Quaternion-based robust trajectory tracking control for uncertain quadrotors

This paper presents a robust nonlinear controller design approach for uncertain quadrotors to implement trajectory tracking missions. The quaternion representation is applied to describe the rotational dynamics in order to avoid the singularity problem existing in the Euler angle representation. A nonlinear robust controller is proposed, which consists of an attitude controller to stabilize the rotational motions and a position controller to control translational motions. The quadrotor dynamics involves uncertainties such as parameter uncertainties, nonlinearities, and external disturbances and their effects on closed-loop control system can be guaranteed to be restrained. Simulation results on the quadrotor demonstrate the effectiveness of the designed control approach.     

A low-complexity sensor fusion algorithm based on a fiber-optic gyroscope aided camera pose estimation system

Visual tracking, as a popular computer vision technique, has a wide range of applications, such as camera pose estimation. Conventional methods for it are mostly based on vision only, which are complex for image processing due to the use of only one sensor. This paper proposes a novel sensor fusion algorithm fusing the data from the camera and the fiber-optic gyroscope. In this system, the camera acquires images and detects the object directly at the beginning of each tracking stage; while the relative motion between the camera and the object measured by the fiber-optic gyroscope can track the object coordinate so that it can improve the effectiveness of visual tracking. Therefore, the sensor fusion algorithm presented based on the tracking system can overcome the drawbacks of the two sensors and take advantage of the sensor fusion to track the object accurately. In addition, the computational complexity of our proposed algorithm is obviously lower compared with the existing approaches(86% reducing for a 0.5 min visual tracking). Experiment results show that this visual tracking system reduces the tracking error by 6.15% comparing with the conventional vision-only tracking scheme(edge detection), and our proposed sensor fusion algorithm can achieve a long-term tracking with the help of bias drift suppression calibration.     

Single event upset rate modeling for ultra-deep submicron complementary metal-oxide-semiconductor devices

Based on the integral method of single event upset(SEU) rate and an improved charge collection model for ultra-deep submicron complementary metal-oxide-semiconductor(CMOS) devices, three methods of SEU rate calculation are verified and compared. The results show that the integral method and the figure of merit(FOM) methods are basically consistent at the ultra-deep submicron level. By proving the validity of the carrier collection model considering charge sharing, the applicability of two FOM methods is verified, and the trends of single-bit and multiple-bit upset rates for ultra-deep submicron CMOS are analyzed.     

Tree-based data retrieval algorithm for multi-item request with deadline in wireless networks

The data retrieval problem in wireless communication has attracted increasing attentions in many applications such as electronic information sharing and e-business. However, most existing studies do not consider how to retrieve the requested data items in their deadlines. In this paper, we discuss the so-called deadline-based multi-item data retrieval problem, which aims at finding an access pattern for retrieving requested data items in certain deadlines such that the access latency and data miss rate are minimized. We propose two algorithms, named EDFS and UR, to deal with the above problem. The EDFS algorithm gives priority to retrieve the requested data item with the least deadline, while the UR algorithm introduces the urgent rate that is computed by the broadcast time and deadline of requested data item for further reducing the access latency and data miss ratio. Moreover, we design a tree-based data retrieval algorithm that finds the longest downloading sequence of data items in one broadcast cycle and is applied to EDFS and UR for finding data retrieval sequence of requested data items. The efficiency of our proposed schemes has been validated by the extensive experiments.     

A social tag clustering method based on common co-occurrence group similarity

Social tagging systems are widely applied in Web 2.0. Many users use these systems to create, organize, manage, and share Internet resources freely. However, many ambiguous and uncontrolled tags produced by social tagging systems not only worsen users’ experience, but also restrict resources’ retrieval efficiency. Tag clustering can aggregate tags with similar semantics together, and help mitigate the above problems. In this paper, we first present a common co-occurrence group similarity based approach, which employs the ternary relation among users, resources, and tags to measure the semantic relevance between tags. Then we propose a spectral clustering method to address the high dimensionality and sparsity of the annotating data. Finally, experimental results show that the proposed method is useful and efficient.     

阶梯状抽水试验水文地质参数确定

针对传统阶梯状抽水试验参数计算过程中,通常只选择抽水阶段的部分试验数据等问题,应用Theis公式及叠加原理,利用抽水试验所有降深数据(抽水和水位恢复阶段全部资料)求解水文地质参数,利用承压含水层抽水试验数据计算得出导水系数、储水系数,利用潜水含水层抽水试验数据计算得出渗透系数和给水度,此外在低效率抽水井中利用抽水试验数据计算得出井损系数和井流量指数。计算过程中,利用Excel计算并绘制计算水位降深和观测水位降深的拟合曲线,计算过程简单快捷。整个抽水试验过程中,不必再分别提出抽水、水位恢复期的计算公式,可以避免人为选择单个水位降深数据对参数求解带来的影响。     

喀麦隆曼维莱水电站枢纽布置设计

介绍了曼维莱水电站枢纽布置设计及优化过程,在合同方案基础上,根据最新的补充勘测资料及多方案研究对比,对坝线选择、引水发电系统方案选择和厂区枢纽布置及优化设计工作做了详细的介绍,可供同类工程参考。     

Model Predictive Control for Discrete‐Time Systems with Random Delay and Randomly Occurring Nonlinearity

In this paper, the model predictive control problem is investigated for a class of discrete‐time systems with random delay and randomly occurring nonlinearity. The randomly occurring nonlinearity, which describes the phenomena of a class of nonlinear disturbances occurring in a random way, is modeled according to a Bernoulli distributed white sequence with a known conditional probability. Moreover, the random delay is governed by a discrete‐time finite‐state Markov chain. The approach of delay fractioning is applied to the controller synthesis. It is shown that the proposed model predictive controller guarantees the stochastic stability of the closed‐loop system. Finally, a numerical simulation is given to illustrate the effectiveness of the proposed method.