Visual Object Tracking and Servoing Control of a Nano-Scale Quadrotor: System,Algorithms, and Experiments

There are two main trends in the development of unmanned aerial vehicle (UAV) technologies: miniaturization and intellectualization, in which realizing object tracking capabilities for a nano-scale UAV is one of the most challenging problems. In this paper, we present a visual object tracking and servoing control system utilizing a tailor-made 38 g nano-scale quadrotor. A lightweight visual module is integrated to enable object tracking capabilities, and a micro positioning deck is mounted to provide accurate pose estimation. In order to be robust against object appearance variations, a novel object tracking algorithm, denoted by RMCTer, is proposed, which integrates a powerful short-term tracking module and an efficient long-term processing module. In particular, the long-term processing module can provide additional object information and modify the short-term tracking model in a timely manner. Furthermore, a position-based visual servoing control method is proposed for the quadrotor, where an adaptive tracking controller is designed by leveraging backstepping and adaptive techniques. Stable and accurate object tracking is achieved even under disturbances. Experimental results are presented to demonstrate the high accuracy and stability of the whole tracking system.      

A class of genetic algorithms for multiple-level warehouse layout problems

A new kind of warehouse layout problem, multiple-level warehouse layout problem (MLWLP), is investigated. Both horizontal and vertical travel costs need to be considered when making a layout. In the problem, unit travel costs are item-dependent and different items can be mixed in a cell. An IP model is proposed, which is shown to be NP-hard. An effective assignment method is presented and genetic algorithm heuristics developed. Extensive computational experiments are conducted to verify the effectiveness of the algorithms.     

Nonlinear maximum power point tracking control and modal analysis of DFIG based wind turbine

The doubly fed induction generator based wind turbine (DFIG-WT) has strong nonlinearities originated from the aerodynamics of the wind turbine and the coupled dynamic of the DFIG, and can operate under a time-varying and wide operation region. This paper investigates a feedback linearisation controller based on the detailed model of the DFIG-WT, the control objective is to maximize energy conversion for this system. The original nonlinear system is partially linearized to a third-order linear system and a remained second-order internal nonlinear system. Fully decoupled control of the external dynamics is achieved, and the stability of the remained internal dynamics is analyzed via Lyapunov stability method. Moreover, modal analysis is applied for the nonlinear system controlled by the proposed nonlinear controller to verify its global optimal performance and low-voltage ride-through (LVRT) capability over various wind operation range. Simulation studies verify that more accurate tracking and better LVRT capability can be achieved in comparison with conventional vector control (VC).     

Recursive implementation of MUSIC algorithm to minimize power system disturbances

This paper exhibits new recursive implementation of the root-MUSIC algorithm in power system applications in order to extract the instantaneous power disturbances, which emanate from the arc furnace. The MUSIC algorithm is selected because it has an outstanding capability to estimate and track the frequencies of all types of distortion such as harmonics and interharmonics. The utilized algorithm has been newly developed so as to recursively track the instantaneous disturbances in the arc furnace current and consequently mitigate them. The suggested development of the recursive root-MUSIC is compared with the ESPRIT in order to prove that the adopted technique outperforms the high-resolution common techniques in a noisy or non-noisy environment. The instantaneous disturbance is formed by an innovative formulation of the recursive notch filter. Moreover, the experimental results are given to prove the practicality of the proposed concepts and techniques.     

Gaussian mixture presentation of measurements for long-range radar tracking

In long-range radar tracking, the measurement uncertainty region has a thin and curved shape in Cartesian space due to the fact that the measurement is accurate in range but inaccurate in angle. Such a shape reflects grievous measurement nonlinearity, which can lead to inconsistency in tracking performance and significant tracking errors in traditional nonlinear filters, such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). In this paper, we propose a modified version of the Gaussian Mixture Measurement-Integrated Track Splitting (GMM-ITS) filter to deal with the nonlinearity of measurements in long-range radar tracking. Not only is the state probability density function (pdf) approximated by a set of Gaussian track components, but the likelihood function (LF) is approximated by several Gaussian measurement components. In this way, both the state pdf and LF in the proposed filter have more accurate approximation than traditional filters that approximate measurements using just one Gaussian distribution. Simulation experiments show that the proposed filter can successfully avoid the inconsistency problem and also obtain high tracking accuracy in both 2-D (with range-angle measurements) and 3-D (with range-direction-cosine measurements) long-range radar tracking.     

不确定性X-Y定位平台PID控制方法研究

X-Y定位平台属于强耦合非线性系统,且由于结构复杂性及外界干扰,当前测量水平难以获得其精确的数学模型,提出基于自适应神经网络的PID控制策略。考虑到X-Y定位平台系统精确的数学模型难以获得,利用神经网络良好的学习能力来逼近系统未知非线性模型,设计神经网络控制器;为了保证神经网络在学习的初期阶段的控制精度,设计PID控制器来进行辅助补偿控制;为加快学习速度,提高运动控制的实时性,设计变学习率的优化算法来实现神经网络权值的在线调整。试验结果验证了所提控制方法的有效性。     

Enhanced control strategies for a hybrid battery/photovoltaic system using FGS-PID in grid-connected mode

This paper suggests improved control strategies using Fuzzy Gain Scheduling of Proportional-Integral-Derivative (FGS-PID) controller for a hybrid Photovoltaic (PV) and Battery Energy Storage (BES) system under different weather conditions. The proposed scheme is implemented using a two-level control system structure, combining the benefits of the PID as well as the fuzzy logic controller (FLC) for maximum power point tracking (MPPT). Ziegler-Nichols tuning method is also employed to select the initial values of PID gains. Within the period of steady-states and transients, FGS-PID adopts the gains to ensure the stability of the control scheme. It also damps out transient fluctuations and reduces settling time. Also, BES could be employed to provide a stable and reliable power from the output of PV sources to loads. It can enhance the performance of the entire power system during the grid-connected mode. The simulation results under Matlab/Simulink show that the suggested control strategies are robustness, fast transient response and proper steady-state performance in the grid-connected mode in comparison other presented methods.     

Design and validation of a motion-tracking system for ROM measurements in home rehabilitation

This work deals with the design, implementation and experimental validation of a home rehabilitation system capable of bringing a real-time 3D reconstruction of human posture to the therapist’s desk. The system has been validated against two commercial systems, capable of providing joint angle measurements and commonly used in rehabilitation gyms, which are used profitably to assist clinics in limb motor dysfunction treatment. Early experimental results promise to provide measurements accurate enough to complement the subjective therapist’s perception with objective observations, leading to quantitative evaluation.