Advanced control

Background

A great deal attention has been paid to highly nonlinear systems under uncertainty in research areas or industries. Designing optimization based control strategies considering  uncertainties in measurements and experiments promotes the performances of complex dynamic systems such as blow-down wind tunnels, e-drive motors, hybrid energy systems (Fig.1).

  

Fig.1 Dynamic systems

Methodology

The ongoing projects in our lab foucus on the technical problems in energizing Permanet Magnet Synchronous Motor (PMSM), whose structure is shown in Fig.2. The main concerns are:

  1. Control of PMSM (reference tracking, servo)  PMSM dynamics control concerns the tracking performance of PMSM. Benchmark of PMSM control method is Field Oriented Control (FOC). Thus, new method such as Robust Control is proposed trying to overtake FOC.
  2. Energy loss during PMSM driving  PMSM energy loss optimization is a research branch trying to minimize the energy used by the PMSM during its operation.
  3. Hybrid Energy Supplement  PMSM hybrid energy supplement utilize battery and ultracapacitor (UC) to construct a hybrid energy storage system (HESS). The control interest includes system design, energy flow split strategy and battery/UC sizing.

Fig.2 The structure of PMSM

The goal in our lab is to develop Intelligent control strategies in order to:

  • Improve systems’ dynamic performance under different usage conditions and/or scenarios
  • Analyze the mechanism of the energy flow in multi-source energy systems.

Students

RunzeCai, RuixiangZheng