Intelligent Control of Six-Phase Permanent Magnet Synchronous Motor Drive System for Electric Power Steering System(2/3)

Project Details


The purpose of this project is to develop a digital signal processor (DSP)-based intelligent control of six-phase permanent magnet synchronous motor (PMSM) on electric power steering (EPS) system. In the first year of this project, the EPS system based on a six-phase PMSM is designed, and the dynamic model of six-phase PMSM and the EPS system are both analyzed and derived. Moreover, the DSP-based motor drive and control system is developed to actuate the EPS system based on a six-phase PMSM. Since the EPS system is highly nonlinear and is very sensitive to the uncertainties including parameter variations and external disturbance, the control accuracy is very sensitive to the uncertainties. From the reason stated above, the stability of EPS system is the most important issue in the whole development of the system. Thus, in the second year of this project, an improved differential evolution (IDE) wavelet fuzzy neural network with asymmetric membership function (WFNN-AMF) is proposed for the position control of the six-phase PMSM based EPS system. In this control system, the learning rates of IDE WFNN-AMF are adapted online using improved differential evolution algorithm. The developed IDE algorithm has several advantages, such as easy to implement, fast convergence and simple structure, instead of the time-consuming trial and error method. Furthermore, an intelligent two-order sliding-mode controller (I2OSMC) will be proposed and developed to improve the control performance and to achieve the requirements of stability of steering control of six-phase PMSM drive system in the third year of this project. Compared with traditional first-order sliding mode control, the uncertainties of the EPS system is estimated using the WFNN-AMF with online learning and fast convergence capabilities in order to smooth the chattering effect owing to the sliding function. A robust controller is also adopted to compensate the reconstruction error of WFNN-AMF. As a result, the newly-proposed I2OSMC will be able to have a satisfactorily tracking performance with guaranteed stability.A TMS320F28335 DSP made by Texas Instruments (TI) is the core of the proposed control system. The proposed control algorithms are realized in the DSP using the “C” language. Moreover, a DSP extension board reads the rotor position, motor speed and six-phase currents from the sensors using encoder interface circuit and analog to digital converters (ADCs). Furthermore, the resulted pulse width modulation (PWM) signals are sent to control the IGBT-based inverter and actuate the six-phase PMSM according to the field-oriented control. Therefore, the position control of the DSP-based six-phase PMSM drive system can be achieved. In addition, the EPS system using the DSP-based six-phase PMSM drive system with guaranteed stability and accurate position control can be used as the prototype for commercial realization.
Effective start/end date1/08/1631/07/17

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 11 - Sustainable Cities and Communities
  • SDG 12 - Responsible Consumption and Production
  • SDG 17 - Partnerships for the Goals


  • Six-phase permanent synchronous motor
  • electric power steering (EPS) system
  • digital signal processor (DSP)
  • wavelet fuzzy neural network with asymmetric membership function (WFNN-AMF)
  • improved


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