Data-driven zero-sum neuro-optimal control for a class of continuous-time unknown nonlinear systems with disturbance using ADP
This paper is concerned with a new data-driven zero-sum neuro-optimal control problem for
continuous-time unknown nonlinear systems with disturbance. According to the input-output …
continuous-time unknown nonlinear systems with disturbance. According to the input-output …
Data-driven control for discrete-time piecewise affine systems
This paper studies the problem of data-driven control for discrete-time piecewise affine
(PWA) systems. Based on a sequel of sampled control inputs and states with satisfactory …
(PWA) systems. Based on a sequel of sampled control inputs and states with satisfactory …
Detection of anomalies in industrial iot systems by data mining: Study of christ osmotron water purification system
MSS Garmaroodi, F Farivar… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Industry 4.0 will make manufacturing processes smarter but this smartness requires more
environmental awareness, which in case of Industrial Internet of Things, is realized by the …
environmental awareness, which in case of Industrial Internet of Things, is realized by the …
Data-driven LQR control design
GRG da Silva, AS Bazanella… - IEEE control systems …, 2018 - ieeexplore.ieee.org
This letter presents a data-driven solution to the discrete-time infinite horizon linear
quadratic regulator (LQR) problem. The state feedback gain is computed directly from a …
quadratic regulator (LQR) problem. The state feedback gain is computed directly from a …
Data-driven control and process monitoring for industrial applications—Part I
This first part of the Special Section presents 13 papers, which can be categorized into three
main topics, namely,“data-driven controller tuning/design”(including six papers [10] …
main topics, namely,“data-driven controller tuning/design”(including six papers [10] …
A novel framework for fault diagnosis using kernel partial least squares based on an optimal preference matrix
J Yi, D Huang, H He, W Zhou, Q Han… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
In the standard kernel partial least squares (KPLS), the mapped data in the feature space
need to be centralized before extraction of new score vectors. However, each vector of the …
need to be centralized before extraction of new score vectors. However, each vector of the …
Multi-objective bacterial foraging optimization algorithm based on parallel cell entropy for aluminum electrolysis production process
Environment-friendly aluminum electrolysis production process has long been a challenging
industrial issue due to its built-in difficulty in optimizing numerous highly coupled and …
industrial issue due to its built-in difficulty in optimizing numerous highly coupled and …
Recognizing the gradual changes in sEMG characteristics based on incremental learning of wavelet neural network ensemble
F Duan, L Dai - IEEE Transactions on Industrial Electronics, 2016 - ieeexplore.ieee.org
Most myoelectric prosthetic hands use a fixed pattern recognition model to identify the user's
hand motion commands. Since surface electromyogram (sEMG) characteristics vary with …
hand motion commands. Since surface electromyogram (sEMG) characteristics vary with …
Real-time optimization of automatic control systems with application to BLDC motor test rig
Driven by the increasing demands on production quality, system performance, and the
reliability and safety issues of process industry, this paper proposes an integrated process …
reliability and safety issues of process industry, this paper proposes an integrated process …
An indirect data-driven method for trajectory tracking control of a class of nonlinear discrete-time systems
This paper presents an indirect data-driven method for the trajectory tracking control
problem of a class of nonlinear discrete-time systems, which have unknown dynamics. This …
problem of a class of nonlinear discrete-time systems, which have unknown dynamics. This …