Articles
IEEE Transactions on Industrial Electronics (02780046)71(12)pp. 15372-15382
This article presents a comprehensive approach to addressing the challenges of unbalanced rotors in permanent magnet (PM) synchronous machines by proposing a load torque (LT) observer for unbalance detection and a current injection technique for minimizing torque oscillations resulting from the unbalanced rotor. The primary objective is to enhance the operational efficiency and performance of electric motors by identifying the effects of the unbalanced rotor on the motor torque. The proposed LT observer utilizes real-time speed measurement to estimate the total LT. To significantly reduce the torque oscillations from the unbalanced rotor, optimum current components are injected with meticulously calculated amplitude and phase. The proposed method operates in synchronization with the rotor position, and the injected currents are extracted via an optimization problem from an adaptive model that is continuously updated through a parameter's identification method. The effectiveness of the proposed approach is demonstrated through experimental evaluations on a representative experimental setup. The results reveal that the LT observer accurately detects rotor unbalance and the current injection technique successfully minimizes motor torque oscillations, resulting in smoother motor operation, reduced noise, and improved overall efficiency. © 1982-2012 IEEE.
International Journal of Systems Science (00207721)55(13)pp. 2741-2758
Designing a full-state observer for nonlinear systems has always been accompanied by challenges and restrictive constraints. Mainly, applying a state observer in nonlinear systems with non-minimum phase characteristics is more challenging when the limiting constraints are not satisfied due to diverging internal dynamics. In this paper, a robust sliding-mode observer approach has been successfully employed to estimate the states of nonlinear systems with unbounded and diverging dynamics. The design principles of this observer are based on applying a classifying algorithm in single-input single-output and multiple-input multiple-output nonlinear systems. It is noteworthy that this observer is highly robust against disturbance, uncertainty and measurement noise, and its conditions are less conservative compared to previous nonlinear sliding-mode observers. One novel feature of the proposed observer is that while the system's state gets unbounded and diverged in fault-occurring scenarios or critical circumstances, this observer retains accuracy. The efficiency of the proposed observer is verified in the simulation results for two nonlinear industrial systems, including a hydro-turbine power generation plant and a continuous stirred tank reactor. © 2024 Informa UK Limited, trading as Taylor & Francis Group.
Journal of the Franklin Institute (00160032)360(14)pp. 10728-10744
This paper deals with state estimation for a class of Lipschitz nonlinear systems under a time-varying disconnected communication network. A distributed observer consists of some local observers that are connected to each other through a communication network. We consider a situation where a communication network does not remain connected all the time, and the network may be caused by intermittent communication link failure. Moreover, each local observer has access to a local measurement, which may be insufficient to ensure the system's observability, but the collection of all measurements in the network ensures observability. In this condition, the purpose is to design a distributed observer where the estimated state vectors of all local observers converge to the state vector of the system asymptotically, while local observers exchange estimated state vectors through a communication network and use their local measurements. According to theoretical analysis, a nonlinear and a robust nonlinear distributed observer exist when in addition to the union of all communication topologies being strongly connected during a time interval, the component of each communication graph is also strongly connected during each subinterval. The existence conditions of the distributed observers are derived in terms of a set of linear matrix inequalities (LMIs). Finally, the effectiveness of the presented method is numerically verified using some simulation examples. © 2023 The Franklin Institute
Journal of Navigation (03734633)76(6)pp. 709-730
This paper proposes a switched model to improve the estimation of Euler angles and decrease the inertial navigation system (INS) error, when the centrifugal acceleration occurs. Depending on the situation, one of the subsystems of the proposed switched model is activated for the estimation procedure. During global positioning system (GPS) outages, an extended Kalman filter (EKF) operates in the prediction mode and corrects the INS information, based on the system error model. Compared with previous works, the main advantages of the proposed switched-based adaptive EKF (SAEKF) method are (i) elimination of INS error, during the centrifugal acceleration, and (ii) high accuracy in estimating the attitude and positioning, particularly during GPS outages. To validate the efficiency of the proposed method in various trajectories, an experimental flight test is performed and discussed, involving a microelectromechanical (MEMS)-based INS. The comparative study shows that the proposed method considerably improves the accuracy in various scenarios. © The Author(s), 2024. Published by Cambridge University Press on behalf of The Royal Institute of Navigation.
