Contents¶
- Introduction
- Models
- System Identification
- Linear or Nonlinear System Identification
- Linear Models
- Nonlinear Models
- NARMAX Methods
- What is the Purpose of System Identification?
- Is System Identification Machine Learning?
- Nonlinear System Identification and Forecasting Applications: Case Studies
- Abbreviations
- Variables
- Book Organization
- NARMAX Model Representation
- Basis Function
- Linear Models
- ARMAX
- ARX
- ARMA
- AR
- FIR
- Other Variants
- Nonlinear Models
- NARMAX
- NARMA
- NAR
- NFIR
- Mixed NARMAX Models
- Neural NARX Network
- General Model Set Representation
- MIMO Models
- Parameter Estimation
- Least Squares
- Total Least Squares
- Recursive Least Squares
- Least Mean Squares
- Extended Least Squares Algorithms
- Model Structure Selection
- Introduction
- The Forward Regression Orthogonal Least Squares
- Case Study
- Information Criteria
- Overview of the Information Criteria Methods
- AIC
- AICc
- BIC
- LILC
- FPE
- Overview of the Information Criteria Methods
- Meta Model Structure Selection (MetaMSS)
- Meta-heuristics
- Standard Particle Swarm Optimization (PSO)
- Standard Gravitational Search Algorithm (GSA)
- The Binary Hybrid Optimization Algorithm
- Meta-Model Structure Selection (MetaMSS): Building NARX for Regression
- Case Studies: Simulation Results
- MetaMSS vs FROLS
- Meta-MSS vs RJMCMC
- MetaMSS algorithm using SysIdentPy
- Accelerated Orthogonal Least Squares
- Entropic Regression
- Multiobjective Parameter Estimation
- Introduction
- Multi-objective optimization problem
- Pareto Optimal Definition and Pareto Dominance
- Affine Information Least Squares Algorithm
- Case Study - Buck converter
- Multiobjective Model Structure Selection
- Introduction
- Multiobjective Error Reduction Ratio
- Multiobjective Meta Model Structure Selection
- Case Studies
- References
- NARX Neural Network
- Introduction
- NARX Neural Network
- NARX Neural Network vs. Recursive Neural Network
- Case Studies
- References
- Severely Nonlinear Systems
- Introduction
- Modeling Hysteresis With Polynomial NARX Model
- Continuous-time loading-unloading quasi-static signal
- Hysteresis loops in continuous time \(\mathcal{H}_t(\omega)\)
- Rate Independent Hysteresis in polynomial NARX model
- Validation
- The
predict
Method in SysIdentPy - Infinity-Step-Ahead Prediction
- One-step Ahead Prediction
- n-step Ahead Prediction
- Model Performance
- Metrics Available in SysIdentPy
- Case study
- The
- Case Studies: System Identification and Forecasting
- M4 Dataset
- Coupled Eletric Device
- Wiener-Hammerstein
- Air Passenger Demand Forecasting
- System With Hysteresis - Modeling a Magneto-rheological Damper Device
- Silver box
- F-16 Ground Vibration Test Benchmark
- PV Forecasting
- Industrial Robot Identification Benchmark (coming soon)
- Two-Story Frame with Hysteretic Links (coming soon)
- Cortical Responses Evoked by Wrist Joint Manipulation (coming soon)
- Total quarterly beer production in Australia (coming soon)
- Australian Domestic Tourism Demand (coming soon)
- Electric Power Consumption (coming soon)
- Gas Rate CO2 (coming soon)
- Number of Patients Seen With Influenza-like Illness (coming soon)
- Monthly Sales of Heaters and Ice Cream (coming soon)
- Monthly Production of Milk (coming soon)
- Half-hourly Electricity Demand in England and Wales (coming soon)
- Daily Temperature in Melbourne (coming soon)
- Weekly U.S. Product Supplied of Finished Motor Gasoline (coming soon)
- Australian Total Wine Sales (coming soon)
- Quarterly Production of Woollen Yarn in Australia (coming soon)
- Hourly Nuclear Energy Generation (coming soon)