Jie Bao

Has grant

Professor

University of New South Wales

Australia

Research Interests

Explore related searches

Professors in Australia

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

Recent Grants

Grant: Close

An Integrated Approach to Distributed Fault Diagnosis and Fault-tolerant Control for Plantwide Processes

Open Date: 2016-01-01

Close Date: 2018-12-01

Grant: Close

Control of Distributed Energy Storage System using Vanadium Batteries

Open Date: 2015-01-01

Close Date: 2017-12-01

Grant: Close

Dissipativity based distributed model predictive control for complex industrial processes

Open Date: 2013-01-01

Close Date: 2015-01-01

Grant: Close

Dissipativity based distributed model predictive control for complex industrial processes

Open Date: 2013-01-01

Close Date: 2015-12-01

Grant: Close

Anode current distribution monitoring and analysis

Open Date: 2013-01-01

Close Date: 2015-12-01

Articles (13)

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Collaborators (1)

Biao Huang

Professor

University of Alberta

CANADA

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Jie Bao

Research Interests

Explore related searches

Contact this professor

Recent Grants

Articles (13)

A big data-driven predictive control approach for nonlinear processes using behaviour clusters

An Approach to Data-Based Linear Quadratic Optimal Control

Hybrid Cooling-Based Thermal Management of Containerised Vanadium Flow Battery Systems in Photovoltaic Applications

Thermal Modelling and Simulation Studies of Containerised Vanadium Flow Battery Systems

A contraction-constrained economic Model Predictive Control for nonlinear processes using multi-timescale models

Data-Based Fault Diagnosis via Dissipativity-Shaping

Distributed Data-driven Predictive Control via Dissipative Behavior Synthesis

On Approximation of System Behavior from Large Noisy Data Using Statistical Properties of Measurement Noise

Multi-level data-predictive control for linear multi-timescale processes with stability guarantee

Discrete‐time contraction constrained nonlinear model predictive control using graph‐based geodesic computation

Discrete-time contraction-based control of nonlinear systems with parametric uncertainties using neural networks

Contraction analysis and control synthesis for discrete-time nonlinear processes

Data predictive control of nonlinear process feature dynamics through latent variable behaviours

Collaborators (1)

Biao Huang

Make your next move.