the fuzzy neural network;carrying out verification and model selection of the trained fuzzy neural network with the verification set; inputting the test set into the trained fuzzy neural network, wherein the result is used asthe final evaluation of the model. The method can effectively resist data loss, data distortion and signal saturation of non-flame detection channel sampling data.

The invention discloses a mechanical arm posture robustness control method based on an interference estimator. The mechanical arm robustness control method comprises steps of establishing a mechanical arm dynamic model and performing feedback linearity on the mechanic arm dynamic model to simplify the dynamic model into a disturbed double integration model, setting a double-component posture robustness controller in order to realize mechanical arm posture robustness tracking control, and converting a compensated control signal to a voltage signal to input into an actuator so as to complete posture robustness control of the mechanical arm under a disturbed condition. The double-component posture controller comprises two parts. One part is used for configuring an input of a nominal system in order to guarantee that a closed loop system can track reference signals and the other part is used for configuring an interference estimator for performing real-time estimation on model uncertainty and external disturbance and then performing compensation on a control signal. The mechanical arm robustness control method based on the interference estimator can effectively remove or inhibit uncertainty or an interference signal in a kinematic model in order to realize high accuracy tracking on a mechanical arm posture expectation reference signal, and is strong in interference resistance, clear in controlling parameters, less in calculation and strong in implementation.

The invention belongs to the technical field of micro-positioning platforms. The invention discloses a micro-positioning platform based on piezoelectric ceramic driving and a modeling and control method thereof. The micro-positioning platform comprises a hardware part and a software part, the software part comprises Simulink software loaded in an industrial personal computer, and communication connection between the industrial personal computer and a data collection card is realized based on the software part to form closed-loop deviation control; the modeling method adopts a Hammerstein modelas a modeling basis, and comprises a static nonlinear part and a linear dynamic part: constructing a static nonlinear function based on a Boc-Wen model, and identifying unknown parameters of the model by adopting a particle swarm algorithm; a linear dynamic model is constructed, the model is equivalent to a linear second-order time-invariant system, and a Matlab recognition toolbox is adopted inthe model to obtain parameters; according to the control method, a composite control mode of feedforward control and feedback control is adopted; in conclusion, the high-precision positioning device has a high-precision positioning effect.

The invention discloses a self-organizing TS-type fuzzy network modeling method applied to infrared flame recognition, comprising the following steps: (1) collecting time-domain signal data of different flames and interference sources, and preprocessing the time-domain signal data to obtain frequency-domain signal data; (2) extracting the characteristic information from the time-domain and frequency-domain signal data of the waveform, obtaining the characteristic vector of the flame, and composing a sample set; (3) dividing the sample set into training set, verification set and test set; (4) building TS-RBF fuzzy neural network; (5) setting TS-RBF fuzzy neural network parameters initial value, using the training set of samples to TS-RBF fuzzy neural network training, structure, parameter learning; (6) using verification sets to test the training TS- Verification and Model Selection of RBF Fuzzy Neural Network; (7) inputting the test set into the trained TS-RBF fuzzy neural network, theresults as the final evaluation of the model.

The invention discloses a temperature control method for a continuous casting billet induction heating process, based on iterative learning control. The method comprises the steps that historical process data is preprocessed, and an input and output trajectory of the latest operation process is taken as a reference trajectory; a historical data trajectory subtracts the reference trajectory, a large amount of nonlinearity is removed, and a perturbation model variable is obtained; a revised dataset is processed through the partial least-squares regression method, and a linearized perturbation model around the reference trajectory is obtained; the control input voltage of the operation is calculated according to a learning law of iterative learning control; the control input voltage obtained through calculation is applied to the induction heating process, so that the billet outlet temperature of the process is obtained; newly obtained process data is added into a historical database, an old data is removed, and the next iteration cycle begins. The method sufficiently utilizes the characteristic of the repeatability of the induction heating process, introduces the iterative learning algorithm, and enables an output temperature trajectory to furthest track an expected temperature trajectory.

The invention provides a stability control method for unfolding of a three-dimensional space tether system operating in a low earth elliptical orbit in an initial stage. A tether is released to a desired length and the swing of the tether is restrained only by adjusting the limited tether tension without relying on other thrusters. The method comprises the following steps that S1, a two-body spacetether system dynamic model considering tether mass is established; S2, under the conditions such as disturbance, uncertainty, underactuation, restricted tether swing angle and tether tension, basedon a nonlinear model predictive control (NMPC) algorithm, a pseudo-spectral algorithm is used for discretizing an original nonlinear model, and an open loop optimal problem in predictive control is transformed into a nonlinear programming problem for solving; and S3, according to the solution of the nonlinear programming problem, the control quantity of the next control period is determined to form the closed-loop control. Finally, the three-dimensional space tether system operating in the low earth elliptical orbit is stably released and unfolded in the initial stage.

The invention relates to a comprehensive energy utilization system for desert and an operation method thereof. The comprehensive energy utilization system comprises a wind driven generator, a solar photovoltaic module, a solar heat collector, a heat storage tank, a fermentation tank, a gas storage tank, a biogas generator, a lithium bromide unit, a storage battery energy storage device, a fresh water preparation device, a fresh water reservoir, a psammophyte plantation, a desert animal breeding garden, a water pump and a bitter alkaline water tank. According to the invention, the renewable energy sources of solar energy and wind energy enriched in the desert area are fully utilized, and the generated clean electric energy meets the power consumption of the area. The storage battery energy storage device stores generated surplus electric energy when wind and light resources are rich, the gas storage tank is used for the biogas power generation system, the waste heat utilization system conducts gradient utilization on waste heat of a biogas power generator, and the solar heat collector and the heat storage tank supply energy to the system to achieve multiple guarantees of heat sources.

The invention discloses a method for capturing a special laser processing beam spot through projection imaging, belonging to the scope of semi-conductor manufacturing equipment. A series of transmitting graphics are designed on a photolithography mask, and the photolithography mask is moved through a driving mechanism so as to select a specific transmitting graphic on the photolithography mask. The incident laser beams pass through the specific transmitting graphic on the photolithography mask, then enter a projection imaging lens group and are projected and form an image on the surface of a wafer, forming a desired lasing beam spot. With sharp edges, the beam spot sufficiently restrains the uncertainty of process control in laser processing caused by the diffraction effect. On the other hand, since the series of transmitting graphics can be put on the photolithography mask and the ratio of the projection photolithographic system can be designed to be variable, the geometric shape and the size of the laser beam spot obtained through the method are freely adjustable. Therefore, the method can ensure to obtain ideal and evener process control effect in laser processing.

The invention discloses a coal-fired unit drum boiler water level control method for improving transient performance based on parameter self-adaptation. The method includes the following steps that atransfer function model of a known coal-fired unit drum boiler water feeding system control model is equivalently converted into a state space model, the measuring error is considered, the tracking error is defined, system transformation is carried out through the error conversion technology, a self-adaptive control law is designed for a transformed system, and the error between the water level actual value and the set value of a water feeding system is kept within the error bound preset by a user. Meanwhile, the situations that parameters are unknown and bounded disturbance exists are considered in the control method. The control method can overcome the uncertainty in existing models and enhance the robustness of the control system and has anti-disturbance capacity. In addition, by meansof the method, the transient output error of the system is kept within a preset boundary layer, it can be guaranteed that the overshoot is not too large, the control effect is improved as much as possible while safety production is guaranteed, and then the production efficiency is improved.