Controller Design Based on Echo State Network with Delay Output for Nonlinear System

Abstract

For the nonlinear systems with delay output, the control performance of the system is affected by the previous output of the system, such as crawling robots of photovoltaic panels. In this paper, an improved controller design method based on echo state network with delay output (DO-ESN) is proposed for designing the controller of a class of nonlinear system. According to the internal characteristics of DO-ESN, the DO-ESN can match the system characteristics of nonlinear systems with delay output, such that the proposed controller can quickly meet the control performance of the nonlinear system. In order to ensure the stability of the controller, a sufficient condition is given for the echo state property of DO-ESN. Finally, a simulation example is used to illustrate the effectiveness of the proposed method.

Robust fault diagnosis of a high-voltage circuit breaker via an ensemble echo state network with evidence fusion

“…Only the output weights of the ESN need to be trained by a linear regression algorithm, which avoids gradient disappearance and high computational complexity. Therefore, ESN models have been widely applied in control [29,30], pattern recognition [31,32], and nonlinear time series prediction [33,34]. As a novel research field, machine learning and swarm intelligence approaches have been successfully combined, and outstanding results have been obtained in different areas.…”

Novel hybrid model based on echo state neural network applied to the prediction of stock price return volatility

“…Applications of ESN for stock price return forecasting are found in Zhang, Liang, and Chai (2013) and Dan et al (2014). Other studies that consider the application of ESNs are Yao et al (2019) and Yao (2020). A summary of the ESN performance as reported in previous related studies is presented in Table 1.…”