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Nonlinear system identification for cascaded block model: an application to electrode polarization impedance
1Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA 19104.
IEEE Transactions on Bio-Medical Engineering
|June 1, 1990
Summary
A novel algorithm identifies cascaded linear-nonlinear-linear systems using input-output data. This method accurately models complex systems, including nonlinear phenomena in noble metal electrodes, without prior knowledge.
Area of Science:
- Systems identification
- Nonlinear dynamics
- Control theory
Background:
- Complex systems often comprise cascaded linear and nonlinear subsystems.
- Accurate modeling of these systems is crucial for analysis and control.
- Existing methods may require prior knowledge or specific input signals.
Purpose of the Study:
- To develop a new algorithm for identifying cascaded LNL systems.
- To model systems based strictly on input-output relationships.
- To validate the algorithm with numerical examples and experimental data.
Main Methods:
- Utilizes multilevel input signals to decouple linear and nonlinear subsystems.
- Employs a predictor-corrector algorithm to minimize a cost function and estimate parameters.
- Assumes the nonlinear element is equicontinuous or satisfies the Weierstrass criterion.
Main Results:
- The algorithm successfully identifies systems with continuous or abrupt nonlinearities.
- Numerical examples show consistent results across step, sinusoidal, and white noise inputs.
- The method was applied to model the interfacial phenomenon of platinum electrodes.
Conclusions:
- The developed algorithm provides a robust method for identifying LNL systems.
- It is versatile, applicable to various nonlinearity types and input signals.
- The approach is validated through successful modeling of a real-world electrochemical system.