Modelos de espacio de estados neuronales
Los modelos de espacio de estados neuronales son un tipo de modelos de espacio de estados no lineales en los que las funciones de transición de estado y medición se han modelado utilizando redes neuronales. Puede identificar los pesos y sesgos de estas redes utilizando System Identification Toolbox™. Puede utilizar el modelo entrenado para el control, la estimación, la optimización y el modelado de orden reducido.
Tareas de Live Editor
| Realice la estimación de un modelo de espacio de estados neuronal | Estimate neural state-space model in the Live Editor (Desde R2023b) |
Funciones
createMLPNetwork | Create and initialize a Multi-Layer Perceptron (MLP) network to be used within a neural state-space system (Desde R2022b) |
setNetwork | Assign dlnetwork object as the state or output function of a
neural state-space model (Desde R2024b) |
nssTrainingOptions | Create training options object for neural state-space systems (Desde R2022b) |
nlssest | Estimate nonlinear state-space model using measured time-domain system data (Desde R2022b) |
generateMATLABFunction | Generate MATLAB functions that evaluate the state and output functions, and their Jacobians, of a nonlinear grey-box or neural state-space model (Desde R2022b) |
idNeuralStateSpace/evaluate | Evaluate a neural state-space system for a given set of state and input values and return state derivative (or next state) and output values (Desde R2022b) |
idNeuralStateSpace/linearize | Linearize a neural state-space model around an operating point (Desde R2022b) |
sim | Simulate response of identified model |
Objetos
idNeuralStateSpace | Neural state-space model with identifiable network weights (Desde R2022b) |
nssTrainingADAM | Adam training options object for neural state-space systems (Desde R2022b) |
nssTrainingSGDM | SGDM training options object for neural state-space systems (Desde R2022b) |
nssTrainingRMSProp | RMSProp training options object for neural state-space systems (Desde R2024b) |
nssTrainingLBFGS | L-BFGS training options object for neural state-space systems (Desde R2024b) |
Bloques
| Neural State-Space Model | Simulate neural state-space model in Simulink (Desde R2022b) |
Temas
- What Are Neural State-Space Models?
Understand the structure of a neural state-space model.
- Neural State-Space Model of SI Engine Torque Dynamics
This example describes reduced order modeling (ROM) of the nonlinear torque dynamics of a spark-ignition (SI) engine using a neural state-space model.
- Neural State-Space Model of Simple Pendulum System
This example shows how to design and train a deep neural network that approximates a nonlinear state-space system in continuous time.
- Augment Known Linear Model with Flexible Nonlinear Functions
This example demonstrates a method to improve the normalized root mean-squared error (NRMSE) fit score of an existing state-space model using a neural state-space model.
- Reduced Order Modeling of a Nonlinear Dynamical System Using Neural State-Space Model with Autoencoder
This example shows reduced order modeling of a nonlinear dynamical system using a neural state-space (NSS) modeling technique.
- Reduced Order Modeling of Electric Vehicle Battery System Using Neural State-Space Model
This example shows a reduced order modeling (ROM) workflow, where you use deep learning to obtain a low-order nonlinear state-space model that serves as a surrogate for a high-fidelity battery model.
