神经网络由于其在非线性系统建模与优化求解方面的优势, 被广泛应用于预测控制中,
形成了各种各样的神经网络预测控制算法. 本文系统地评述了非线性系统神经网络预测控制系统 …

In the Proportional-Integral-Derivative (PID) controllers the control signal is a linear function
of: the current control error (the proportional part), the past errors (the integral part) and the …

Reliable and timely fault detection and isolation are necessary tasks to guarantee
continuous performance in complex industrial systems, avoiding failure propagation in the …

This study deals with the design of a cell puncture mechanism (CPM) driven by a
piezoelectric actuator to complete the cell puncture process. Then, a novel robust controller …

This study compares the multi-period predictive ability of linear ARIMA models to nonlinear
time delay neural network models in water quality applications. Comparisons are made for a …

The manuscript addresses the problem of developing a modelling strategy that can
accurately capture the dynamics of a non-linear batch process, demonstrated on a uni-axial …

Model Predictive Control (MPC) algorithms typically use the classical L 2 cost function,
which minimises squared differences of predicted control errors. Such an approach has …

Artificial neural network modeling techniques have been recognized as important vehicles in
the microwave computer‐aided design (CAD) area in addressing the growing challenges of …

Behavioral modeling of nonlinear dynamic systems for control design and system monitoring
of technical systems is a non-trivial task. One example is fault diagnosis where the objective …

We present a state-space dynamic neural network (SSDNN) method for modeling the
transient behaviors of high-speed nonlinear circuits. The SSDNN technique extends the …