This paper presents a new observer design methodology for a time varying actuator FAULT ESTIMATION. A new linear matrix inequality (LMI) design algorithm is developed to tackle the limitations (e.g. equality constraint and robustness problems) of the well known so called FAST adaptive FAULT ESTIMATION observer (FAFE). The FAFE is capable of estimating a wide range of time-varying actuator FAULT signals via augmenting the Luenberger-observer by a proportional integral FAULT estimator feedback. Within this framework, the main contribution of this paper is the proposal of new LMI formulation that incorporates the use of L2 norm minimization: (a) to obviate the FAFE equality constraint in order to relax the design algorithm, (b) to ensure robustness against external disturbances, (c) to provide additional degrees of freedom to solve the infeasible optimization problem via assigning different proportional and integral FAULT estimator gains. Finally, a VTOL aircraft simulation example is used to illustrate the effectiveness of the proposed FAFE.

In this paper, an active approach for designing FAULT Tolerant Controller (FTC) is proposed. This aprroach utilizes the idea of dynamical observer for simultaneous ESTIMATION of system states and FAULTs. The main advantage of the dynamical observer is looking at the simultaneous ESTIMATION of system states and FAULTs purely as a robust control problem. In this proposed approach, the controller has a fixed structure and there is no need to reconfiguration of the controller to accommodate or compensate the effect of the FAULTs occurred in the system which makes the proposed approach practical for real systems. The control law is a linear function of the system states and estimated FAULTs and is designed to keep the closed loop system asymptotically stable and the performance of the closed loop system in an acceptable level in the presence of FAULTs and disturbances. A constructive algorithm based on Linear Matrix Inequality (LMI) is presented for FTC design. The merit of the proposed control scheme has been verified by the simulation on the four-tank process subjected to the actuator FAULTs.

This paper presents a novel approach for FAULT type ESTIMATION in power systems. The FAULT type ESTIMATION is the first step to estimate instantaneous voltage, voltage sag magnitude and duration in a three-phase system at FAULT duration. The approach is based on time-domain state ESTIMATION where redundant measurements are available. The current based model allows a linear mapping between the measured variable and the states to be estimated. This paper shows a possible for FAULT instance detection, FAULT location identification and FAULT type ESTIMATION utilizing residual analysis and topology error processing. The idea is that the FAULT status does not change measurement matrix dimensions but changes some elements of the measurement matrix. The paper addresses how to rebuilt measurement matrix for each type of FAULTs. The proposed algorithm is shown that the method has high effectiveness and high performance for forecasting FAULT type and for estimating instantaneous bus voltage. The performance of the novel approach is tested on IEEE 14-bus test system and the results are shown.

In this paper a new method for determining the search area for motion ESTIMATION algorithm based on block matching is suggested. In the proposed method the search area is adaptively found for each block of a frame. This search area is similar to that of the full search (FS) algorithm but smaller for most blocks of a frame. Therefore, the proposed algorithm is analogous to FS in terms of regularity but has much less computational complexity. To find the search area, the temporal and spatial correlations among the motion vectors of blocks are used. Based on this, the matched block is chosen from a rectangular area that the prediction vectors set out. Simulation results indicate that the speed of the proposed algorithm is at least 7 times better than the FS algorithm.      

An algebraic method based on unknown input observer for FAULT ESTIMATION in linear time invariant system with unknown input is implementable if matching condition is satisfied. Matching condition limits practical application of these methods. In this article, a method is proposed for FAULT ESTIMATION which need not satisfy matching condition. Unlike classical methods, the provided method does not require auxiliary output for FAULT ESTIMATION. In the first step, the unknown input is divided in two parts: the matched and the unmatched unknown inputs. Assuming that there exist a dynamic model for the unmatched part, new augmented system is constructed. The augmented system is revealed as a new system with matched unknown input. Then, the effect of matched unknown input is perfectly removed from observer ESTIMATION using the traditional unknown input decoupling strategy. In the next step, the full order observer is designed for the augmented system. A FAST adaptive law is employed for the FAULT ESTIMATION. Lyapunov stability condition of state and FAULT ESTIMATION are derived by linear matrix inequality (LMI) criteria. The effectiveness of the proposed method is shown via numerical simulation on a flexible joint example.

FAULT occurrence in real operating systems usually is inevitable and it may lead to performance degradation or failure and requires to be meddled quickly by making appropriate decisions, otherwise, it could cause major catastrophe. This gives rise to strong demands for enhanced FAULT tolerant control to compensate the destructive effects and increase system reliability and safety in the presence of FAULTs. In this paper, an approach for ESTIMATION and control of simultaneous actuator and sensor FAULTs is presented by using integrated design of a FAULT ESTIMATION and FAULT tolerant control for time-varying linear systems. In this method, an unknown input observer-based FAULT ESTIMATION approach with both state feedback control and sliding mode control was developed to assure the closed-loop system's robust stability via solving a linear matrix inequality formulation. The presented method has been applied to a linear parameter varying system and the simulation results show the effectiveness of this method for FAULT ESTIMATION and system stability.

An important technique in image and video processing is global motion ESTIMATION (GME). The common GME methods can be classified in direct and indirect categories. Whereas the direct global motion ESTIMATION techniques boast reasonable precision they tend to suffer from high complexity. As with indirect methods, though presenting lower complexity, they mostly exhibit lower accuracy than their direct counterparts. In this paper, the authors introduce a robust algorithm for GME with near identical accuracy and almost 50-times FASTer than MPEG-4 verification model (VM). This approach entails two stages in which, first, motion vector of sampled block is employed to obtain initial GME then Levenberg-Marquardt algorithm is applied to the subsampled pixels to optimize the initial GME values. As will be shown, the proposed solution exhibits remarkable accuracy and speed features with experimental results distinctively bearing them out.

In this paper, an adaptive FAULT tolerant nonlinear control is proposed for attitude tracking problem of satellite with three magnetorquers and one reaction wheel in the presence of inertia uncertainties, external disturbances, and actuator FAULTs. Firstly, sliding surface variable is chosen based on avoiding the singularity of control signal and guaranteeing the convergence of attitude tracking error to zero in a finite-time. Subsequently, modified non-singular FAST terminal sliding mode is designed as FAULT tolerant control approach. Then, the control gain of reaching law is adaptively designed to improve the performance of proposed controller. The adaptive control gain is designed independent of the upper and lower bounds of the actuator effectiveness factors. Stability proof is performed by Lyapunov function candidate to show that attitude tracking errors and angular velocities are converged to zero. To evaluate the performance of proposed method, simulation results are compared with their non-adaptive version. Outcomes show better performance of the proposed controller in tracking the desired attitude, a significant reduction in convergence time, and reduction in the chattering of control torque.

Double-circuit power systems are one of the main types of modern transmission lines due to their reliability. FAULT location in these transmission lines has always been a potential problem due to the mutual coupling between lines. Accordingly, this paper presents a novel objective function for the FAULT location using synchronous post-FAULT measurements of currents and voltages captured by distance protective relays. Moreover, a FAST and accurate modern metaheuristic optimization algorithm for this cost function is proposed, which are key parameters to estimate the FAULT location methods based on optimization algorithms. In this regard, first, the input data (current and voltage signals) were refined using some auxiliary functions such as FAST Fourier transformation (FFT), Decaying Dc Elimination (DDE), and frequency tracking algorithm to accurately extract the fundamental component of the voltage and current signals. Afterwards, the proposed FAULT location based on the proposed metaheuristic optimization algorithm estimates the FAULT location using these input signals. The main advantage of the presented algorithm is the parallel ESTIMATION processing to improve the convergence speed and the accuracy of the objective function of the FAULT location, and was applied to various FAULT types and various operating conditions to validate the performance of the proposed approach. In addition, the performance of the proposed method was compared with different FAULT location methods. The simulation was implemented in the PSCAD and MATLAB® software. The simulation results show that the novel proposed approach outperforms other FAULT locations in estimating the FAULT location.