Observer-based robust high-order fully actuated attitude autopilot design for spinning glide-guided projectiles

This paper investigates the design of an attitude autopilot for a dual-channel controlled spinning glideguided projectile(SGGP),addressing model uncertainties and external disturbances.Based on fixed-time stable theory,a disturbance observer with integral sliding mode and adaptive techniques is proposed to mitigate total disturbance effects,irrespective of initial conditions.By introducing an error integral signal,the dynamics of the SGGP are transformed into two separate second-order fully actuated systems.Subsequently,employing the high-order fully actuated approach and a parametric approach,the nonlinear dynamics of the SGGP are recast into a constant linear closed-loop system,ensuring that the projectile's attitude asymptotically tracks the given goal with the desired eigenstructure.Under the proposed composite control framework,the ultimately uniformly bounded stability of the closed-loop system is rigorously demonstrated via the Lyapunov method.Validation of the effectiveness of the proposed attitude autopilot design is provided through extensive numerical simulations.

Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

Fuel recycling feedback control via real-time boron powder injection in EAST with full metal wall

A feedback control of fuel recycling via real-time boron powder injection,addressing the issue of continuously increasing recycling in long-pulse plasma discharges,has been successfully developed and implemented on EAST tokamak.The feedback control system includes four main parts:the impurity powder dropper(IPD),a diagnostic system measuring fuel recycling level represented by D_(α)emission,a plasma control system(PCS)implementing the Proportional Integral Derivative(PID)algorithm,and a signal converter connecting the IPD and PCS.Based on this control system,both active control and feedback control experiments have recently been performed on EAST with a full metal wall.The experimental results show that the fuel recycling can be gradually reduced to lower level as PCS control voltage increases.In the feedback control experiments,it is also observed that the D_(α)emission is reduced to the level below the target D_(α)value by adjusting boron injection flow rate,indicating successful implementation of the fuel recycling feedback control on EAST.This technique provides a new method for fuel recycling control of long pulse and high parameter plasma operations in future fusion devices.

Not in Control,but Liable?Attributing Human Responsibility for Fully Automated Vehicle Accidents

Human agency has become increasingly limited in complex systems with increasingly automated decision-making capabilities.For instance,human occupants are passengers and do not have direct vehicle control in fully automated cars(i.e.,driverless cars).An interesting question is whether users are responsible for the accidents of these cars.Normative ethical and legal analyses frequently argue that individuals should not bear responsibility for harm beyond their control.Here,we consider human judgment of responsibility for accidents involving fully automated cars through three studies with seven experiments(N=2668).We compared the responsibility attributed to the occupants in three conditions:an owner in his private fully automated car,a passenger in a driverless robotaxi,and a passenger in a conventional taxi,where none of these three occupants have direct vehicle control over the involved vehicles that cause identical pedestrian injury.In contrast to normative analyses,we show that the occupants of driverless cars(private cars and robotaxis)are attributed more responsibility than conventional taxi passengers.This dilemma is robust across different contexts(e.g.,participants from China vs the Republic of Korea,participants with first-vs third-person perspectives,and occupant presence vs absence).Furthermore,we observe that this is not due to the perception that these occupants have greater control over driving but because they are more expected to foresee the potential consequences of using driverless cars.Our findings suggest that when driverless vehicles(private cars and taxis)cause harm,their users may face more social pressure,which public discourse and legal regulations should manage appropriately.

Bifurcation analysis and control study of improved full-speed differential model in connected vehicle environment

In recent years, the traffic congestion problem has become more and more serious, and the research on traffic system control has become a new hot spot. Studying the bifurcation characteristics of traffic flow systems and designing control schemes for unstable pivots can alleviate the traffic congestion problem from a new perspective. In this work, the full-speed differential model considering the vehicle network environment is improved in order to adjust the traffic flow from the perspective of bifurcation control, the existence conditions of Hopf bifurcation and saddle-node bifurcation in the model are proved theoretically, and the stability mutation point for the stability of the transportation system is found. For the unstable bifurcation point, a nonlinear system feedback controller is designed by using Chebyshev polynomial approximation and stochastic feedback control method. The advancement, postponement, and elimination of Hopf bifurcation are achieved without changing the system equilibrium point, and the mutation behavior of the transportation system is controlled so as to alleviate the traffic congestion. The changes in the stability of complex traffic systems are explained through the bifurcation analysis, which can better capture the characteristics of the traffic flow. By adjusting the control parameters in the feedback controllers, the influence of the boundary conditions on the stability of the traffic system is adequately described, and the effects of the unstable focuses and saddle points on the system are suppressed to slow down the traffic flow. In addition, the unstable bifurcation points can be eliminated and the Hopf bifurcation can be controlled to advance, delay, and disappear,so as to realize the control of the stability behavior of the traffic system, which can help to alleviate the traffic congestion and describe the actual traffic phenomena as well.

Cooperative Rate Splitting Transmit Design for Full-Duplex-Enabled Multiple Multicast Communication Systems

This paper examines the performance of Full-Duplex Cooperative Rate Splitting(FD-CRS)with Simultaneous Wireless Information and Power Transfer(SWIPT)support in Multiple Input Single Output(MISO)networks.In a Rate Splitting Multiple Access(RSMA)multicast system with two local users and one remote user,the common data stream contains the needs of all users,and all users can decode the common data stream.Therefore,each user can receive some information that other users need,and local users with better channel conditions can use this information to further enhance the reception reliability and data rate of users with poor channel quality.Even using Cell-Center-Users(CCUs)as a cooperative relay to assist the transmission of common data can improve the average system speed.To maximize the minimum achievable rate,we optimize the beamforming vector of Base Station(BS),the common streamsplitting vector,the cooperative distributed beamvector and the strong user transmission power under the power budget constraints of BS and relay devices and the service quality requirements constraints of users.Since the whole problem is not convex,we cannot solve it directly.Therefore,we propose a low complexity algorithm based on Successive Convex Approximation(SCA)technology to find the optimal solution to the problemunder consideration.The simulation results show that FD C-RSMA has better gain andmore powerful than FD C-NOMA,HD C-RSMA,RSMA and NOMA.

Target Controllability of Multi-Layer Networks With High-Dimensional Nodes

This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion.

Exact controllability of rational expectations model with multiplicative noise and input delay

This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.

双PWM变流器飞轮系统母线电压LADRC二次控制策略

提出一种基于二阶线性自抗扰控制(LADRC)的飞轮储能系统直流母线电压二次控制策略来应对飞轮储能系统频繁充放电切换带来的母线电压波动问题,其将母线电压及微分值分别视为状态变量,负载功率、参数不确定性等内外干扰视为扩展状态量进行扰动观测器设计。该策略能将工况切换造成电压波动的观测扰动量实时补偿至控制量中,实现扰动补偿。加入二次控制解决LADRC面对非常值扰动会存在稳态误差的问题,保证飞轮储能系统在充放能切换过程中母线电压具备较好的快速响应和抗干扰性能的同时实现无差控制。最后通过仿真验证了所提策略的有效性。

未知环境中基于控制障碍函数的机器人安全控制研究综述

随着机器人系统工作环境的复杂程度日益增加,以及对实时性需求的逐步提升,机器人的安全避障能力将面临新的挑战,控制障碍函数作为一种基于控制器的安全方法在机器人安全控制系统中迎来新的发展契机。调研分析了控制障碍函数及基于二次规划的优化控制器,总结了机器人在已知和未知环境中的避障问题,综述了高斯过程和强化学习两种理论合成控制障碍函数的策略。最后,讨论了未来基于控制障碍函数的空地协同机器人安全控制需要重点关注的问题,为未来控制障碍函数的理论研究和技术应用提供了参考。

线性Markov跳变随机系统的Pareto最优控制

目前针对多个主体、多个目标的带有Markov跳变的线性随机系统的控制问题的研究较少且较为浅显.本文研究了具有乘性噪声的连续时间线性Markov跳变随机系统的Pareto最优控制问题.假设多个主体、多个性能指标由状态和控制变量中的二次部分和线性部分的线性组合而形成,证明了Pareto最优与加权和优化之间的关系,从而将多目标优化问题转化为特殊的单目标加权和最优控制问题.基于Pareto博弈理论与广义Itô公式,系统的Pareto有效策略可以通过一组耦合的广义Riccati微分方程与一组耦合的线性微分方程求解,并且可以得到每一个控制器的Pareto解.最后,本文通过数值仿真验证理论结果的有效性.

基于最优阻抗选取的机器人自适应鲁棒导纳控制

本文提出了一种基于最优阻抗选择的机器人自适应鲁棒导纳控制策略,以提高机器人与环境交互的性能.本文的创新点包括:1)提出了一种新的环境阻抗复合学习估计方法,保证阻抗参数估计值约束在预定的集合内,通过初始激励保证了估计误差的指数收敛性;2)基于估计的环境阻抗,设计机器人期望的最优刚度和阻尼,实现交互力和轨迹跟踪误差的最优协调;3)设计了一种基于时滞估计的自适应鲁棒导纳控制器,使机器人能够以规定的性能跟踪导纳轨迹.在自适应鲁棒控制器中,采用饱和函数来代替传统的滑模控制,极大地缓解了可能出现的抖振问题.通过对比仿真验证了本文环境阻抗估计方法和自适应鲁棒导纳控制的有效性.

基于改进虚拟振荡器和滑模控制的光储微电网控制策略

针对下垂控制模式下的光储微电网动态响应性能较差、受外界扰动时超调量较大的问题。文章提出了一种基于改进虚拟振荡器控制和滑模控制的光储微电网控制策略。光储微电网中光伏系统采用两级式结构,前级DC-DC变换器采用滑模控制,以增强微电网对外部干扰的鲁棒性;后级逆变器采用引入最大功率点追踪算法的虚拟振荡器控制,使光伏电池实现最大功率点追踪控制,提高了微电网的动态响应速度。储能系统逆变器采用虚拟惯性的虚拟振荡器控制,将惯量及阻尼特性引入虚拟振荡器控制中,为光储微电网提供可靠的功率和频率支撑。最后,基于Matlab/Simulink平台搭建了光储微电网的仿真模型,与传统下垂控制策略的仿真结果进行对比,验证了本文所提控制策略的可行性及有效性。

陆相层序地层构型与沉积模拟研究现状及进展

层序地层学作为一种新的盆地分析方法,受到广大地质学家的重视,尤其是陆相层序构型与数值模拟研究已成为一个国际性热门方向。文中总结了陆相层序构型在国内外的研究进展,介绍了国外近年来的“下游控制区”和“上游控制区”概念以及层序构型特征,“下游控制区”发育依赖于相对海(湖)平面变化的“低位正常海(湖)退”、“海(湖)侵”、“高位正常海(湖)退”和“下降阶段”体系域,“上游控制区”发育不依赖相对海(湖)平面变化的高河道合并体系域和低河道合并体系域。国内层序构型研究也有多种观点,最有代表性的应该是“L型、T型、TH型、H型(E-H型和L-H型)”层序构型的划分。陆相层序模拟已经从水槽物理实验为主发展到当今以数值模拟及水槽实验并举的时代。在介绍层序数值模拟发展史、国内外研究现状的基础上,重点介绍了SEDPAK正演化模拟、SEDSIM正演数值模拟、基于Delft3D模型的三维正演模拟、DIONISOS的三维正演模拟及基于N-S方程的层序数值模拟等5种数值模拟方法,总结了陆相湖盆层序构型及数值模拟在油气勘探开发领域的应用情况,分析了目前存在的理论问题、数值模拟技术难点及数值模拟未来的发展方向。

城市过饱和区域积分终端滑模控制算法

【目标】现有基于滑模变结构的区域边界控制算法存在明显缺陷,即系统状态需要在时间趋于无穷大时才能收敛到平衡点,仅能保证系统的渐进稳定。这显然无法满足现代城市交通管理对于快速响应和高效调控的需求。为克服该局限,提出一种基于宏观基本图和积分终端滑模的区域边界控制算法,获得较快的收敛速度以及较好的鲁棒性和扰动抑制特性。【方法】首先,将干扰(非门控或区域内部交通量)和宏观基本图建模中的不确定性视为集总干扰,建立城市过饱和区域边界控制系统模型。在此基础上,引入非线性积分终端滑动超平面,设计一种基于积分终端滑模的边界控制算法。【结果】将所提方法应用于5×5均匀棋盘路网中,路网累积空间交通流量有超过1%的提升,部分算例中接近5%;平均速度有超过5%的提升,部分算例中超过8%。所提出算法具有较快的收敛速度和较好的扰动抑制能力,能显著提升路网累计吞吐量和路网中车辆平均速度,缓解过饱和区域交通拥堵。【结论】相较于既有滑模变结构边界控制算法,所提出算法采用非线性积分终端滑动超平面,能保证受控路网状态在预设有限时间内收敛到期望状态;相较于既有比例积分控制策略,能更好处理受控路网中非常值干扰交通需求和宏观基本图建模中存在的低离散度。

港口重载AGV转向稳定性容错控制策略

针对四轮独立驱动与转向(4WID-4WIS)型港口重载自动导引车(AGV)常见的驱动电机失效情况,提出了三层控制结构的容错控制策略来进行转向稳定性容错控制。上层控制模块设计为模型预测控制器(MPC)与PI车速跟随控制器,实现港口AGV的路径跟踪;中层控制模块设计为横摆角速度、质心侧偏角RBF神经网络鲁棒滑模控制器,用来计算出最佳附加横摆力矩;下层控制模块设计为失效分配策略,对力矩进行重新分配。最后,搭建了CarMaker测试平台,通过实验验证了容错控制策略的有效性与优越性。

模块化多电平矩阵换流器的等值阻抗模型解析分析

模块化多电平矩阵换流器(M3C)的阻抗建模是柔性低频输电系统稳定性分析和故障特性分析的关键理论基础。介绍了M3C的拓扑结构、数学模型与控制策略。在此基础上,分析了计及M3C拓扑结构特点、dq坐标变换过程和双dq分解控制的扰动电流-桥臂电压-扰动电压传递响应特性,推导了M3C等值阻抗特性与频率的关系,建立了可用固定电阻与随频率变化电抗串联表示的M3C等值阻抗数学模型。在PSCAD/EMTDC仿真平台上利用扫频法对等值阻抗理论分析的准确性进行验证,并讨论了系统控制参数、运行功率、一次参数等不同因素对M3C阻抗频率特性的影响。

基于模型预测控制的无人车编队避障方法

为研究障碍物环境下基于模型预测控制的无人车编队避障方法,建立了包含虚拟智能体状态的编队避障函数,使避障问题容易用优化方法求解.在无人车编队内部引入优先级策略实现编队内部避碰,并通过动态事件触发机制减小无人车之间通讯带宽占用.对该方法进行了计算机仿真验证,在给定多边形障碍物环境下,使用领导者-追随者架构执行编队行驶任务,并借助事件触发器实现间歇通讯.结果表明,相较于传统方法,所设计的编队控制器能够提高带宽约束下无人车编队行驶安全性.

基于模糊PID控制的拖拉机遥控转向系统研究

由于拖拉机实际作业环境较为恶劣,为保证驾驶员的安全,提出了一种拖拉机遥控转向系统的设计方案。首先,对拖拉机现有的液压转向系统进行了分析,并提出了遥控转向系统的结构设计和控制策略设计;然后,通过AMEsim和Simulink分别搭建了遥控转向系统的液压部分模型和模糊PID控制器并进行了联合仿真实验。实验结果表明:设计的遥控转向系统能够实现拖拉机的转向,模糊PID控制器相对于常规PID控制器的控制效果更好,阶跃响应时间由1.49 s缩短到1.07 s,正弦跟踪响应最大误差由0.028 m缩短到0.015 m,抗干扰性也更强。

基于PID切换控制的弹道修正引信滚转角控制方法

为解决弹道修正引信在修正过程中弹体受力变化较大引起的模型非线性问题,为保证滚转角控制算法的有效控制范围可有效覆盖整个修正控制过程,采用了基于动压变化的位置-速度双闭环比例-积分-微分(proportional-integral-differential,PID)切换控制算法.在传统PID控制算法基础上引入切换控制,将PID控制系统设计成子系统,依靠引信动力学模型与动压之间的关联,以动压为切换信号制定切换规则将多个PID控制系统串联,拓宽了滚转角控制系统的有效控制范围.结合理论分析与仿真验证,结果表明:在整个弹道修正控制过程中定位精度在0.25°以内,响应时间小于0.3 s,验证了基于动压变化的PID切换控制算法对非线性的引信滚转角控制模型、持续滚转角控制的可行性.