The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform
M. S. Zaky - One of the best experts on this subject based on the ideXlab platform.
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Sensorless Induction Motor Drives Using Adaptive Flux Observer at Low Frequencies
Engineering Technology & Applied Science Research, 2018Co-Authors: M. S. Zaky, H. A. Maksoud, Haitham Z. AzaziAbstract:Operation at low frequencies of sensorless drives using machine model-based estimation methods is a challenging issue. This paper proposes an adaptive flux Observer (AFO) method of speed estimation for sensorless induction motor drives. The Observer Feedback gains are designed to guarantee accurate speed estimation, especially at low frequencies in the regenerating mode operation. A complete sensorless IM drive with the proposed AFO is executed in the laboratory. Extensive experimental results under different operating conditions are provided to prove the effectiveness of the proposed AFO, particularly under low stator frequencies in both motoring and regenerating modes of operation.
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Sensorless Torque/Speed Control of Induction Motor Drives at Zero and Low Frequencies With Stator and Rotor Resistance Estimations
IEEE Journal of Emerging and Selected Topics in Power Electronics, 2016Co-Authors: M. S. Zaky, Mohamed K. MetwalyAbstract:Stability, robustness, and estimation accuracy of the adaptive flux Observer (AFO) for sensorless induction motor (IM) drives are the most critical issues at zero and very low frequencies. In this paper, the design of speed, stator resistance, and rotor resistance estimators, to improve the robustness of AFO to parameters variation, is proposed. These estimators are arranged to have a cascade multi-input multi-output structure, and simplified to a single-input single-output structure for stability analysis and gain selections. To design both the Observer Feedback gains and adaptive proportional-integral gains, the stability conditions of the estimators are derived to guarantee a stable AFO in all the four quadrants of operation. The sensitivity analysis against stator and rotor resistance variations is also provided. The detailed analytical, simulation, and experimental results are presented to validate the proposed AFO of sensorless IM drives in torque- and speed-controlled modes of operation, particularly at zero and very low frequencies.
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stability analysis of speed and stator resistance estimators for sensorless induction motor drives
IEEE Transactions on Industrial Electronics, 2012Co-Authors: M. S. ZakyAbstract:This paper presents an analysis by which the stability of a multiple-input-multiple-output system of simultaneous speed and stator resistance estimators for sensorless induction motor drives can be successfully predicted. The instability problem of an adaptive flux Observer (AFO) is deeply investigated. In order to achieve stability over a wide range of operation, a design of the Observer Feedback gain is proposed. Furthermore, closed-loop control systems of the independent use of the two estimators are developed. Therefore, all gains of the adaptive proportional-integral controllers are selected and generalized to provide good tracking performance as well as fast dynamic response. The performance of the AFO using the proposed gains, with a sensorless indirect-field-oriented-controlled induction motor drive, is verified by simulation and experimental results. The results show a good improvement in both convergence and stability, particularly in the regenerative mode at low speeds, which confirm the validity of the proposed analysis.
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A stable adaptive flux Observer for a very low speed-sensorless induction motor drives insensitive to stator resistance variations
Ain Shams Engineering Journal, 2011Co-Authors: M. S. ZakyAbstract:Abstract In recent years, numerous attempts have been made to improve the performance of sensorless induction motor drives. However, parameter variations, low-speed and zero-speed operations are the most critical aspects affecting the accuracy and stability of sensorless drives. This paper presents a stable adaptive flux Observer (AFO) for sensorless induction motor drives insensitive to stator resistance variations. Design of the Observer Feedback gain of AFO is proposed to guarantee the stability, especially at low speeds. The adaptive law parameters are designed to give quick transient response and good tracking performance. The sensitivity of AFO to stator resistance mismatch is studied. A stator resistance adaptation scheme for accurate speed estimation at low speeds is derived. The relation between the identification error of rotor speed and adaptive gains is clarified based on Lyapunov theory. Experimental setup using DSP-DS1102 control board is implemented. Simulation and experimental results confirm the efficacy of the proposed approach.
C-c Ku - One of the best experts on this subject based on the ideXlab platform.
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A New H ∞ Robust Control for Discrete Ship Autopilot Stochastic System via Observer Feedback
2018 International Automatic Control Conference (CACS), 2018Co-Authors: C-c Ku, Guan-wei Chen, Hung-pan ChungAbstract:This paper is to study an Observer-based control problem of uncertain ship autopilot stochastic system. Different from the existing efforts, stochastic behaviors described as multiplicative noise is considered in LPV system to discuss practical application of ship autopilot system. Furthermore, an individual H ∞ control scheme is developed to attenuate worst effects of external disturbance on state and estimation error of the system. For designed criterion, a novel Lyapunov function with full elements and extended projection lemma are applied to derive Linear Matrix Inequality (LMI) which can directly apply convex optimization algorithm. Through solving the LMIs, the Observer-based gain scheduled controller can be designed at a step such that the H ∞ performance and asymptotical stability of the considered system driven by the designed controller can be guaranteed. Finally, simulation results are provided to illustrate the applicability and usefulness of the proposed method.
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A New H∞ Robust Control for Discrete Ship Autopilot Stochastic System via Observer Feedback
2018 International Automatic Control Conference (CACS), 2018Co-Authors: C-c Ku, Guan-wei Chen, Hung-pan ChungAbstract:This paper is to study an Observer-based control problem of uncertain ship autopilot stochastic system. Different from the existing efforts, stochastic behaviors described as multiplicative noise is considered in LPV system to discuss practical application of ship autopilot system. Furthermore, an individual H∞ control scheme is developed to attenuate worst effects of external disturbance on state and estimation error of the system. For designed criterion, a novel Lyapunov function with full elements and extended projection lemma are applied to derive Linear Matrix Inequality (LMI) which can directly apply convex optimization algorithm. Through solving the LMIs, the Observer-based gain scheduled controller can be designed at a step such that the H∞ performance and asymptotical stability of the considered system driven by the designed controller can be guaranteed. Finally, simulation results are provided to illustrate the applicability and usefulness of the proposed method.
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Passive fuzzy controller design via Observer Feedback for stochastic Takagi-Sugeno fuzzy models with multiplicative noises
International Journal of Control Automation and Systems, 2011Co-Authors: W-j Chang, C-c KuAbstract:This paper investigates the fuzzy control problem of a class of nonlinear continuous-time stochastic systems with achieving the passivity performance. A model-based Observer Feedback fuzzy control utilizing the concept of so-called parallel distributed compensation (PDC) is employed to stabilize the class of nonlinear stochastic systems that are represented by the Takagi-Sugeno (T-S) fuzzy models. Based on the Lyapunov criteria, the Linear Matrix Inequality (LMI) technique is used to synthesize the Observer Feedback fuzzy controller design such that the closed-loop system satisfies stability and passivity constraints, simultaneously. Finally, a numerical example is given to demonstrate the applicability and effectiveness of the proposed design method.
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H(∞) constrained fuzzy control via state Observer Feedback for discrete-time Takagi-Sugeno fuzzy systems with multiplicative noises.
Isa Transactions, 2010Co-Authors: W-j Chang, Wen-yuan Wu, C-c KuAbstract:Abstract The purpose of this paper is to study the H ∞ constrained fuzzy controller design problem for discrete-time Takagi–Sugeno (T–S) fuzzy systems with multiplicative noises by using the state Observer Feedback technique. The proposed fuzzy controller design approach is developed based on the Parallel Distributed Compensation (PDC) technique. Through the Lyapunov stability criterion, the stability analysis is completed to develop stability conditions for the closed-loop systems. Besides, the H ∞ performance constraints is also considered in the stability condition derivations for the worst case effect of disturbance on system states. Solving these stability conditions via the two-step Linear Matrix Inequality (LMI) algorithm, the Observer-based fuzzy controller is obtained to achieve the stability and H ∞ performance constraints, simultaneously. Finally, a numerical example is provided to verify the applicability and effectiveness of the proposed fuzzy control approach.
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Observer-Feedback fuzzy control with passivity property for discrete-time affine Takagi-Sugeno fuzzy models
Proceedings of the Institution of Mechanical Engineers Part I: Journal of Systems and Control Engineering, 2010Co-Authors: W-j Chang, C-c Ku, F-c KuAbstract:AbstractBy considering discrete-time affine Takagi-Sugeno fuzzy models, this paper presents an Observer-Feedback fuzzy control approach for achieving the passivity property of closed-loop systems. The passivity property of the system is used to deal with all external disturbances. The proposed Observer-Feedback fuzzy controller is developed based on the parallel distribution compensation technique. Also, an iterative linear matrix inequality algorithm is used to obtain a feasible solution for the proposed Observer-Feedback fuzzy control problem. Finally, two numerical simulations of discrete-time nonl-inear systems are presented that highlight the application of the proposed Observer-Feedback fuzzy controller design approach.
Wu-sheng Lu - One of the best experts on this subject based on the ideXlab platform.
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Roundoff noise minimization in closed-loop systems using optimal error Feedback and realization
2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), 2015Co-Authors: Takao Hinamoto, Wu-sheng LuAbstract:We investigate the problem of optimizing error-Feedback and realization to minimize the roundoff noise subject to l2-scaling constraints in a system in which full-order state Observer Feedback is used in place of system state Feedback. In this paper, the optimal error-Feedback matrix is determined in closed-form in advance. As a result, joint optimization of error-Feedback and realization is no longer required. An iterative optimization technique for obtaining the optimal coordinate transformation matrix that minimizes the roundoff noise subject to l2-scaling constraints is explored by emplying a quasi-Newton algorithm. We also describe a separate optimization technique for comparison purposes. The results of numerical experiments demonstrate the validity and effectiveness of the proposed technique.
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Optimal error Feedback and realization for roundoff noise minimization in linear discrete-time systems with full-order state Observer Feedback
2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015Co-Authors: Takao Hinamoto, Wu-sheng LuAbstract:The optimization problem of error-Feedback and realization to minimize the roundoff noise in a closed-loop system with full-order state Observer Feedback subject to l2-scaling constraints is investigated. It is shown that joint optimization of error-Feedback and realization is not needed when utilizing a general-matrix error-Feedback loop because the optimal error-Feedback matrix, in closed-form, can be determined in advance. An analytic technique is developed for obtaining the optimal realization that minimizes the roundoff noise subject to l2-scaling constraints. A numerical example is presented to demonstrate the validity and effectiveness of the proposed technique.
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ISCAS - Optimal error Feedback and realization for roundoff noise minimization in linear discrete-time systems with full-order state Observer Feedback
2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015Co-Authors: Takao Hinamoto, Wu-sheng LuAbstract:The optimization problem of error-Feedback and realization to minimize the roundoff noise in a closed-loop system with full-order state Observer Feedback subject to l 2 -scaling constraints is investigated. It is shown that joint optimization of error-Feedback and realization is not needed when utilizing a general-matrix error-Feedback loop because the optimal error-Feedback matrix, in closed-form, can be determined in advance. An analytic technique is developed for obtaining the optimal realization that minimizes the roundoff noise subject to l 2 -scaling constraints. A numerical example is presented to demonstrate the validity and effectiveness of the proposed technique.
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Roundoff Noise Minimization in State-Space Discrete-Time Systems Using Joint Optimization of High-Order Error Feedback and Realization
IEEE Transactions on Circuits and Systems I: Regular Papers, 2014Co-Authors: Takao Hinamoto, Wu-sheng LuAbstract:This paper deals with the joint optimization problem of high-order error-Feedback and realization for minimizing roundoff noise at the output of a closed-loop system with a full-order Observer Feedback system subject to l2-scaling constraints. It is shown that the problem can be converted into an unconstrained optimization problem by using linear-algebraic techniques. The unconstrained optimization problem at hand is then solved iteratively by employing an efficient quasi-Newton algorithm with closed-form formulas for key gradient evaluation. A case study is presented to demonstrate the validity and effectiveness of the proposed technique.
Steffen Leonhardt - One of the best experts on this subject based on the ideXlab platform.
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Observer-Based Human Knee Stiffness Estimation
IEEE Transactions on Biomedical Engineering, 2017Co-Authors: Berno J.e. Misgeld, Markus Lüken, Robert Riener, Steffen LeonhardtAbstract:Objective: We consider the problem of stiffness estimation for the human knee joint during motion in the sagittal plane. Methods: The new stiffness estimator uses a nonlinear reduced-order biomechanical model and a body sensor network (BSN). The developed model is based on a two-dimensional knee kinematics approach to calculate the angle-dependent lever arms and the torques of the muscle-tendon-complex. To minimize errors in the knee stiffness estimation procedure that result from model uncertainties, a nonlinear Observer is developed. The Observer uses the electromyogram (EMG) of involved muscles as input signals and the segmental orientation as the output signal to correct the Observer-internal states. Because of dominating model nonlinearities and nonsmoothness of the corresponding nonlinear functions, an unscented Kalman filter is designed to compute and update the Observer Feedback (Kalman) gain matrix. Results: The Observer-based stiffness estimation algorithm is subsequently evaluated in simulations and in a test bench, specifically designed to provide robotic movement support for the human knee joint. Conclusion: In silico and experimental validation underline the good performance of the knee stiffness estimation even in the cases of a knee stiffening due to antagonistic coactivation. Significance: We have shown the principle function of an Observer-based approach to knee stiffness estimation that employs EMG signals and segmental orientation provided by our own IPANEMA BSN. The presented approach makes realtime, model-based estimation of knee stiffness with minimal instrumentation possible.
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Glucose-insulin model of glucose metabolism in acute diabetic swine based on Luenberger Observer
2012 American Control Conference (ACC), 2012Co-Authors: Katrin Lunze, Marian Walter, Steffen LeonhardtAbstract:Clinical studies have to be prepared meticulously to reduce the risk for each subject when testing new therapy devices. Here, the establisment of adequate animal trials could reduce the safety risks and accelerate the certification of technical developments for clinical studies. In particular, for the realisation of an artificial pancreas for type 1 diabetes patients, animal trials with Goettingen minipigs seem to be useful. To understand the glucose-insulin system in that breed and to design an adequate control algorithm for a future closed-loop therapy system, two different linear model approaches for the glucose metabolism are described. Therefore, two LUENBERGER Observer were identified for a simple PT2 and a more complex blood glucose trajectory approximation during oral glucose tolerance test and subcutaneously injected insulin dose. By analysing the Observer Feedback, it could be shown, that both approaches seem to be reasonable. Nevertheless, the models have to be improved in future by further glucose-insulin interactions and measurement data.
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ACC - Glucose-insulin model of glucose metabolism in acute diabetic swine based on Luenberger Observer
2012 American Control Conference (ACC), 2012Co-Authors: Katrin Lunze, Marian Walter, Steffen LeonhardtAbstract:Clinical studies have to be prepared meticulously to reduce the risk for each subject when testing new therapy devices. Here, the establisment of adequate animal trials could reduce the safety risks and accelerate the certification of technical developments for clinical studies. In particular, for the realisation of an artificial pancreas for type 1 diabetes patients, animal trials with Goettingen minipigs seem to be useful. To understand the glucose-insulin system in that breed and to design an adequate control algorithm for a future closed-loop therapy system, two different linear model approaches for the glucose metabolism are described. Therefore, two LUENBERGER Observer were identified for a simple PT 2 and a more complex blood glucose trajectory approximation during oral glucose tolerance test and subcutaneously injected insulin dose. By analysing the Observer Feedback, it could be shown, that both approaches seem to be reasonable. Nevertheless, the models have to be improved in future by further glucose-insulin interactions and measurement data.
Eugene Lavretsky - One of the best experts on this subject based on the ideXlab platform.
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ALCOSP - Adaptive Systems with Closed–loop Reference Models: Composite control and Observer Feedback
IFAC Proceedings Volumes, 2020Co-Authors: Travis E Gibson, Anuradha M Annaswamy, Eugene LavretskyAbstract:Abstract A class of Closed-loop Reference Models (CRM) was shown in Gibson et al. (2013) to have improved transient performance. In this paper, we show that the introduction of CRM in Combined direct and indirect Model Reference Adaptive Control (CMRAC) leads to significant improvement in their transient response as well. We also show that CRM allow stable Feedback of noise-free state estimates in CMRAC. Theoretical derivations are supported with numerical simulations.
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adaptive systems with closed loop reference models composite control and Observer Feedback
IFAC Proceedings Volumes, 2013Co-Authors: Travis E Gibson, Anuradha M Annaswamy, Eugene LavretskyAbstract:Abstract A class of Closed-loop Reference Models (CRM) was shown in Gibson et al. (2013) to have improved transient performance. In this paper, we show that the introduction of CRM in Combined direct and indirect Model Reference Adaptive Control (CMRAC) leads to significant improvement in their transient response as well. We also show that CRM allow stable Feedback of noise-free state estimates in CMRAC. Theoretical derivations are supported with numerical simulations.
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On Adaptive Control With Closed-Loop Reference Models: Transients, Oscillations, and Peaking
IEEE Access, 2013Co-Authors: Travis E Gibson, Anuradha M Annaswamy, Eugene LavretskyAbstract:One of the main features of adaptive systems is an oscillatory convergence that exacerbates with the speed of adaptation. Recently, it has been shown that closed-loop reference models (CRMs) can result in improved transient performance over their open-loop counterparts in model reference adaptive control. In this paper, we quantify both the transient performance in the classical adaptive systems and their improvement with CRMs. In addition to deriving bounds on L-2 norms of the derivatives of the adaptive parameters that are shown to be smaller, an optimal design of CRMs is proposed that minimizes an underlying peaking phenomenon. The analytical tools proposed are shown to be applicable for a range of adaptive control problems including direct control and composite control with Observer Feedback. The presence of CRMs in adaptive backstepping and adaptive robot control is also discussed. Simulation results are presented throughout this paper to support the theoretical derivations.
