• Journal of Electrical Engineering and Technology
• /
• v.12 no.1
• /
• pp.272-283
• /
• 2017

In this paper, an improved predictive functional control (PFC) scheme for permanent magnet synchronous motor (PMSM) control system is proposed, on account of the standard PFC method cannot provides a satisfying disturbance rejection performance in the case of strong disturbances. The PFC-based method is first introduced in the control design of speed loop, since the good tracking and robustness properties of the PFC heavily depend on the accuracy of the internal model of the plant. However, in orthodox design of prediction model based control method, disturbances are not considered in the prediction model as well as the control design. A minimum-order observer (MOO) is introduced to estimate the disturbances, which structure is simple and can be realized at a low computational load. This paper adopted the MOO to observe the load torque, and the observations are then fed back into PFC model to rebuild it when considering the influence of perturbation. Therefore, an improved PFC strategy with torque compensation, called the PFC+MOO method, is presented. The validity of the proposed method was tested via simulation and experiments. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.

• Journal of Power Electronics
• /
• v.15 no.6
• /
• pp.1547-1558
• /
• 2015

A predictive functional control (PFC) scheme for permanent magnet synchronous motor (PMSM) servo systems is proposed in this paper. The PFC-based method is first introduced in the control design of speed loop. Since the accuracy of the PFC model is influenced by external disturbances and speed detection quantization errors of the low distinguishability optical encoder in servo systems, it is noted that the standard PFC method does not achieve satisfactory results in the presence of strong disturbances. This paper adopted the Kalman filter to observe the load torque, the rotor position and the rotor angular velocity under the condition of a limited precision encoder. The observations are then fed back into PFC model to rebuild it when considering the influence of perturbation. Therefore, an improved PFC method, called the PFC+Kalman filter method, is presented, and a high performance PMSM servo system was achieved. The validity of the proposed controller was tested via experiments. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.

• Earthquakes and Structures
• /
• v.25 no.3
• /
• pp.187-198
• /
• 2023

Model Predictive Control (MPC) is an advanced control approach that uses the current states of the system model to predict its future behavior. In this article, according to the seismic dynamics of structural systems, the Predictive Functional Control (PFC) method is used to solve the control problem. Although conventional PFC is an efficient control method, its performance may be impaired due to problems such as uncertainty in the structure of state sensors and process equations, as well as actuator saturation. Therefore, it requires the utilization of appropriate estimation algorithms in order to accurately evaluate responses and implement actuator saturation. Accordingly, an extended PFC is presented based on the H-ifinity (H∞) filter (HPFC) while considering simultaneously the saturation actuator. Accordingly, an extended PFC is presented based on the H-ifinity (H∞) filter (HPFC) while considering the saturation actuator. Thus, the structural responses are formulated by two estimation models using the H∞ filter. First, the H∞ filter estimates responses using a performance bound (𝜃). Second, the H∞ filter is converted into a Kalman filter in a special case by considering the 𝜃 equal to zero. Therefore, the scheme based on the Kalman filter (KPFC) is considered a comparative model. The proposed method is evaluated through numerical studies on a building equipped with an Active Tuned Mass Damper (ATMD) under near and far-field earthquakes. Finally, HPFC is compared with classical (CPFC) and comparative (KPFC) schemes. The results show that HPFC has an acceptable efficiency in boosting the accuracy of CPFC and KPFC approaches under earthquakes, as well as maintaining a descending trend in structural responses.