Nonlinear Systems

Training Neural Networks with MATLAB to Predict Nonlinear System Outputs

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First, input a sine signal into the nonlinear system to obtain a set of input-output data, train a neural network, and then use this neural network to predict the output of the nonlinear system. %shenjingwangluoxunlian close all clear ; y_1=0; y_2=0; z_1=0; z_2=0; t1=0:0.05:50; u1=10*sin(2*pi*5*t1); Len=length(u1); yy1=zeros(1,Len); for k1=1:Len z_0=u1(k1); y_0=0.2*y_1/(1.5+0.1*y_1*y_1)-0.4*y_2-0.8*z_1+0.6*z_1*z_2; yy1(k1)=y_0; y_2=y_1; y_1=y_0; z_2=z_1; … Read more

Real-Time Calibration of Models and Accurate Estimation of Lettuce Dry Weight Using Greenhouse Climate Data Without Crop Sensors

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Real-Time Calibration of Models and Accurate Estimation of Lettuce Dry Weight Using Greenhouse Climate Data Without Crop Sensors

Introductionใ€€ใ€€By utilizing standard greenhouse climate sensing (CO2, temperature, humidity), accurately estimate the dry weight of lettuce, online identify and correct deviations in key model parameters, achieving low-cost and high-precision non-destructive monitoring of crops. Research Background and Scientific Issuesใ€€ใ€€The precise climate control of high-tech greenhouses relies on an accurate understanding of crop status. However, direct measurements … Read more

MATLAB Example: CKF (Cubature Kalman Filter) Filtering Routine for Two-Dimensional Nonlinear Systems with Nonlinear States and Observations, Code Download Link Included

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MATLAB Example: CKF (Cubature Kalman Filter) Filtering Routine for Two-Dimensional Nonlinear Systems with Nonlinear States and Observations, Code Download Link Included

The state equation and observation equation are both two-dimensional and nonlinear. There are Chinese comments, and you can modify the code as needed.<span>After subscribing to the column, you can directly view the source code, paste it into a MATLAB empty script, and run it to obtain results.</span> Article Directory Program Introduction Running Results MATLAB Source … Read more

MATLAB | Diffusion Mapping + Linear Kalman Filtering + Koopman Operator | A Non-Parametric Method for State Estimation of High-Dimensional Nonlinear Stochastic Dynamical Systems

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MATLAB | Diffusion Mapping + Linear Kalman Filtering + Koopman Operator | A Non-Parametric Method for State Estimation of High-Dimensional Nonlinear Stochastic Dynamical Systems

Click the blue text above to follow us ๐Ÿ“‹๐Ÿ“‹๐Ÿ“‹ The contents of this article are as follows: ๐ŸŽ๐ŸŽ๐ŸŽ Contents ๐Ÿ’ฅ1 Overview ๐Ÿ“š2 Results ๐ŸŽ‰3 References ๐ŸŒˆ4 MATLAB Code, Data, Articles 1 Overview Abstract: This article presents a non-parametric method for state estimation of high-dimensional nonlinear stochastic dynamical systems, which evolve according to a gradient flow … Read more