Challenges and opportunities on nonlinear state estimation of chemical and biochemical processes
This paper provides an overview of nonlinear state estimation techniques along with a
discussion on the challenges and opportunities for future work in the field. Emphasis is given …
discussion on the challenges and opportunities for future work in the field. Emphasis is given …
Intelligent particle filter and its application to fault detection of nonlinear system
The particle filter (PF) provides a kind of novel technique for estimating the hidden states of
the nonlinear and/or non-Gaussian systems. However, the general PF always suffers from …
the nonlinear and/or non-Gaussian systems. However, the general PF always suffers from …
Process fault diagnosis with model-and knowledge-based approaches: Advances and opportunities
Fault diagnosis plays a vital role in ensuring safe and efficient operation of modern process
plants. Despite the encouraging progress in its research, develo** a reliable and …
plants. Despite the encouraging progress in its research, develo** a reliable and …
Enhanced particle filtering for bearing remaining useful life prediction of wind turbine drivetrain gearboxes
Bearing is the major contributor to wind turbine gearbox failures. Accurate remaining useful
life prediction for drivetrain gearboxes of wind turbines is of great importance to achieve …
life prediction for drivetrain gearboxes of wind turbines is of great importance to achieve …
Propagating input uncertainties into parameter uncertainties and model prediction uncertainties—A review
A review of uncertainty quantification techniques is provided for a variety of situations
involving uncertainties in model inputs (independent variables). The situations of interest are …
involving uncertainties in model inputs (independent variables). The situations of interest are …
State estimation in nonlinear system using sequential evolutionary filter
As a commonly encountered problem in the particle filters (PFs), the particle impoverishment
is caused partially by the reduction of particle diversity after resampling. In this paper, a …
is caused partially by the reduction of particle diversity after resampling. In this paper, a …
Target tracking algorithm based on adaptive strong tracking particle filter
L Jia‐qiang, Z Rong‐hua, C **‐li… - IET Science …, 2016 - Wiley Online Library
The primary problem of tracking filtering algorithms is the tracking stability and effectiveness
of target states. Based on the particle filter, an adaptive strong tracking particle filter …
of target states. Based on the particle filter, an adaptive strong tracking particle filter …
Evaluation of a combined MHE-NMPC approach to handle plant-model mismatch in a rotary tablet press
The transition from batch to continuous processes in the pharmaceutical industry has been
driven by the potential improvement in process controllability, product quality homogeneity …
driven by the potential improvement in process controllability, product quality homogeneity …
Predictive control optimization based PID control for temperature in an industrial surfactant reactor
Due to the character of nonlinearity, uncertainties, time delays and so on in the industrial
reactors, the performance of proportional-integral-derivative (PID) control cannot always …
reactors, the performance of proportional-integral-derivative (PID) control cannot always …
Performance assessment, diagnosis, and optimal selection of non-linear state filters
Non-linear state filters of different approximations and capabilities allow for real-time
estimation of unmeasured states in non-linear stochastic processes. It is well known that the …
estimation of unmeasured states in non-linear stochastic processes. It is well known that the …