Hi everyone, I aim to build a model of my system using real-time data. My system is a MIMO (Multiple Input Multiple Output) system, where the inputs are RPM and rudder angle, and the outputs are linear velocity and angular velocity. Also the system is cross-coupled, so both inputs effect both outputs and I think that there is nonlinear model. I want to implemented system identification model. I collected data for train and validation. Then, I implemented filter and prepared for system identification. I tried different models such as TF, State Space and Nonlinear models. I see that best models estimated by Nonlinear ARX model. But I don’t know how can I find the best model fit because there are many options in Nonlinear ARX model window. For example there are many options in Nonlinear Function bar such as Wavelet, Sigmoid, Neural, Gaussian etc… So how can i find best model fit. Do I need to write code about grid search may be it finds best possible trying different conditions? Do you have any recommendation?Hi everyone, I aim to build a model of my system using real-time data. My system is a MIMO (Multiple Input Multiple Output) system, where the inputs are RPM and rudder angle, and the outputs are linear velocity and angular velocity. Also the system is cross-coupled, so both inputs effect both outputs and I think that there is nonlinear model. I want to implemented system identification model. I collected data for train and validation. Then, I implemented filter and prepared for system identification. I tried different models such as TF, State Space and Nonlinear models. I see that best models estimated by Nonlinear ARX model. But I don’t know how can I find the best model fit because there are many options in Nonlinear ARX model window. For example there are many options in Nonlinear Function bar such as Wavelet, Sigmoid, Neural, Gaussian etc… So how can i find best model fit. Do I need to write code about grid search may be it finds best possible trying different conditions? Do you have any recommendation? Hi everyone, I aim to build a model of my system using real-time data. My system is a MIMO (Multiple Input Multiple Output) system, where the inputs are RPM and rudder angle, and the outputs are linear velocity and angular velocity. Also the system is cross-coupled, so both inputs effect both outputs and I think that there is nonlinear model. I want to implemented system identification model. I collected data for train and validation. Then, I implemented filter and prepared for system identification. I tried different models such as TF, State Space and Nonlinear models. I see that best models estimated by Nonlinear ARX model. But I don’t know how can I find the best model fit because there are many options in Nonlinear ARX model window. For example there are many options in Nonlinear Function bar such as Wavelet, Sigmoid, Neural, Gaussian etc… So how can i find best model fit. Do I need to write code about grid search may be it finds best possible trying different conditions? Do you have any recommendation? model, system MATLAB Answers — New Questions

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