This paper presents a new technique for nonlinear continuous-time observer design based on the differential State-dependent Riccati equation (SDRE) filter, with guaranteed exponential stability. Although impressive results have rapidly emerged from the use of SDRE designs for observers and filters, the underlying theory is yet scant and there remain many unanswered questions such as stability and convergence. In this paper, Lyapunov stability analysis is used to obtain the required conditions for exponential stability of the estimation error dynamics. Furthermore, through a simulation study of a second order nonlinear model, which satisfies the stability conditions, the promising performance of the proposed observer is demonstrated. Finally, in order to examine the effectiveness of the proposed method, it is applied to highly nonlinear flux and angular velocity estimation problem for induction machines. The simulation results verify how effectively the modification proposed in this paper can increase the region of attraction and the observer error decay rate.

Proportional Navigation is commonly used in the terminal phase of homing missiles. To implement this guidance law, it is necessary to measure or calculate Line of Sight (LOS) rate. It is usually necessary to use gimballed seekers to measure the LOS rate. However, if the system is equipped with a strapdown seeker, the LOS rate must be calculated from derivation or estimation methods. Because the signal measured by seekers usually contains noise, so deriving this signal requires a low pass filter that will cause the behavior changes in the measured variable. The issue in this paper is the design of a discrete time sliding mode extended State observer to estimate the LOS rate and evaluate it in the guidance loop. This is done by performing computer simulations. Implementing continuous time observers in processors has challenges such as sampling time selection and it is better to design the observer in discrete time form from the beginning so that its implementation issues can be considered from the design level and in computer simulations.

Under unbalanced grid condition, in a doubly-fed induction generator (DFIG), voltage, current, and flux of the stator become asymmetric. Therefore, active-reactive power and torque will be oscillating. In DFIG controlling rotor side converter (RSC) aims to eliminate power and torque oscillations. However, simultaneous elimination of the power and torque oscillations is not possible. Also, grid side converter (GSC) aims to regulate DC-Link voltage. In this paper, in order to regulate DC-Link voltage, an extended State observer (ESO) based on a generalized proportional-integral (GPI) controller, is employed. In this controlling method, DC-Link voltage is controlled without measuring the GSC current, and due to using the GPI controller, the improved dynamic response is resistant against voltage changes, and the settling time is reduced. A versatile rotor position computation algorithm (RPCA) is utilized to measure the rotor speed. This algorithm is simple, yet it is accurate and is resistant to changes in the resistance of the rotor and stator. The simulations are implemented by MATLAB software in the synchronous positive and negative sequence reference (d-q).

This paper proposes a novel hybrid control framework by combing enhanced extended State observer with trajectory linearization control for air vehicle acceleration tracking problems. First, based on the tracking error dynamics derived by Taylor expansion for the original nonlinear system along the desired trajectory, a feedback linearization-based control law is designed to stabilize a linear time-varying system. To reduce the controller performance sensitivity to uncertainties, with partial model information, an enhanced extended State observer is constructed to estimate the tracking error vector, as well as the uncertainties in an integrated manner. The closed-loop stability of the system under the proposed compound scheme is established. Both numerical simulation studies and an application example of air vehicle acceleration autopilot design demonstrate the feasibility and efficacy of the proposed method.

In this paper, an adaptive fuzzy extended State observer is proposed to estimate the States and external disturbances simultaneously for Single-Input-Single-Output nonlinear affine systems. The observer gains are time-varying and adjusted using an adaptive law. The Takagi-Sugeno fuzzy system is used for modeling that, unlike Mamdani methods, provides a more precise and comprehensive analysis. The proposed adaptive fuzzy observer is designed to relax the limitations of the extended State observers and improve system performance as compared to the classical methods in presence of time-varying disturbances. Moreover, the stability of the proposed method and the convergence of the estimation error are analyzed using the Lyapunov stability Theory. The performance of the proposed method is shown in simulations of control of the inverted pendulum. The simulation results, as compared to the non-adaptive fuzzy observer, show better performance in terms of transient and steady-State responses, control input amplitude, and robustness in presence of measurement noise and external disturbances.

In this paper, a delay compensation for a class of unknown systems with simultaneous State and input delays through the predictive adaptive observer is investigated. Despite the unknown term, an adaptive State observer is designed to have an exact prediction. The upper bounds of uncertainty with time varying delay are considered unknown, which do not require to be known for the design. Then, the second observer is introduced for simultaneous delay compensation in State and input that input delay can be optionally longer than the delay in the State. Besides, in this approach, the numerical solution is not implied for delay compensation of input in uncertainty system. Based on Lyapunov theory, it has been proved, the input delay in systems with the unknown term can compensate by means of designed observers, while the estimation error is small and bounded. For more details, we also show a numerical example that indicates the proposed approaches’ impact.

Permanent magnet synchronous motors due to its high efficiency and power density, reliable performance and simple construction, industrially used. One of the problems with these Motor need accurate information to control its speed and position. Recently, because of the difficulties of the speed sensors, speed estimation is used instead of measuring it. In this paper, the State dependent model reference adaptive controller based on pseudo linearization is used to control the permanent magnet synchronous motor that its parameters are determined based on Lyapunov theory. This controller show good results by production control law, despite changing circumstances and maintain system stability despite external disturbances. Also due to uncertainty in the estimation of the position and speed of motor parameters, high impact, online identification of these parameters is necessary. In this paper, adaptive augmented observer is used to estimate speed and identify motor parameters online. The main advantage of this estimator is that speed and load torque estimation and identification of parameters are simultaneously thus volume and time calculations are reduced. The simulation results show convenient tracking of desired speed with the load torque, changing the motor parameters and the speed reference.

Reliability and robustness are two main goals in developing control systems for wind turbine (WT) due to the existence of different sources, such as unknown malfunctions or faults. Their ignorance can significantly jeopardize the system performance and even stability. This paper presents a new active fault tolerant control (FTC) for WT system considering the fault of pitch system. The nonlinear model of WT is constructed in the form of strict-feedback in order to design an appropriate FTC-based backstepping control law. The mechanism of fault detection is based on a modified nonlinear fuzzy State observer, where the estimation of unknown terms is realized via fuzzy approximators, incorporated in the fuzzy observer. Accordingly, the rotor speed of the system can follow the desired reference in the presence of an actuator fault. The robust behavior, fast response, and acceptable tracking performance together with the model-free structure are the important properties of the proposed FTC-based controller. The stability of the overall closed-loop system, including the controller and the observer, is derived by the Lyapunov method. Simulation results highlight the superior performance of the proposed control method.