Event-triggered distributed receding horizon control for tracking and formation of homogeneous multi-agent systems

This paper proposes an event-triggered distributed receding horizon control (DRHC) approach for the formation and tracking problems of homogeneous multi-agent systems. For each agent, an event-triggering condition, based on assumed predictive information of the neighbours, is derived from stability analysis. Considering the uncertain deviation between the assumed and true predictive information, we design a time-varying compatibility constraint for the individual optimization problem. In the event-triggered DRHC algorithm, each agent solves the optimization problem and communicates with its neighbours only when the event-triggering condition is satisfied, so the communication and computation burden are reduced. Moreover, guarantees for the recursive feasibility and asymptotic stability of the overall system are proved. A simulation example is provided to illustrate effectiveness of the proposed approach.     

Compound fault-tolerant attitude control for hypersonic vehicle with reaction control systems in reentry phase

In this paper, a novel compound fault-tolerant attitude control (FTC) scheme is proposed for reentry hypersonic vehicles with aerodynamic surfaces and reaction control systems (RCS) in the presence of parameter uncertainties, external disturbances and aerodynamic surfaces faults. Aerodynamic surfaces work as the primary actuators and RCS serve as auxiliary actuators. When aerodynamic surfaces cannot provide the required attitude control torque due to low dynamic pressure or faults, RCS are activated to assist aerodynamic surfaces to generate the residual torque. A nonlinear disturbance observer-based sliding mode controller is designed to calculate the required attitude control torque which can handle the parametric uncertainties and external disturbances together. The quadratic programming method is applied to obtain the optimal aerodynamic surfaces deflections from the required control torque. An innovative fuzzy rule-based decision-making system is design to solve the RCS control allocation problem, which is conceptually easy to understand and computationally efficiently compared with existing approaches. Based on quantized control theory, the closed-loop control system stability is rigorously analyzed. Simulation results are given to demonstrate the effectiveness and efficiency of developed FTC scheme.     

A review on MRAS-type speed estimators for reliable and efficient induction motor drives

Induction machines have recently been very popular in variable-speed drives, because of their robust construction and relatively low manufacturing costs (brushless), maintenance-free and well-matured control methods. However, for high-precision control and efficiency optimization one needs the information on the rotor speed which can be measured using different speed sensors. All sensors require a mounting space and cabling, they also generate extra costs and reduce system reliability. Therefore, many of the recent research efforts have been dedicated to sensorless or encoderless electrical drives offering such considerable advantages as: lower cost, reduced size and hardware complexity of the drive system, elimination of sensor cables, lower maintenance requirements, possible operation in aggressive environment, higher noise immunity, reliable and user friendly operation. In this article all well-known sensorless techniques are shortly addressed, but the main focus is on the solutions based on the Model Reference Adaptive System (MRAS) concept. The mathematical models and schemes of all types of MRAS-type speed estimators known from the literature are gathered in this article. The comparative analysis of these speed estimators is done from the following points of view: the speed adaptation mechanism derivation based on the Lyapunov theory, stability problems near zero speed and in the regenerating operation mode, and the sensitivity of MRAS estimators to induction machine parameter changes.     

Visual detection and tracking with UAVs,following a mobile object

ABSTRACT

Conception and development of an Unmanned Aerial Vehicle (UAV) capable of detecting, tracking and following a moving object with unknown dynamics is presented in this work, considering a human face as a case of study. Object detection is accomplished by a Haar cascade classifier. Once an object is detected, it is tracked with the help of a Kalman Filter (KF), and an estimation of the relative position with respect to the target is obtained. A linear controller is used to validate the proposed vision scheme and for regulating the aerial robot's position in order to keep a constant distance with respect to the mobile target, employing as well the extra available information from the embedded sensors. The proposed system was extensively tested in real-time experiments, through different conditions, using a commercial quadcopter connected via wireless to a ground station running under the Robot Operative System (ROS). The proposed overall strategy shows a good performance even under disadvantageous conditions as outdoor flight, being robust against illumination changes, image noise and the presence of other people in the scene.     

Digital hysteresis sliding mode control for interleaved DC–DC converters

This paper presents a digital constant frequency sliding mode control (SMC) law for interleaved DC–DC converters. Constant switching frequency and interleaving are achieved by dynamically adjusting the hysteresis of the control signals generating comparators. The interleaving method neither imposes constraints on the number of required phases to obtain a specific output voltage nor uses quasi-SMC. Hence, the control scheme achieves high flexibility, robustness, and performance. Furthermore, a sliding mode observer (SMO) for reconstructing the inductor currents is proposed. Experimental results for a two-phase buck converter are reported. The control concept accomplishes an improved dynamic performance in comparison with quasi-SMC.     

Design of switchable band‐notched frequency selective absorber

An active band‐notched frequency selective absorber (BNFSA) with switchable notch band is proposed in this article. The BNFSA is a two‐layer structure composed of a lossy layer at the top and a ground plane at the bottom, separated by an air spacer. The element of the lossy layer is a lumped‐resistor‐loaded metallic dipole with a parallel LC resonance structure, which is realized by complementary n‐shaped resonator (CnR) inserted in the center, and PIN diode is welded at two arms of CnR. The bias circuit printed on the back of the substrate of the lossy layer connects to anode and cathode of the diode by via hole and isolates by the inductor. Simulation results show that the notch bands are located at 4.50 and 6.81 GHz when the diode sets to ON and OFF, respectively. To validate the performance of switchable BNFSA, the prototypes are fabricated and measured, reasonable agreement between simulated and measured results is obtained.     

A novel miniaturized frequency selective surface

A novel single layer miniaturized frequency selective surface made of circular unit cell elements is presented in this article. The frequency selective surface (FSS) unit cell measures 0.055λ₀ × 0.055λ₀, where λ₀ corresponds to its free space wavelength. The proposed FSS offers band stop characteristics with bandwidth of 137.5 MHz centered at 1.39 GHz. The symmetrical structure of the unit cell elements provides polarization independency. The miniaturized unit cell elements help achieving angular independency for both TE and TM mode of polarization. The miniaturized design provides excellent angular independency with negligible frequency shift for varying incident angles. A prototype of the FSS is fabricated and its simulation results are validated using measurements.     

基于结构化遮挡编码和极限学习机的局部遮挡人脸识别

提出使用结构化遮挡编码（SOC）结合极限学习机（ELM）的算法来处理人脸识别中的遮挡问题。首先，使用SOC去除图像上的遮挡物，将遮挡物体与人脸分离开；同时，通过局部性约束字典（LCD）来估计遮挡物的位置，建立遮挡字典和人脸字典。然后，将建立好的人脸字典矩阵进行归一化处理，并利用ELM对归一化的数据进行分类识别。最后，在AR人脸库上进行的仿真实验结果表明，所提方法对不同遮挡物和不同区域遮挡的图像具有较好的识别率和鲁棒性。     

基于PSO-ELM模型的潜油柱塞泵冲次优化方法

为改进油井后期泵效低下、能耗高等缺陷，提出了一种基于PSO-ELM模型的潜油柱塞泵冲次优化方法.采用粒子群（PSO）算法与极限学习机（ELM）相结合的方式来实现动液面软测量建模；根据动液面及潜油柱塞泵工作电流变化，以油井运行经济性最优为目的建立目标函数得到潜油柱塞泵冲次，解决了在油井生产时不能准确调节抽油机冲次问题；最后以目标函数关系建立模糊控制器模型，根据输入参数调整潜油柱塞泵冲次.实验结果表明，建立的软测量模型预测动液面精度高，模糊控制器能够更加合理地调整抽油机冲次，最终达到智能调整冲次大小、提高油井采油率及节能的目的.     

On one boundary problem for nonlinear stationary controlled system

The object of study is nonlinear stationary controlled system of ordinary differential equations with constant disturbance in the right part. The problem of constructing the synthesising control function providing the transfer of this system from the initial state to the origin is considered. The sufficiently simple for numerical implementation algorithm of solution of the above-mentioned problem is obtained. It is shown that for local null controllability of the considered system, it is sufficient that the conditions of the Kalman's type were satisfied. In addition, the estimates restricting the choice of initial conditions and external disturbances under which the transfer is guaranteed are obtained. The main idea of the method of construction of the desired control function consists in reducing the original problem to stabilisation of a special kind linear non-stationary system and solving the Cauchy problem for an auxiliary system of ordinary differential equations closed by stabilising control. The simplicity of the realisation of this algorithm is determined by the construction of the auxiliary system and its stabilisation that could be obtained by analytical methods. The effectiveness of the method is illustrated by solving the problem of crane control and its numerical simulation.