Trust-region based instantaneous optimal semi-active control of long-span spatially extended structures with MRF-04K damper

In the field of civil engineering, magnetorheological fluid （MRF） damper-based semi-active control systems have received considerable attention for use in protecting structures from natural hazards such as strong earthquakes and high winds. In this paper, the MRF damper-based semi-active control system is applied to a long-span spatially extended structure and its feasibility is discussed. Meanwhile, a _trust-region method based instantaneous optimal semi-active control algorithm （TIOC） is proposed to improve the performance of the semi-active control system in a multiple damper situation. The proposed TIOC describes the control process as a bounded constraint optimization problem, in which an optimal semi- active control force vector is solved by the trust-region method in every control step to minimize the structural responses. A numerical example of a railway station roof structure installed with MRF-04K dampers is presented. First, a modified Bouc- Wen model is utilized to describe the behavior of the selected MRF-04K damper. Then, two semi-active control systems, including the well-known clipped-optimal controller and the proposed TIOC controller, are considered. Based on the characteristics of the long-span spatially extended structure, the performance of the control system is evaluated under uniform earthquake excitation and travelling-wave excitation with different apparent velocities. The simulation results indicate that the MR fluid damper-based semi-active control systems have the potential to mitigate the responses of full-scale long-span spatially extended structures under earthquake hazards. The superiority of the proposed TIOC controller is demonstrated by comparing its control effectiveness with the clipped-optimal controller for several different cases.

Power-balancing Instantaneous Optimization Energy Management for a Novel Series-parallel Hybrid Electric Bus

Energy management（EM） is a core technique of hybrid electric bus（HEB） in order to advance fuel economy performance optimization and is unique for the corresponding configuration. There are existing algorithms of control strategy seldom take battery power management into account with international combustion engine power management. In this paper, a type of power-balancing instantaneous optimization（PBIO） energy management control strategy is proposed for a novel series-parallel hybrid electric bus. According to the characteristic of the novel series-parallel architecture, the switching boundary condition between series and parallel mode as well as the control rules of the power-balancing strategy are developed. The equivalent fuel model of battery is implemented and combined with the fuel of engine to constitute the objective function which is to minimize the fuel consumption at each sampled time and to coordinate the power distribution in real-time between the engine and battery. To validate the proposed strategy effective and reasonable, a forward model is built based on Matlab/Simulink for the simulation and the dSPACE autobox is applied to act as a controller for hardware in-the-loop integrated with bench test. Both the results of simulation and hardware-in-the-loop demonstrate that the proposed strategy not only enable to sustain the battery SOC within its operational range and keep the engine operation point locating the peak efficiency region, but also the fuel economy of series-parallel hybrid electric bus（SPHEB） dramatically advanced up to 30.73% via comparing with the prototype bus and a similar improvement for PBIO strategy relative to rule-based strategy, the reduction of fuel consumption is up to 12.38%. The proposed research ensures the algorithm of PBIO is real-time applicability, improves the efficiency of SPHEB system, as well as suite to complicated configuration perfectly.

Dynamics and adaptive control of a dual-arm space robot with closed-loop constraints and uncertain inertial parameters

A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.

Application of Single Neuron Adaptive PID Regulators with Auto-tuning Gain in Industrial Parameter(Pressure)Closed-loop Process Control Systems

A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of induStrial parameter closed-loop process controlsystems is improved, and the work quality of the systems bettered.

Interference Management for DS-CDMA Systems through Closed-Loop Power Control, Base Station Assignment, and Beamforming

In this paper, we propose a smart step closed-loop power control (SSPC) algorithm and a base station assignment method based on minimizing the transmitter power (BSA-MTP) technique in a direct sequence-code division multiple access (DS-CDMA) receiver with frequency-selective Rayleigh fading. This receiver consists of three stages. In the first stage, with constrained least mean squared (CLMS) algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference (IPI) is reduced in other paths in each RAKE finger. Also in this stage, the multiple access interference (MAI) from other users is reduced. Thus, the matched filter (MF) can use for more reduction of the IPI and MAI in each RAKE finger in the second stage. Also in the third stage, the output signals from the matched filters are combined according to the conventional maximal ratio combining (MRC) principle and then are fed into the decision circuit of the desired user. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can significantly reduce the network bit error rate (BER) compared to the other methods. Also, we observe that significant savings in total transmit power (TTP) are possible with our methods.

Method for Evaluating Instantaneous Sector Capacity

A method for evaluating instantaneous sector capacity based on the workload of air traffic controller(ATC)is developed.The basic characteristics of the assessed sector is described and a model to correlate the workload with the instantaneous sector capacity is developed using workload data.The correlation between the regional sector/approach sector capacity and the traffic flow organization is analyzed.Experimental results show that the instantaneous sector capacity assessment is reasonable and the instantaneous capacity is strongly correlated with the spatial and temporal distributions of the traffic flow and the sector operation mode.These results can provide an important reference for sector operation safety,capacity prediction,air traffic management,and airspace design.

Model Reference Adaptive Control for Switched Systems with Closed-loop Reference Model Under Arbitrary Switching

This paper explores the model reference adaptive control problem for a class of switched linear systems under arbitrary switching with no need for the measurability of the system state.Based on the state of reference model and the measurable output error, adaptive laws and controllers are designed for switched systems.Each subsystem may have its individual reference model and controller, which increases the design flexibility.The introduction of the closed-loop reference model is to get a better transient performance of the whole switched systems.A numerical example is provided to verify the effectiveness of the main results.

Joint Closed-Loop Power Control and Adaptive Beamforming for Wireless Networks with Antenna Arrays in a 2D Urban Environment

The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to decrease the interference in wireless communication networks. In this paper, we propose smart step closed-loop power control (SSPC) algorithm in wireless networks in a 2D urban environment with constrained least mean squared (CLMS) algorithm. This algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. Also, we present switched-beam (SB) technique for enhancing signal to interference plus noise ratio (SINR) in wireless networks. Also, we study an analytical approach for the evaluation of the impact of power control error (PCE) on wireless networks in a 2D urban environment. The simulation results indicate that the convergence speed of the SSPC algorithm is faster than other algorithms. Also, we observe that significant saving in total transmit power (TTP) are possible with our proposed algorithm. Finally, we discuss three parameters of the PCE, number of antenna elements, and path-loss exponent and their effects on capacity of the system via some computer simulations.

A Deep Reinforcement Learning-Based Power Control Scheme for the 5G Wireless Systems

In the fifth generation(5G)wireless system,a closed-loop power control(CLPC)scheme based on deep Q learning network(DQN)is introduced to intelligently adjust the transmit power of the base station(BS),which can improve the user equipment(UE)received signal to interference plus noise ratio(SINR)to a target threshold range.However,the selected power control(PC)action in DQN is not accurately matched the fluctuations of the wireless environment.Since the experience replay characteristic of the conventional DQN scheme leads to a possibility of insufficient training in the target deep neural network(DNN).As a result,the Q-value of the sub-optimal PC action exceed the optimal one.To solve this problem,we propose the improved DQN scheme.In the proposed scheme,we add an additional DNN to the conventional DQN,and set a shorter training interval to speed up the training of the DNN in order to fully train it.Finally,the proposed scheme can ensure that the Q value of the optimal action remains maximum.After multiple episodes of training,the proposed scheme can generate more accurate PC actions to match the fluctuations of the wireless environment.As a result,the UE received SINR can achieve the target threshold range faster and keep more stable.The simulation results prove that the proposed scheme outperforms the conventional schemes.

Data-Driven Model Identification and Control of the Inertial Systems

In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the system in the open loop. To tackle these difficulties, an approach of data-driven model identification and control algorithm design based on the maximum stability degree criterion is proposed in this paper. The data-driven model identification procedure supposes the finding of the mathematical model of the system based on the undamped transient response of the closed-loop system. The system is approximated with the inertial model, where the coefficients are calculated based on the values of the critical transfer coefficient, oscillation amplitude and period of the underdamped response of the closed-loop system. The data driven control design supposes that the tuning parameters of the controller are calculated based on the parameters obtained from the previous step of system identification and there are presented the expressions for the calculation of the tuning parameters. The obtained results of data-driven model identification and algorithm for synthesis the controller were verified by computer simulation.

基于可控串联电抗的新能源送出线路故障性质识别方法

针对不带并联电抗器的新能源送出线,能否正确区分故障性质是确保新能源系统安全可靠运行的重中之重。为降低新能源送出线故障对电力设备和系统的冲击,提高重合闸成功率,减少新能源发电系统脱网的发生,提出基于可控串联电抗限流信息的新能源送出线路故障性质识别方法。在送出线路上设计串联可控限流电抗器,在线路故障相跳闸时基于等值阻抗的预判投入可控电抗,在串联电抗限流特性下分析瞬时性故障和永久性故障时的线路电流差异,建立电流突变量比较判据,并能够确定故障电弧熄灭时刻,进而构建新能源场站送出线路基于故障性质识别的自适应重合闸策略。仿真结果表明,所提方法能快速、可靠地识别结果,应用在新能源场站送出线路工程上能有效提高线路的重合率。

稳控装置在海油平台电网的应用

稳控装置采用先进的平台化设计思想,通过硬件、软件模块化设计提供标准模型服务。稳控装置是陆地电网遇到大扰动时,为保证电力系统稳定性而在电厂或变电站内装设的控制设备,按标准化策略实现切机、切负荷、快速减出力等功能。本文通过对国产电网稳控装置标准服务的研究,制定适应于海洋平台电站管理的稳控策略,完成稳控装置智能化策略和功能研发;根据现场策略需求配置稳控主从机,研发适用于现场工况的控制处置策略和智能化需求。

船舶永磁同步推进电机的优化I/f起动控制方法

为解决高转矩与高转动惯量的船舶推进电机在开环I/f控制中转速和转矩波动大、电机易失步、效率低的问题,提出一种I/f控制改进方法。通过建立转矩角观测器,调节给定电流矢量的幅值,使其跟随负载转矩变化,提高系统鲁棒性。同时,将电机运行状态推进至接近最大转矩电流比状态,提高电机的运行效率;通过瞬时有功功率调节电流矢量的角速度,降低电磁转矩波动,加快电机的转速收敛过程。最后,在Matlab/Simulink中进行仿真实验,实验结果表明该方法可以显著提高推进电机运行效率和稳定性。

基于自适应分层滑模的塔式起重机防摆与定位控制

针对三维空间中呈现二级摆结构的塔式起重机的防摆与定位控制问题,考虑变幅回转联合运行工况,提出了一种自适应分层滑模控制方案。首先将塔式起重机系统分为定位子系统、一级摆角子系统和二级摆角子系统,设计了分层滑模控制律;然后设计了自适应律,提高了系统对参数的适应性和对外在干扰的抑制性能;最后验证了系统的稳定性并对系统进行了仿真。仿真结果表明,系统在受到瞬时扰动时,自适应律可估算出扰动大小,控制器能快速做出反应,调整控制力/力矩以抵消瞬时扰动,使瞬时扰动不对系统的位置以及吊钩和负载的摆角造成明显影响。该文自适应分层滑模控制器能在一定程度上抑制瞬时扰动造成的吊钩和负载的摆动,具有较好的鲁棒性。

基于ICR的履带车辆路径跟踪与转向控制算法研究

针对丘陵山区单边制动农用履带车辆路径跟踪精度低、控制次数多、转向偏差大等问题,本文开展不同负载条件下履带车辆路径跟踪控制研究。首先,对履带车辆的转向运动学进行理论分析,并建立履带车辆运动学模型;其次,根据履带车辆单边制动转向特性,提出一种基于瞬时旋转中心(Instantaneous center of rotation, ICR)的大角度转向控制算法,该算法能够根据规划路径的转向点位置与履带车辆转向瞬心,规划出最优的转向目标点,并控制履带车辆在该转向目标点一次性转向到所需航向,与此同时,完成转向控制器设计;最后,开展履带车辆在3种不同负载条件下的仿真试验与田间试验。仿真结果表明,大角度转向控制算法产生的跟踪路径平均误差面积与平均转向控制次数分别降低68.95%、68.77%;田间试验结果表明,大角度转向控制算法产生的跟踪路径平均横向偏差均值、平均转向控制次数与转向点处平均最小偏差分别减少57.27%、33.93%、62.29%,且路径跟踪效果更优,验证了大角度转向控制算法的有效性。试验结果满足履带车辆路径跟踪的要求,为实现农用履带车辆的路径跟踪提供理论基础与参考。

不同暴雨条件下扇形和羽形流域的洪水规律

为了探讨降雨过程时空分布不均匀性对河道径流的影响,以沂河、沭河流域为例,利用瞬时单位线法和马斯京根法计算重现期为10、 20、 50 a的3 d特征暴雨和2019年台风“利奇马”暴雨在2个流域中的洪水流量,得出各防洪控制站在不同暴雨条件下的洪水规律。结果表明:扇形流域内洪水汇流较集中,容易发生洪灾;羽形流域内各支流洪水交错汇入干流,近水先去,远水后去,洪水较缓和,沂河的防汛压力大于沭河的防汛压力;在相同降雨量条件下,沂沭河流域内临沂站在从北向南的降雨过程中更易形成大洪峰,斜午站、石拉渊站和重沟站在从南向北的降雨过程中更易形成大洪峰;莒县站位于沭河上游,控制流域包含多个支流和3个水库,流域形状为属于羽形流域的沭河流域中的扇形流域,具有洪水汇流集中的特点,沭河莒县站的防汛压力大于沭河其他防洪控制站的防汛压力,而且当沭河流域出现大范围同步降雨过程时,莒县站更易形成大洪峰。

基于滑模神经网络直接瞬时转矩控制的优化

针对开关磁阻电机在滞环控制策略中存在的较大转矩脉动问题,在传统直接瞬时转矩控制的基础上引入了反向传播(BP)神经网络控制策略,以转矩误差的平方为性能指标函数对直接瞬时转矩控制进行优化调整,抑制了电机在运行时的转矩脉动。进一步,在整体双闭环控制策略基础上,引入滑模控制对转速环节进行改进,提高了系统的响应速度和鲁棒性。最后,利用Matlab/Simulink对传统直接瞬时转矩控制和改进直接瞬时转矩控制进行仿真测试,验证了所提策略的有效性和可行性。

Robot-Oriented 6G Satellite-UAV Networks: Requirements, Paradigm Shifts, and Case Studies

Networked robots can perceive their surroundings, interact with each other or humans,and make decisions to accomplish specified tasks in remote/hazardous/complex environments. Satelliteunmanned aerial vehicle(UAV) networks can support such robots by providing on-demand communication services. However, under traditional open-loop communication paradigm, the network resources are usually divided into user-wise mostly-independent links,via ignoring the task-level dependency of robot collaboration. Thus, it is imperative to develop a new communication paradigm, taking into account the highlevel content and values behind, to facilitate multirobot operation. Inspired by Wiener’s Cybernetics theory, this article explores a closed-loop communication paradigm for the robot-oriented satellite-UAV network. This paradigm turns to handle group-wise structured links, so as to allocate resources in a taskoriented manner. It could also exploit the mobility of robots to liberate the network from full coverage,enabling new orchestration between network serving and positive mobility control of robots. Moreover,the integration of sensing, communications, computing and control would enlarge the benefit of this new paradigm. We present a case study for joint mobile edge computing(MEC) offloading and mobility control of robots, and finally outline potential challenges and open issues.

Bioinspired Closed-loop CPG-based Control of a Robotic Manta for Autonomous Swimming

Fish in nature exhibit a variety of swimming modes such as forward swimming,backward swimming,turning,pitching,etc.,enabling them to swim in complex scenes such as coral reefs.It is still difficult for a robotic fish to swim autonomously in a confined area as a real fish.Here,we develop an untethered robotic manta as an experimental platform,which consists of two flexible pectoral fins and a tail fin,with three infrared sensors installed on the front,left,and right sides of the head to sense the surrounding obstacles.To generate multiple swimming modes of the robotic manta and online switching of different modes,we design a closed-loop Central Pattern Generator(CPG)controller based on distance information and use a combination of phase difference and amplitude of the CPG model to achieve stable and rapid adjustment of yaw angle.To verify the autonomous swimming ability of the robotic manta in complex scenes,we design an experimental scenario with a concave obstacle.The experimental results show that the robotic manta can achieve forward swimming,backward swimming,in situ turning within the concave obstacle,and finally exit from the area safely while relying on the perception of external obstacles,which can provide insight into the autonomous exploration of complex scenes by the biomimetic robotic fish.Finally,the swimming ability of the robotic manta is verified by field tests.

大黄■虫丸治疗非酒精性脂肪性肝炎痰瘀互结证的临床疗效与安全性

目的:观察大黄■虫丸治疗非酒精性脂肪性肝炎(NASH)痰瘀互结证的临床疗效与安全性。方法:选取2020年5月11日至2022年1月20日四川大学华西医院收治的NASH患者,均辨证为痰瘀互结证的患者216例作为研究对象,采用区组随机化方法分为对照组和观察组,每组108例,观察组脱失10例,对照组脱失9例。对照组接受健康宣教,根据病情给予降压、降糖、调脂、保肝降酶等标准化基础治疗;观察组在对照组治疗方法基础上,联用大黄虫丸。治疗前及治疗后(治疗1年)对比2组肝活检缓解率、肝纤维化扫描仪(FibroScan)测定的肝纤维化评级缓解率、中医证候积分、体质量指数及肝功能指标[血清谷丙转氨酶(GPT)、血清总胆红素(TB)、血清谷草转氨酶(GOT)]、血脂指标[总胆固醇(TC)、高密度脂蛋白胆固醇(HDL-C)、三酰甘油(TG)、低密度脂蛋白胆固醇(LDL-C)]、临床疗效及安全性。结果:观察组患者肝活检缓解率高于对照组(χ^(2)=14.512,P=0.002),肝纤维化评级改善率高于对照组(χ^(2)=15.550,P=0.001)。观察组临床中医证候总有效率高于对照组(χ^(2)=21.438,P<0.05)。治疗后,2组患者体质量指数及肝功能、血脂指标均较治疗前改善(P<0.05);治疗后,2组体质量指数及血脂指标比较差异无统计学意义(P>0.05),观察组肝功能指标(GPT、GOT、TB)低于对照组(P<0.05)。共发生不良事件37例次,均为轻微不良反应,未经处理或对症治疗后缓解,2组不良事件发生率比较差异无统计学意义(P>0.05)。结论:大黄■虫丸可改善NASH痰瘀互结证患者的肝纤维化、中医证候与肝功能,安全性良好。