in this paper, an adaptive neuro fuzzy inference system (anfis) based control is proposed for the tracking of a micro-electro mechanical systems (mems) gyroscope sensor. the anfis is used to train parameters of the controller for tracking a desired trajectory. numerical simulations for a mems gyroscope are looked into to check the effectiveness of the anfis control scheme. it proves that the sy...

In this paper, we present a novel onboard robust visual algorithm for long-term arbitrary 2D and 3D object tracking using a reliable global-local object model for unmanned aerial vehicle (UAV) applications, e.g., autonomous tracking and chasing a moving target. The first main approach in this novel algorithm is the use of a global matching and local tracking approach. In other words, the algori...

This paper proposes a nonlinear path control for backward driving of a car-like mobile robot pushing trailer with off-axle hitching. The control law is constructed using high-gain design techniques and involves error coordinates expressed which are partially linked to the trailer and invariant properties with respect to the vehicle speed. The stability of the closed-loop system is analyzed usin...

This paper presents a fast frontal face detection method. We use motion segmentation algorithm that makes use of differencing to detect moving people’s faces. The novelty of this paper comes from the differencing in real time input images, preprocessing to remove noises (morphological operator and so on), detecting edge lines and restoration, finding the face area and cutting the head candidate...

One of the main problems in wind energy conversion system (WECS) is how to achieve maxim­u­m output power in different wind speeds. Maximum methods for maximum power point tracking in wind energy conversion syst­e­ms require the knowledge of system characteristics and mechanic sensors. So, using these methods practically will follow with high price and an abundant difficulties. In this pape...

We consider Bayesian inference in sequential latent variable models in general, and in nonlinear state space models in particular (i.e., state smoothing). We work with sequential Monte Carlo (SMC) algorithms, which provide a powerful inference framework for addressing this problem. However, for certain challenging and common model classes the state-of-the-art algorithms still struggle. The work...