This paper presents an adaptive nonlinear observer for sensorless passivity based control applied to permanent magnet synchronous motor. The passivity based control approach is applied to a complex and coupled nonlinear mathematical model of permanent magnet synchronous motor without any approximation or cancellation of nonlinearities. A nonlinear adaptive observer is proposed to estimate the mechanical speed and the unmeasured load torque (unknown disturbance) that has an effect on the control performance; therefore, those estimated states are then used to improve the performance of the passivity based control for permanent magnet synchronous motor. The performance of the proposed controller-observer have been tested using MATLAB/SIMULINK, where those Simulation results show a perfect tracking of the mechanical speed and load torque
The permanent magnet synchronous motor has been widely used for industrial applications due to its simplicity, robustness and low cost; however, the permanent magnet synchronous motor (PMSM) is described by a nonlinear coupled and complex mathematical model; which is a challenging task for control engineering. Many control techniques have been studied and applied to drive the permanent magnet synchronous machine, such as: Feedback linearization control, sliding mode control, adaptive control, backstepping control, passivity based control... The passivity based control term was introduced in (Ortega & Spong, 1988), which was inspired from three proposed control laws that are applied to a robot manipulator (Paden & Panja, 1988; Slotine & Li, 1991; Takegaki & Arimoto, 1981). The passivity based control (PBC) was applied to dynamical systems that could be modeled using Euler-Lagrange, such as permanent magnet synchronous motor (PMSM) in (Romeo, Antonio, Per, & Hebertt, 1998). Hence the passivity based control technique has been used to enhance the performance of the permanent magnet synchronous motor such as: passivity based voltage control (PBVC) (Achour, 2011), passivity based current control PBCC (Achour, Mendil, Bacha, & Munteanu, 2009), passivity based control with flux orientation (Belabbes, et al., 2009) and interconnection and damping assignment passivity (IDA-passivity) (Khanchoul, et al., 2014; Petrovic, Ortega, & Stankovic, 2001). Therefore, different strategies of the passivity based control combined with other control techniques have been applied to drive the PMSM such as: integral action control (Zhuang & Huang, 2017), sliding mode control (Yang et al., 2018), backstepping control (Belabbes & Larbaoui, 2015), adaptive control (Liu et al., 2014) and Fuzzy sliding mode (Shen & Ji, 2007).