Unlike traditional visual cryptography based on a threshold mechanism in which the secret image can be revealed by stacking k,(2≤k≤n) shadows or more. In our suggested (kk,nn) progressive secret sharing scheme with unexpanded pixel, we could obtain until n−1n−1 revealed secret images with progressive enhanced contrast in an increasing way from the lowest quality, in the case of stacking two shares, to a highest quality in the case of stacking all the nn shares. Our scheme not only has the advantage of the unexpanded shares, but also the use of very simple Boolean XOR and OR operations to recover the secret image perfectly. Moreover, the proposed scheme does not need any codebooks to construct shares. The experimental results indicate the privilege of our method compared with the other related work.

Electrocardiogram (ECG) signals are often contaminated with artefacts and noises which can lead to incorrect diagnosis when they are visually inspected by cardiologists. In this paper, the well-known discrete Fourier series (DFS) is re-explored and an efficient DFS-based method is proposed to reduce contribution of both baseline wander (BW) and powerline interference (PLI) noises in ECG records. In the first step, the determination of the exact number of low frequency harmonics contributing in BW is achieved. Next, the baseline drift is estimated by the sum of all associated Fourier sinusoids components. Then, the baseline shift is discarded efficiently by a subtraction of its approximated version from the original biased ECG signal. Concerning the PLI, the subtraction of the contributing harmonics calculated in the same manner reduces efficiently such type of noise. In addition of visual quality results, the proposed algorithm shows superior performance in terms of higher signal-to-noise ratio and smaller mean square error when faced to the DCT-based algorithm.

In this paper, state variables estimation and Fuzzy Sliding Mode Control (FSMC) are presented in order to estimate the state variables and altitude-attitude tracking control in presence of internal and external disturbances for unmanned quadrotor. The main idea of the proposed control strategy is the development of an Extended Kalman Filter (EKF) for the observation of the states. Fuzzy logic systems are used to adapt the unknown switching-gains to eliminate the chattering phenomenon induced by Sliding Mode Control (SMC). The stability of the system is guaranteed in the sense of Lyapunov. The effectiveness and robustness of the proposed controller-observer scheme that takes into account internal and external disturbances are demonstrated on computer simulation using Matlab environment.

A robust nonlinear controller based on an improved feedback linearization technique with state observer in presence of uncertainties and external disturbances is developed for a class of nonlinear systems. First, by combining classical feedback linearization approach with a robust control term and a fuzzy logic system, we design and study an efficient controller for such systems. Second, we propose an optimized extended Kalman filter for the observation of the states. The parameters to be optimized are the covariance matrices Q and G, which play an important role in the extended Kalman filter performances. This optimization is insured by the particle swarm optimization algorithm. The Lyapunov synthesis approach is used to prove the stability of the whole control loop. The proposed approach is simulated on a nonlinear inverted‐pendulum system. Simulation results demonstrate the robustness and effectiveness of the proposed scheme and exhibit a more superior performance than its conventional counterpart.

In this study, an optimized extended Kalman filter (EKF), and an interval type-2 fuzzy sliding mode control (IT2FSMC) in presence of uncertainties and disturbances are presented for robotic manipulators. The main contribution is the proposal of a novel application of Biogeography-Based Optimization (BBO) to optimize the EKF in order to achieve high performance estimation of states. The parameters to be optimized are the covariance matrices Q and R, which play an important role in the performances of EKF. The interval type-2 fuzzy logic system is used to avoid chattering phenomenon in the sliding mode control (SMC). Lyapunov theorem is used to prove the stability of control system. The suggested control approach is demonstrated using a computer simulation of two-link manipulator. Finally, simulations results show the robustness and effectiveness of the proposed scheme, and exhibit a more superior performance than its conventional counterpart.

The main purpose of this paper is to integrate fuzzy logic technique and backstepping synthesis to sliding mode control to develop a Fuzzy Backstepping-Sliding Mode Controller (FBSMC) to resolve the problem of altitude and attitude tracking control of unmanned quadrotor systems under large external disturbances. First, a backstepping-sliding mode control for quadrotor is introduced. Moreover, a fuzzy logic system is employed to adapt the unknown switching gains to eliminate the chattering phenomenon induced by switching control on the conventional Backstepping-Sliding Mode Controller (BSMC). The dynamical motion equations are obtained by EulerNewton formalism. The stability of the system is guaranteed in the sense of the Lyapunov stability theorem. Simulation results are carried out using Matlab/Simulink environment to illustrate the effectiveness and robustness of the proposed controller.