187 results about "Nonlinear parameters" patented technology

A central air-conditioning system energy consumption simulation method based on a multi-region coupling model comprises the steps that basic data and initial parameters of a cold-chain logistics center site are obtained, and the basic data and the initial parameters are preprocessed; and constructing a multi-region coupling physical mechanism model based on a heat and mass transfer equation, and outputting a physical model state through a finite difference method by taking the basic data and the initial parameters as boundary conditions. And taking the physical model state as the input of a convolutional neural network, extracting short-period penetration load characteristics through time sequence convolution, and outputting a short-period penetration load prediction result. And combining the short-term penetration load prediction result with the cargo thermal parameters and the partition state as the input of a Transform model, and outputting multi-region energy consumption distribution prediction data. And performing strategy optimization processing on the multi-region energy consumption distribution prediction data through MPC, and calculating a preliminary control strategy. And searching a global optimal solution in the high-dimensional nonlinear parameter space through a myxomycete optimization algorithm, and outputting an optimal control strategy.

The invention relates to the technical field of injection molding process control, and discloses an injection molding parameter self-learning collaborative regulation and control system which is characterized in that multi-source parameters such as temperature and pressure are acquired in real time through a data acquisition module, and the multi-source parameters are mapped to a low-dimensional manifold space through a dynamic manifold construction module to decouple a nonlinear coupling relationship; the chaos synchronization control module suppresses external disturbance based on master-slave system design, and the distributed optimization module realizes multi-target real-time decision by adopting a split Bregman algorithm; the execution module converts the optimization instruction into a control signal and triggers closed-loop feedback; and the federated learning architecture realizes cross-device strategy migration by extracting continuous homology features of a manifold space and combining a Hausdorff distance and homeomorphic mapping, and drives a global model to update. According to the invention, the technical problems of difficult dynamic regulation and control of nonlinear parameters, insufficient real-time performance of multi-constraint optimization, low cross-scene repeated parameter adjustment efficiency and lack of self-adaptability of long-term process drift in the injection molding process are solved.

The invention discloses an unmanned aerial vehicle flight path planning method based on an improved star-graffiti algorithm, and belongs to the field of unmanned aerial vehicle flight path planning. The invention relates to a method for carrying out flight path planning on a single task executed by an unmanned aerial vehicle. Firstly, a starting point, a target point position and a threat area range are determined; establishing a route planning cost model based on path cost, angle cost, height cost, speed cost and threat cost; optimizing the established cost model, on the basis of a basic individual algorithm, updating the position of the population by adopting an updating formula with nonlinear parameters hybridized with the individual algorithm, and embedding an elite selection method to improve the optimizing capability; and when an iteration upper limit is reached, obtaining an optimal individual position, namely an optimal track, and realizing track planning. According to the invention, optimization of the algorithm is realized, the calculation result is more flexible and simpler, and premature convergence is avoided.

The invention relates to the technical field of aero-engines, and discloses a dry friction damper multi-target robust optimization method considering multi-source uncertainty, and the method specifically comprises the following steps: 1, quantifying the uncertainty parameters of a dry friction damper; step 2, performing hyper-Latin cube (LHS) sampling on value ranges of geometric parameters and contact parameters caused by abrasion to obtain parameter combination sampling capable of expressing global characteristics in a global sample space; 3, calculating a corresponding nonlinear dynamic response by using a multi-dimensional harmonic balance method (MHBM) by using the nonlinear parameters obtained by sampling; by means of the mode of synchronously optimizing key design parameters of the friction-damping system, the optimal robustness design of the friction-damping system is allowed to be carried out under parameter uncertainty with the purpose of vibration reduction, the damping effect of the dry friction damper is improved, the Pareto optimal solution of the neural network is solved through the genetic algorithm, and the optimal stability of the friction-damping system is improved. Therefore, the multi-objective optimization is realized and the calculation efficiency is improved.

The invention discloses a nonlinear ultrasonic guided wave detection system based on multi-channel receiving, and the system comprises a high-energy fundamental frequency ultrasonic excitation module which is controlled by a trigger signal to generate an electric signal and carries out the amplification and filtering processing; the transmitting transducer generates ultrasonic waves to act on a target object under the excitation of the high-energy fundamental frequency ultrasonic excitation module; the variable-angle receiving transducer array is used for receiving the ultrasonic guided wave signal fed back by the target object and converting the ultrasonic guided wave signal into a feedback electric signal; the ultrasonic acquisition module is used for amplifying the feedback electric signal, sampling the feedback electric signal and converting the feedback electric signal into a digital signal under the instruction of the control and signal processing module; the control and signal processing module comprises an FPGA (Field Programmable Gate Array) chip and an ARM (Advanced RISC Machines) main processor, and is used for controlling the generation of an instruction and performing time domain-frequency domain-space domain information extraction on the digital signal sent by the ultrasonic acquisition module, and calculating to obtain a material nonlinear parameter carried by the guided wave signal; and performing micro-damage evaluation and life prediction based on the nonlinear parameters of the material.

The invention discloses a method and a system for simulating influence of interface pressure of a prefabricated cable intermediate joint on ultrasonic non-linear parameters. The simulation method comprises the following steps: establishing a two-dimensional simulation solid mechanics geometric model; setting material parameters of the solid mechanical geometric model; setting boundary conditions of the solid mechanical geometric model; a solid mechanical geometric model and setting of material parameters and boundary conditions are utilized, and a steady-state mechanical analysis mode is adopted to conduct contact stress simulation under different stress conditions; importing the solid mechanical geometric model subjected to stress simulation into a sound field coupling model, coupling a solid mechanical physical field and an electrostatic physical field in a sound field, and performing ultrasonic signal simulation; and in combination with the actual state of the prefabricated cable intermediate joint, carrying out simulation calculation on the influence of different interface pressures on ultrasonic non-linear parameters. The accurate value of the interfacial pressure can be obtained by analyzing the nonlinear parameters of the echo signals.

The invention provides an ultrasonic nonlinear static parameter monitoring method for creep damage of a high-temperature alloy component, and particularly relates to the technical field of material monitoring. The method comprises the following steps: S1, arranging an ultrasonic probe; s2, determining the emission frequency of the excitation end; s3, respectively calculating an incident angle and an emergent angle of the signal; s4, exciting fundamental frequency ultrasonic waves; s5, receiving the signal and uploading the collected signal to a cloud processing system; s6, carrying out fast Fourier transform and calculating a nonlinear parameter of a static component; s7, establishing a linear relation with creep time, and constructing a creep damage linear quantitative model; s8, calculating a static component nonlinear parameter of the healthy sample; and S9, completing quantitative analysis of the damage by using nonlinear parameters. The method solves the problems that a traditional nonlinear ultrasonic method depends on second harmonic nonlinear parameters, phase velocity matching conditions in the middle and later periods are seriously damaged, response shows a nonlinear trend, unique creep time cannot be determined according to the parameters, and then the unique damage state cannot be determined.

The invention provides a grey wolf optimization feature selection method, device and equipment based on an adaptive mechanism, and relates to the technical field of data processing. The method comprises the following steps: acquiring a data set to be subjected to feature selection, and initializing a grey wolf optimization algorithm; the fitness value of each grey wolf is calculated with the purpose of obtaining the current optimal solution, and three current optimal wolves are obtained; then taking the current optimal three wolves as search guidance, combining a nonlinear parameter control strategy, adopting an improved grey wolf step length updating calculation mode, adaptively adjusting variation intensity in the search process, updating and calculating related parameters, positions and fitness values of each grey wolf, and continuously converging the distance between the prey and the grey wolf in the search process; and calculating the score of each grey wolf, and selecting the solution candidate with the highest score as the optimal solution in the current population until the maximum number of iterations is reached, thereby obtaining a global optimal solution. The method is used for processing feature selection in high-dimensional and complex classification, and is high in convergence speed and high in accuracy.

The invention relates to the technical field of wireless communication, and discloses a digital pre-distortion method for improving the linearity of a power amplifier in a phased array system, which comprises the following steps of: 1, acquiring a nonlinear parameter of the power amplifier under a dynamic load in real time, the nonlinear parameters comprise an input signal amplitude-phase characteristic, a temperature parameter and a quantum tunneling current parameter; 2, generating a pre-distortion compensation signal based on the nonlinear parameter, wherein the pre-distortion compensation signal comprises a quantum phase compensation item and a dynamic phase change compensation item; and step 3, superposing the pre-distortion compensation signal to an original input signal to generate a pre-distortion modulation signal. The linearity of the power amplifier is improved by introducing the quantum phase compensation item and the dynamic phase change compensation item, nonlinear parameters are accurately obtained in real time in a dynamic load environment, and the precision of pre-distortion compensation is improved.

The invention relates to the technical field of radio-frequency signal processing, and discloses a 5G radio-frequency signal amplification method and system, and the method comprises the steps: decomposing an obtained radio-frequency signal into a high-frequency sub-band and a low-frequency sub-band through a multilayer wavelet packet, judging whether the radio-frequency signal is sparse in a wavelet packet domain, and carrying out the sparse reconstruction of an LI norm minimization problem if the radio-frequency signal is sparse; obtaining feature data of each sub-band, extracting a nonlinear transfer function of each sub-band through a CNN-GRU network, and carrying out transfer learning pre-training and dynamic adaptation updating; on the basis of dynamic adaptation update ending, layered memory polynomial calculation and layered model joint output construction, layered model parameter optimization is converted into a least square problem to obtain an error compensation function, and resource allocation is dynamically adjusted according to the peak-to-average power ratio of an input signal; and based on power amplifier state data, holographic sensing is performed on nonlinear parameters of the device through a fusion model, and dynamic changes of the device are compensated through multi-stage calibration and calibration delay is controlled.

The present invention relates to the field of micro-electromechanical technology, and provides a method, device, equipment and medium for determining nonlinear parameters of a motor. The present invention can improve the accuracy and efficiency of determining nonlinear parameters of a motor during motor testing. The method includes: constructing a nonlinear model of the nonlinear parameters of the motor, using an excitation signal to drive the motor to vibrate, obtaining the voltage measurement values ​​at both ends of the motor in a vibrating state, the motor current measurement values ​​and the motor vibrator acceleration measurement values, and then obtaining the motor vibrator velocity and vibrator displacement based on the motor vibrator acceleration measurement values, and then constructing an overdetermined equation group associated with the nonlinear model based on the nonlinear model, fitting the overdetermined equation group according to the aforementioned voltage measurement values, motor current measurement values ​​and motor vibrator acceleration measurement values, and obtaining the aforementioned nonlinear parameters.

The invention aims to provide a cooperative control algorithm for realizing motor synchronization and load position tracking so as to effectively solve the problem of coupling control of motor synchronization and load tracking and the problems of unknown system state, unknown nonlinearity and parameter uncertainty estimation and compensation, so that a multi-motor servo system has the characteristics of rapidness, accuracy and stability. In order to achieve the purpose, the technical scheme of the invention provides a multi-motor servo system cooperative control method based on an adaptive observer. Aiming at a multi-motor servo system, through the steps of model conversion, self-adaptive observer design, self-adaptive cooperative control design and the like, the influence of an unknown system state, unknown parameters and nonlinearity is solved, and rapid motor synchronization and accurate load position tracking control are realized.

The invention relates to the technical field of image signal processing, and discloses an agent-free ISP hyper-parameter high-speed optimization method and system, and the method comprises the following steps: collecting RAW data through a sensor, carrying out the black level correction, and initializing the ISP register parameter mapping; a multi-dimensional state vector is constructed by combining the coded image and the parameters, and the master and slave agents generate discrete adjustment amounts in parallel; after a register is updated through nonlinear quantization, a composite reward is calculated based on target detection and image quality, and data is stored and network parameters are updated through a priority experience pool; the system comprises a sensor module, an ISP hardware processing unit, a master-slave agent decision module, a reward calculation module, a register mapping module and an experience playback module. According to the method, hardware-in-the-loop and deep reinforcement learning are combined, and the problems of proxy model distortion, response lag, high data dependence and parameter mutation are solved through master-slave agent parallel decision, a self-supervision reward mechanism and nonlinear parameter mapping.

The invention discloses a finite element simulation method for motion of a magnetically-driven spiral micro-robot in a fluid environment, and belongs to the technical field of finite element simulation. According to the method, a micro-robot model containing a streamline head and a spiral empennage and a fluid environment are constructed through COMSOL software, a peristaltic flow module and a multi-body dynamics module are integrated through the fluid-solid coupling technology, and a fluid-solid coupling transient motion equation is established. The motion characteristics of the micro-robot driven by a rotating magnetic field are accurately simulated by setting material nonlinear parameters, dynamic self-adaptive grid division and a non-uniform step size solving strategy. A rigid domain motion equation and an open boundary condition are innovatively introduced, speed and acceleration probes are combined for real-time monitoring, and the flow field vortex effect caused by spiral propulsion is captured. According to the method, the simulation error is controlled within 5%, the motion trail prediction precision is remarkably improved, a reliable simulation platform is provided for micro-robot structure optimization and magnetic control strategy design, the experiment cost is reduced, and the research and development period is shortened.

The invention belongs to the technical field of crossing of high polymer materials and artificial intelligence, and discloses a method for optimizing the proportion of a nano-composite flame-retardant master batch in engineering plastic based on machine learning. The method is used for solving the problems that a traditional experience trial and error method is low in efficiency in multi-target performance collaborative optimization, high-dimensional nonlinear parameter space search is difficult, and microscopic coupling effect modeling is missing. According to the method, a multi-dimensional input feature set containing material composition and process parameters is constructed, six key performance indexes are combined to form training data, a mixed model formed by cascading a multi-layer perceptron and Gaussian process regression is trained, an improved non-dominated sorting genetic algorithm (NSGA-II) is adopted for multi-target global optimization, and an optimal ratio meeting preset constraints is obtained. The method is an industrial internet technology system service, and solves the technical problem that multi-target performance is difficult to collaboratively optimize due to the fact that a traditional experience trial-and-error method cannot perform modeling and searching on a high-dimensional nonlinear parameter space of a nano-composite flame-retardant system.

The invention discloses a time-varying parameterization nonlinear system dynamic surface control and simulation method with extended time-varying constraint, and relates to the field of nonlinear system stabilization and control, and the method comprises the steps: introducing a tangent function as nonlinear mapping in a controller design process, a nonlinear parameter system with time-varying parameters and extended full-state time-varying constraints is converted into a new unconstrained parameterized system. In addition, an improved DSC with an error compensation signal is used, and a new adaptive control technology is provided for a converted nonlinear system. The proposed design scheme avoids assuming that a virtual control coefficient and an upper limit thereof are known, and proves that all signals in a closed-loop system are in semi-global end consistency bounded. A simulation result verifies the effectiveness of the method.

The invention belongs to the technical field of ultrasonic imaging, and particularly relates to an ultrasonic nonlinear parameter imaging method and system, a medium and a program product. The method comprises the following steps: calculating a fundamental signal and a harmonic signal based on an ultrasonic echo RF signal; extracting the amplitude of the fundamental wave signal and the amplitude of the harmonic wave signal, and calculating to obtain a fundamental wave amplitude ratio and a harmonic wave amplitude ratio; calculating an initial value of a nonlinear coefficient according to a ratio of the fundamental wave amplitude ratio to the harmonic wave amplitude ratio, and estimating a value range of the nonlinear coefficient by using a Newton iteration method; and generating an ultrasonic image based on the value range of the nonlinear coefficient. In the ultrasonic non-linear parameter imaging process, a method for solving a non-linear coefficient by adopting a Newton iteration method is further disclosed, so that the dynamic range of the estimated non-linear coefficient value is expanded, the distinguishing between normal tissues and focus tissues in an obtained ultrasonic image is more obvious, and the sensitivity is higher.

The invention discloses a non-linear ultrasound-based soft package battery internal tiny foreign matter imaging method, which belongs to the field of power battery manufacturing, and comprises the following steps: exciting and receiving non-linear ultrasound on the surface of a soft package battery by using a non-linear ultrasound measurement system, and extracting a non-linear ultrasound time domain signal carrying foreign matter information; performing C scanning on the soft package battery by adopting a three-degree-of-freedom motion platform, and obtaining acoustic nonlinear parameters and spatial distribution of the acoustic nonlinear parameters based on the position of a focused ultrasonic transducer, the nonlinear ultrasonic time domain signal and the frequency spectrum; performing normalization processing on the acoustic nonlinear parameters, and constructing a function relationship between the normalized acoustic nonlinear parameters and different foreign matters; and inverting the size and the position of the foreign matter based on the function relationship between the normalized acoustic nonlinear parameter and different foreign matters and the spatial distribution of the acoustic nonlinear parameter.

Aspects relate to signaling relating to a non-linearity model for power amplifier circuitry of a transmitting device. The power amplifier circuitry may apply digital pre-distortion (DPD) to a signal prior to amplification and transmission of the signal. A receiving device may apply digital post-distortion (DPoD) to a signal received from the transmitting device where the DPoD is based on the non-linearity model. The transmitting device may send to the receiving device non-linearity parameters for the non-linearity model.

The invention relates to a direct current furnace machine-furnace coordination system dynamic modeling method suitable for a wet condition. Based on the law of mass conservation and energy conservation, a lumped parameter method is adopted to construct a dynamic model comprising a coal pulverizing system, a coal economizer-water wall system, a water storage tank system, a superheater system and a steam turbine system; identifying parameters are optimized step by step by only utilizing unit variable load dynamic operation data and combining with the mechanism constraint that the heat absorption capacity of a working medium is monotonically increased along with the coal quantity as fired: static parameters are determined through dynamic data regression, nonlinear parameters are optimized based on a preset water-cooled wall outlet flow and dryness function structure, and the heat absorption capacity of the working medium is calculated. And finally, identifying dynamic parameters step by step by adopting an immune genetic algorithm. The dynamic characteristics and the physical consistency of the established model are verified through open-loop simulation, and the technical problems that dynamic description of the water level of the water storage tank is missing and the modeling precision is low under the wet working condition are solved.

The invention discloses a sine frequency modulation harmonic error compensation method based on Bessel function modulation characteristics, and relates to the technical field of sine frequency modulation nonlinear parameter compensation and high-precision measurement of target absolute distance based on multi-wavelength interference. The problem that the constant phase demodulation precision is insufficient due to the fact that carrier harmonic waves, accompanying amplitude modulation and modulation depth errors cannot be effectively suppressed due to laser modulation nonlinearity in existing sine frequency modulation distance measurement is solved. According to the method, after sine frequency modulation interference signals are collected, high-pass filtering is carried out to remove low-frequency components, Hilbert transform is carried out to remove envelope suppression associated amplitude modulation, window function frequency mixing is carried out to extract modulation depth, a matched carrier containing second harmonics is constructed, and frequency modulation harmonic parameter optimization is achieved through baseband amplitude maximization. And finally, carrying out orthogonal demodulation on the compensated interference signal to obtain a high-precision constant phase. The method is suitable for high-precision multi-wavelength interference ranging, precision displacement measurement and optical metering systems.

The invention provides a gap nonlinear control surface flutter wind tunnel test system and method based on steering engine excitation. The system comprises a wind tunnel test section, a test object and a parameter-adjustable excitation mechanism outside a wind tunnel field, wherein the parameter-adjustable excitation mechanism is composed of a transverse clamping mechanism, a longitudinal supporting mechanism, an excitation system and an angle sensor. The excitation system comprises a steering engine, a steering engine rocker arm and a connecting rod, one end of a spring rod is fixed to the longitudinal supporting mechanism, and the other end is in clearance fit with the connecting rod. By adjusting the effective length of the spring rod, the fit clearance and the excitation of the steering engine, the clearance nonlinear rigidity applied to the test control surface can be changed. In a wind tunnel test, an angle sensor is used for collecting rudder shaft rotation angular displacement response in real time, excitation-response characteristic testing before and after flutter occurs is achieved, and the influence rule of gap nonlinear parameters on rudder surface dynamic characteristics is effectively studied. The test principle is simple, and a new way is provided for excitation-response characteristic measurement of the full-motion control surface under different gap nonlinear rigidities.

The invention discloses a composite material storage life prediction method based on variable transformation and a genetic algorithm, and relates to the technical field of composite material performance evaluation and life prediction, and the method comprises the steps: obtaining performance degradation data at different temperatures through an accelerated aging test, and building a semi-empirical performance degradation model; specific variable transformation is introduced, a nonlinear optimization problem is converted into a linear regression problem, partial model parameters are rapidly solved by adopting a least square method, and meanwhile, key nonlinear parameters are globally optimized by using a genetic algorithm, so that the defect that a traditional method is easy to fall into local optimum is overcome. And establishing a temperature-service life relationship by combining with an archenius model, and realizing storage life prediction at normal temperature. The method also integrates sensitivity analysis and uncertainty quantification functions, and provides reliability evaluation for a prediction result. The method fully considers the influence of the environment temperature, meets the requirement of efficient prediction, and improves the precision and stability of life prediction.

The invention discloses a test method and device for measuring nonlinearity of a phase modulator, and belongs to the technical field of measurement, the device comprises a laser source, a polarization controller, a beam splitter, the phase modulator, a coupler, a photoelectric detector, a microwave source I, an acousto-optic frequency shifter, a microwave amplitude phase detection module and a microwave source II; the laser source is used for outputting a fixed-frequency optical signal to the polarization controller; the polarization controller is used for compensating the polarization state of the optical signal; the beam splitter is used for equally dividing an optical signal into two paths, the first path of optical signal is transmitted to the phase modulator, and the second path of optical signal is transmitted to the acousto-optic frequency shifter; by means of the mode, the problem that the phase modulator directly enters the photoelectric detector, photoelectric conversion cannot be conducted, and nonlinear parameters cannot be detected is solved.

The invention provides a digital-analog hybrid verification method for a clock chip, and the method comprises the steps: building a test top layer based on an analog circuit top layer of the clock chip, and extracting an analog verilog circuit model; completing module-level simulation by using an analog circuit to obtain a nonlinear parameter and a jitter clock parameter; the nonlinear parameters and the jitter clock parameters are inserted into a verilog circuit model to complete nonlinear modeling, and a digital-analog hybrid simulation environment is built in cooperation with a digital RTL / digital netlist; and applying test excitation in a digital-analog hybrid simulation environment to lock the phase-locked loop, and periodically acquiring data to calculate a jitter index so as to complete digital-analog hybrid simulation verification of the clock chip. According to the method, the nonlinear TDC, DTC and DCO models and the jitter clock model are introduced into the digital-analog hybrid verification of the clock chip, so that the simulation can be closer to a real scene, the simulation result is more reliable, and the simulation speed is higher.

The invention discloses a battery off-line and on-line hybrid modeling method and device, a storage medium and a product. The method comprises the following steps: constructing a state dependent model of a battery; determining a state vector according to the state parameter of the battery; taking the state vector as input, and determining a function type coefficient of the state dependent model; converting the state-dependent model into a nonlinear least square model; according to the obtained battery measurement data, performing offline optimization on parameters of the nonlinear least square model by adopting an optimization algorithm to obtain all parameters, and further obtaining a battery offline model; and keeping the non-linear parameters of the battery offline model unchanged, and updating the linear parameters in the battery offline model online according to the real-time measurement data of the battery so as to obtain a real-time updated state dependent model. According to the method, high-precision modeling of the lithium ion battery is realized on the premise of ensuring real-time performance.

The invention discloses a nano-scale displacement real-time compensation measurement method and system based on double-frequency laser interference, and belongs to the technical field of precision measurement. In order to solve the problems that three error sources of environmental drift, periodic nonlinear error and dynamic vibration are mutually coupled and have high real-time requirements in dual-frequency laser interference measurement, a multi-source error unified state space model including measured displacement, an air refractive index parameter, a nonlinear error parameter and a vibration disturbance quantity is constructed. A high-dimensional state vector is divided into a displacement-refractive index group and a nonlinear parameter group by adopting an extended Kalman filter of a grouping updating strategy, the displacement-refractive index group and the nonlinear parameter group are alternately updated in an assembly line parallel mode, nonlinear parameters are identified in real time in combination with an online recursive least square algorithm, and the state of the filter is corrected through a state coupling injection mechanism. Real-time compensation with the end-to-end delay smaller than 80 microseconds is achieved, the displacement measurement residual error is controlled within + / -0.3 nm under the composite disturbance condition, and the method is suitable for precise assembly of intelligent glasses optical assemblies.

The invention provides an underwater robot adaptive control method and device, electronic equipment and a medium, and the method comprises the steps: determining a first posture prediction model of an underwater robot according to a dynamic model of the underwater robot; identifying a to-be-identified parameter of the first attitude prediction model according to the motion data; determining a first attitude of the underwater robot according to the first attitude prediction model, the identification parameters and the motion data; predicting a second attitude of the underwater robot at a second moment according to the first attitude and a control algorithm to obtain a prediction result; determining a control algorithm of the underwater robot according to the first attitude and nonlinear parameters of the underwater robot; according to the control algorithm, a control instruction for the underwater robot is determined, and self-adaptive control over the underwater robot is completed according to the control instruction. The method has the beneficial effect that the accurate adaptive control of the underwater unmanned aerial vehicle is realized.

The invention discloses a phase-control multi-channel nonlinear ultrasonic nondestructive testing system and method based on phase reversal excitation, and the method comprises the steps: generating multi-channel phase reversal waveform data and a control instruction by an upper computer, carrying out the nonlinear parameter extraction of a received digital signal, and calculating a nondestructive testing result; the phase-control high-energy fundamental frequency ultrasonic excitation module suppresses a fundamental frequency signal for the electric signal with the phase reversal waveform, enhances the harmonic amplitude, and performs delay excitation to realize fixed-point focusing; the transmitting transducer array and the receiving transducer array convert the electric signal and the acoustic signal; the multi-path double-band-pass filter is used for carrying out fundamental wave suppression, harmonic wave enhancement and clutter filtering to enhance a nonlinear effect and improve a signal-to-noise ratio; and the phase-controlled ultrasonic acquisition module is used for filtering, amplifying and sampling the multi-channel feedback electric signal and converting the multi-channel feedback electric signal into a digital signal. The method has the multi-channel nonlinear ultrasonic evaluation capability, can realize multi-channel phase reversal waveform excitation, has the ultrasonic fixed-point focusing capability, and remarkably improves the nonlinear effect detection result, so that the detection result is more accurate.

This model parameter estimation device comprises a state quantity calculator to calculate state quantities indicating a state of a target system with respect to a measured value of an input on the basis of a state equation obtained by assigning values to nonlinear parameters for a model that represents the target system using the nonlinear parameters and linear parameters, and time-series data of the input and an output of the target system, a linear parameter estimator to estimate the linear parameters that minimize an error between the measured value of the output and an estimated value of the output calculated on the basis of the model, the state quantities, and the measured value of the input, and a nonlinear parameter updater to repeatedly update the values of the nonlinear parameters so as to make the minimized error to be small until a convergence condition is satisfied.