Ling Liu

In this article, an adaptive finite time disturbance observer (FTDO)-based position sensorless drive method is proposed to improve the position and speed observation performance of surface-mounted permanent magnet synchronous motor (SPMSM). First, to observe system disturbance in a finite time, an adaptive FTDO is proposed by designing an adaptive law and combining it with a fixed time sliding surface. Due to the designed adaptive law can stably track the bound of the first-order derivative of disturbance, the adaptive FTDO does not need to know the bounds of disturbance and its first-order derivative, which will also suppress the chattering of observed disturbance. Subsequently, to compensate for the disturbance in the observed flux initially obtained by the flux observer and simultaneously observe the speed, an adaptive speed observer is designed by adopting the proposed adaptive FTDO. Besides, the finite time convergence and stability of the adaptive FTDO have been demonstrated according to the Lyapunov theory. The coefficient setting guides for adaptive FTDO are also provided. The effectiveness of the proposed adaptive FTDO-based method is verified by contrastive experiments on an SPMSM.

To heighten the observation accuracy and dynamic performance of the permanent magnet synchronous motor sensorless drive system without increasing high frequency noise sensitivity, this article presents a sensorless control scheme. The scheme involves K-infy adaptive super-twisting sliding mode observer (ASTSMO) connected with cascade surface extended state observer (CSESO) in series. By incorporating the K-infy function into the full order STSMO, K-infy ASTSMO suppresses the chattering and overestimation common in traditional SMOs, allowing the observer to maintain reliable performance in a wide speed range. Subsequently, CSESO is connected in series after K-infy ASTSMO to serve as mechanical states observer. By designing the cascaded error surface, CSESO simplifies the tuning process and shows the ability to suppress sensitivity to high-frequency noise, while enhancing the dynamic performance. Stability analysis of the proposed algorithm is provided along with parameter tuning guidelines. Through a series of experiments, the proposed scheme is proved to be capable of delivering improved observation accuracy and dynamic performance over a wide operating range.

This article presents a novel speed-flux transformation model, derived from the traditional active flux model of permanent magnet synchronous motor, which features a known regression term of speed. This advancement achieves nonlinear parameterization of motor speed, enabling the construction of a speed adaptive observer. Then, a high order nonlinear adaptive (HONA) observer is developed by adopting the proposed model, which employs a nonlinear parameter updating law and high order sliding mode correction terms for error estimators, thereby enhancing the system's dynamic response. Due to the known regression term nature of the proposed model, the adaptive observer ensures stability at near-zero speeds, leading to superior performance in low-speed and reversal scenarios. After rigorously proving the observer's stability, a detailed tuning guide for parameters is provided. The effectiveness of the HONA observer is validated through both numerical and experimental works.

To achieve high performance position sensorless drive of surface-mounted permanent magnet synchronous motors (SPMSMs) in a wide speed range, a dual-layer adaptive sliding mode algorithm for hybrid active flux model is proposed in this article. The variation of motor parameters will affect the estimation accuracy of the flux observer, which in turn will affect the observation of rotor position information. To eliminate the influence of disturbance, including parameter variation, on the flux observer, a dual-layer adaptive sliding mode disturbance estimation (ASMDE) algorithm is proposed to establish an improved flux observer. By the aid of the fixed-time sliding mode control, the proposed dual-layer ASMDE algorithm can estimate the disturbance within a finite time while the ranges of the disturbance and its derivatives are unknown. Furthermore, to improve dynamic performance and robustness to load disturbance, the dual-layer ASMDE algorithm is also adopted to design a speed observer that can estimate disturbance in real time. Afterwards, the estimated disturbance is feedforward compensated to the current loop. The finite time convergence and stability of the dual-layer ASMDE algorithm have been proved according to the Lyapunov function. The comparative experiments of this method have been conducted on an SPMSM. The experimental results show that the proposed method can operate stably within the range of 1.5%-100% rated speed. Besides, compared with existing methods, the position estimation error has been reduced by at least 0.27 rad when the speed is reversed, and by at least 0.15 rad when stator resistance mismatch occurs. After disturbance compensation, the acceleration time from 1000 rpm to 2000 rpm with about 50% rated load is reduced by about 0.95s.

This article addresses the nonlinear-parameterized problem of known regressor full-order interior permanent magnet synchronous motor (IPMSM) models, and proposes asymptotically stable observers for the joint estimation of stator resistance, rotor position, and speed. In recent years, several known regressor variants of nonlinear-parameterized full-order IPMSM models have been identified, which eliminate most of the low-speed instability problems. The resulting nonlinear high-gain observers, however, cannot adjust the convergence speed of parameters separately, and their parameter identifiability varies greatly with working conditions. It is, therefore, more appealing to consider a linear adaptive observer to realize stable joint estimation. In this article, by designing model reference adaptive systems and introducing the filtered regressors, the decoupling of nonlinear error dynamics is achieved. The linear feedback design makes it possible to guarantee globally asymptotic stability by applying the Kalman–Yakubovich lemma, while avoiding the disadvantages of nonlinear high-gain observers. Besides, the stability analysis results indicate that the influence of high-order errors can be eliminated by carefully tuning the observer coefficients. Several elaborate working conditions are considered to perform effective comparative experimental verification, including very-low speed experiments, wide-speed operations, and motor reversal tests.

This article presents a fixed-time high-order dynamic observation strategy which possesses the fixed time convergence feature. It mainly includes two aspects: 1) introducing dynamic surface into high-order sliding mode and 2) semiglobal fixed time uniformly ultimately bounded stability in backstepping dynamic surface design. Besides, this strategy is adopted to design a novel cascade fixed-time sliding mode observer-extended state observer for permanent magnet synchronous motor states observation. Specifically, the observer is capable of achieving fixed-time convergence. This implies that the upper bound of the convergence time depends solely on the designed parameters, enabling the system to reach convergence in a limited time with fixed upper bound under any initial conditions. Furthermore, the upper bound of convergence time is calculated and the exact stability is mathematically proved. A tuning guideline for all parameters is also elaborated. Fixed time convergence feature is the major concern in experimental and numerical works arranging. Through the experiment and numerical results, the validate and fixed time convergence feature of the proposed observer are verified.

In this article, an adaptive second-order disturbance observer (SODO)-based position sensorless drive strategy for permanent magnet synchronous motor (PMSM) considering disturbance compensation is proposed. To achieve finite time observation of disturbance in the case of the boundaries of the system disturbance and its derivative are unknown, an adaptive SODO is put forward first. Under the premise that the upper and lower bounds of the adaptive coefficient are not required, the adaptive mechanism of the SODO cannot only guarantee the occurrence of sliding mode, but also make the adaptive coefficient small enough to suppress chattering. Next, to estimate the extended back electromotive force (EMF), a stator current observer is designed by adopting the proposed adaptive SODO. Afterward, to estimate rotor position information through the extended back EMF without adopting phase-locked loop, a speed observer that can omit the low-pass filter used for the estimated extended back EMF filtering and diminish the position estimation error is designed by employing the adaptive SODO. In addition, the disturbance of the speed loop is also observed and compensated. The stability of the adaptive SODO is analyzed by the Lyapunov function. The effectiveness of the proposed position sensorless drive strategy has been verified through comparative experiments on a surface-mounted PMSM.

This article addresses the adaptive observer design problem for sensorless interior permanent magnetic synchronous motor (PMSM) drives with unknown stator resistance. When following the adaptive observer designs in the literature, there are difficulties encountered during tuning the observers' coefficients. Two aspects contribute to the complexity of tuning: the use of locally stable designs and the use of reduced-order models. Unfortunately, owing to the unknown regressors in the conventional interior PMSM (IPMSM) model (including the extended electromotive force model and active flux model), no full-order adaptive observer for sensorless IPMSM drives can be proved to be globally stable. To get rid of the unknown parameter regressors, a parameter-dependent auxiliary state is designed. The IPMSM model is transformed into a new coordinate, in which its dynamics show the characteristic of the Brunovsky form and the known regressors. With the proposed IPMSM model, a series of globally stable adaptive observer theories can be applied directly to the construction of full-order observers. Rigorous theoretical and experimental verifications reveal that a nonlinear parameterized high-gain observer provides superior dynamic performance and robustness.

A sensorless control strategy of permanent magnet synchronous motor (PMSM) with disturbance rejection based on an adaptive sliding mode control law (ASMCL) is proposed in this article. Firstly, an ASMCL is proposed to restrain the chattering of system state while maintaining fast convergence. The finite-time convergence of the ASMCL is proved and the convergence time is independent of the initial state of the system. Next, an improved sliding mode observer (SMO) based on the ASMCL is designed to restrain the chattering of the estimated back ElectroMotive Force (EMF). Afterwards, to improve the ability of suppressing the load disturbance, a disturbance observer on the ground of integral sliding mode control (ISMC) method is presented to gain the observed disturbance current for the feedforward compensation. Further, through the introduction of the ASMCL, an adaptive disturbance observer is proposed to suppress the chattering phenomenon caused by the symbolic function in the constant coefficient disturbance observer. The stabilities of the SMO and the disturbance observer are analyzed according to the Lyapunov stability theory. Comparative experimental results are given to verify the effectiveness of the proposed sensorless control strategy on a surface-mounted PMSM.

This article proposes a known regressors variant of the extended electromotive force (EMF) model, enabling rigorous theoretical stability analysis about the joint estimation of position, speed, and stator resistance in the full-order observer design. According to the literature, adaptive observer designs for nonlinear systems often require the regressors to be known as well as the systems being in Brunovsky observer form. Unfortunately, none of the existing interior permanent magnet synchronous motor (IPMSM) models (i.e., the extended EMF model and the active flux model) are capable of meeting these requirements. By defining a new state variable, the extended EMF model of IPMSM can be transformed into its known regressors variant, thereby, ensuring global stability of the speed and stator resistance adaptive observer. In the new coordinate, the inclusion of stator resistance estimation leads to the overparameterization problem, thus an adaptive high-gain observer is proposed to allow certain nonlinear terms to appear in the regressors. Analyses of stability and parametric sensitivity are also presented, resulting in a robust tuning guideline for the sensorless control system. Simulations and experiments have been conducted to verify the effectiveness of the proposed adaptive observer in a sensorless IPMSM drive, and improvements have been observed in wide-speed operations and disturbance rejections.