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.

Trajectory tracking guidance of interceptor via prescribed performance integral sliding mode with neural network disturbance observer

This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance systems of missiles is challenging.As our contribution,the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy.The global prescribed performance function,which guarantees the tracking error within the set range and the global convergence of the tracking guidance system,is first proposed based on the traditional PPF.Then,a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities.Meanwhile,an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem.A back propagation neural network(BPNN)extended state observer(BPNNESO)is employed in the inner loop to identify disturbances.The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors,convergence times,and overshoots.

Observer-Based Adaptive Robust Precision Motion Control of a Multi-Joint Hydraulic Manipulator

Hydraulic manipulators are usually applied in heavy-load and harsh operation tasks.However,when faced with a complex operation,the traditional proportional-integral-derivative(PID)control may not meet requirements for high control performance.Model-based full-state-feedback control is an effective alternative,but the states of a hydraulic manipulator are not always available and reliable in practical applications,particularly the joint angular velocity measurement.Considering that it is not suitable to obtain the velocity signal directly from differentiating of position measurement,the low-pass filtering is commonly used,but it will definitely restrict the closed-loop bandwidth of the whole system.To avoid this problem and realize better control performance,this paper proposes a novel observerbased adaptive robust controller(obARC)for a multi-joint hydraulic manipulator subjected to both parametric uncertainties and the lack of accurate velocity measurement.Specifically,a nonlinear adaptive observer is first designed to handle the lack of velocity measurement with the consideration of parametric uncertainties.Then,the adaptive robust control is developed to compensate for the dynamic uncertainties,and the close-loop system robust stability is theoretically proved under the observation and control errors.Finally,comparative experiments are carried out to show that the designed controller can achieve a performance improvement over the traditional methods,specifically yielding better control accuracy owing to the closed-loop bandwidth breakthrough,which is limited by low-pass filtering in fullstate-feedback control.

Disturbance Observer-Based Predictive Tracking Control of Uncertain HOFA Cyber-Physical Systems

Dear Editor,In this letter,an output tracking control problem of uncertain cyber-physical systems(CPSs)is considered in the perspective of high-order fully actuated(HOFA)system theory,where a lumped disturbance is used to denote the total uncertainties containing parameters perturbations and external disturbances.

Quantum Realities and Observer-Dependent Universes: An Advanced Observer Model

This paper presents a novel observer model that integrates quantum mechanics, relativity, idealism, and the simulation hypothesis to explain the quantum nature of the universe. The model posits a central server transmitting multi-media frames to create observer-dependent realities. Key aspects include deriving frame rates, defining quantum reality, and establishing hierarchical observer structures. The model’s impact on quantum information theory and philosophical interpretations of reality are examined, with detailed discussions on information loss and recursive frame transmission in the appendices.

A Novel Disturbance Observer Based Fixed-Time Sliding Mode Control for Robotic Manipulators With Global Fast Convergence

This paper proposes a new global fixed-time sliding mode control strategy for the trajectory tracking control of uncertain robotic manipulators.First,a fixed-time disturbance observer(FTDO) is designed to deal with the adverse effects of model uncertainties and external disturbances in the manipulator systems.Then an adaptive scheme is used and the adaptive FTDO(AFTDO) is developed,so that the priori knowledge of the lumped disturbance is not required.Further,a new non-singular fast terminal sliding mode(NFTSM) surface is designed by using an arctan function,which helps to overcome the singularity problem and enhance the robustness of the system.Based on the estimation of the lumped disturbance by the AFTDO,a fixed-time non-singular fast terminal sliding mode controller(FTNFTSMC)is developed to guarantee the trajectory tracking errors converge to zero within a fixed time.The settling time is independent of the initial state of the system.In addition,the stability of the AFTDO and FTNFTSMC is strictly proved by using Lyapunov method.Finally,the fixed-time NFESM(FTNFTSM) algorithm is validated on a 2-link manipulator and comparisons with other existing sliding mode controllers(SMCs) are performed.The comparative results confirm that the FTNFTSMC has superior control performance.

Data-Driven Modeling of Partially Observed Biological Systems

We present a numerical approach for modeling unknown dynamical systems using partially observed data,with a focus on biological systems with(relatively)complex dynamical behavior.As an extension of the recently developed deep neural network(DNN)learning methods,our approach is particularly suitable for practical situations when(i)measurement data are available for only a subset of the state variables,and(ii)the system parameters cannot be observed or measured at all.We demonstrate that,with a properly designed DNN structure with memory terms,effective DNN models can be learned from such partially observed data containing hidden parameters.The learned DNN model serves as an accurate predictive tool for system analysis.Through a few representative biological problems,we demonstrate that such DNN models can capture qualitative dynamical behavior changes in the system,such as bifurcations,even when the parameters controlling such behavior changes are completely unknown throughout not only the model learning process but also the system prediction process.The learned DNN model effectively creates a“closed”model involving only the observables when such a closed-form model does not exist mathematically.

The First Global Map of Atmospheric Ammonia(NH_(3)) as Observed by the HIRAS/FY-3D Satellite

Atmospheric ammonia(NH_(3)) is a chemically active trace gas that plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH_(3) concentration based on the absorption lines of NH_(3) in the thermal infrared region. In this study, we establish a retrieval algorithm to derive the NH_(3)column from the Hyperspectral Infrared Atmospheric Sounder(HIRAS) onboard the Chinese Feng Yun(FY)-3D satellite and present the first atmospheric NH_(3) column global map observed by the HIRAS instrument. The HIRAS observations can well capture NH_(3) hotspots around the world, e.g., India, West Africa, and East China, where large NH_(3) emissions exist. The HIRAS NH_(3) columns are also compared to the space-based Infrared Atmospheric Sounding Interferometer(IASI)measurements, and we find that the two instruments observe a consistent NH_(3) global distribution, with correlation coefficient(R) values of 0.28–0.73. Finally, some remaining issues about the HIRAS NH_(3) retrieval are discussed.

Reduced-Order Observer-Based LQR Controller Design for Rotary Inverted Pendulum

The Rotary Inverted Pendulum(RIP)is a widely used underactuated mechanical system in various applications such as bipedal robots and skyscraper stabilization where attitude control presents a significant challenge.Despite the implementation of various control strategies to maintain equilibrium,optimally tuning control gains to effectively mitigate uncertain nonlinearities in system dynamics remains elusive.Existing methods frequently rely on extensive experimental data or the designer’s expertise,presenting a notable drawback.This paper proposes a novel tracking control approach for RIP,utilizing a Linear Quadratic Regulator(LQR)in combination with a reduced-order observer.Initially,the RIP system is mathematically modeled using the Newton-Euler-Lagrange method.Subsequently,a composite controller is devised that integrates an LQR for generating nominal control signals and a reduced-order observer for reconstructing unmeasured states.This approach enhances the controller’s robustness by eliminating differential terms from the observer,thereby attenuating unknown disturbances.Thorough numerical simulations and experimental evaluations demonstrate the system’s capability to maintain balance below50Hz and achieve precise tracking below1.4 rad,validating the effectiveness of the proposed control scheme.

Observer Based Control for a Class of Systems with Output Deadzone Nonlinearity

In this paper, a combination of model based adaptive design along with adaptive linear output feedback controller is used to compensate for robotic manipulator with output deadzone nonlinearity. The deadzone dynamics are utilized to adaptively estimate the deadzone parameter and a switching function is designed to eliminate the error produced in the adaptive observer dynamics. The overall design of the closed loop system ensures stability in the BIBO criterion.

Mini-CEX联合DOPS评价体系在牙体牙髓病学临床教学中的应用研究

目的:研究联合应用迷你临床演练评估(mini-clinical evaluation exercise,Mini-CEX)与诊疗技能直接观察法(direct observation of procedural skills,DOPS)评估量表在口腔医学专业本科生牙体牙髓病学临床实习教学中的应用效果。方法:对60名在牙体牙髓科实习的口腔医学专业本科生分别在实习开始(0个月)、实习中期(1个月)和实习结束(3个月)时采用Mini-CEX评测量表评测综合病例诊治能力,DOPS量表测评窝洞制备、橡皮障隔离、开髓术等基本临床技能操作并行统计学分析。结果:共完成Mini-CEX量表评测180次,DOPS量表评测540次。随着实习阶段的进展,两种量表的得分均逐步提高,差异有统计学意义(P<0.05)。结论:联合应用Mini-CEX与DOPS评估方法能够有效促进实习医师临床实践能力的培养,值得在牙体牙髓病学的本科临床实习教学中推广。

改良Peyton四步教学法联合DOPS在西藏临床技能培训中的应用

目的探讨基于改良Peyton四步教学法的模拟教学联合操作技能直接观察(direct observation of procedural skills,DOPS)评估方法在西藏临床技能培训中的应用效果。方法选取西藏边坝县人民医院2021年5月—2022年5月参加临床技能培训的51名医护人员为研究对象,随机分为试验组与对照组。试验组采用结合改良Peyton四步教学法进行成人男性导尿术教学,并在培训开始前、培训中期及培训结束后,由带教教师采用DOPS评估方法对学员进行测评。对照组采用传统临床技能培训方法进行教学。在培训结束后发放满意度调查问卷,以了解学员对该教学模式的满意度。结果试验组技能考核平均成绩(90.12±5.50)分,对照组技能考核平均成绩(79.36±6.95)分,两组间成绩比较,其差异具有统计学意义(P<0.001);DOPS评估量表显示,试验组学员在培训结束后临床操作各项能力均较前有显著提高,其差异均具有统计学意义(P<0.05);课后满意度调查结果显示,在赞同“增强相关基础知识”等6个方面,试验组与对照组比较,其差异均具有统计学意义(P<0.001)。结论基于改良Peyton四步教学法的模拟教学联合DOPS评估方法的教学模式可提高西藏藏区医护人员的临床技能操作水平,适合在藏区医护人员临床技能培训中推广。

改进STSMO的PMSM无传感器直接转矩控制系统

为提高滑模观测器转子位置观测精度,抑制抖振频发,提出了一种基于超螺旋滑模观测器(STSMO)的双重滤波直接转矩(DTC)控制方法。传统滑模观测器为了提取连续的扩展反电动势估计值,通常需要外加一个低通滤波器滤除高频信号,采用STSMO来提取反电动势,在低通滤波器前提下增加了卡尔曼滤波器,形成双重滤波结构,进一步滤除噪声和干扰信号,减小估算反电动势中的纹波,同时用饱和函数替代原有的符号函数以减小抖振。实验和仿真结果证明,改进STSMO控制系统能有效抑制系统抖振,具有更好的控制精度和稳态品质。

内科专业住院医师规范化培训指导医师线上DOPS培训的效果研究

目的探讨线上工作坊模式对内科专业住院医师规范化培训(简称住培)指导医师临床操作技能直接观察评估(direct observation of procedural skills,DOPS)师资培训的应用效果。方法选取2022年11月参加广东省内科专业住培普通师资培训班的45名指导医师为研究对象,采用线上分组讨论与教学视频评价反馈相结合的线上工作坊模式进行DOPS师资培训,采用问卷自评的方式评价指导医师对DOPS的掌握程度,并通过问卷调查了解培训前后指导医师对线上DOPS的培训需求与满意度。结果培训前仅17.8%的指导医师使用过DOPS量表;指导医师在培训后对DOPS的掌握程度明显高于培训前[(3.71±0.69)分比(2.29±0.87)分,P<0.01];且95.6%及以上的指导医师表示能够理解“DOPS评分项目的均质化制定方法”和“形成性反馈技巧”;100.0%的指导医师表示在今后住培教学中愿意尝试使用DOPS。课程的整体满意度评分为(8.40±1.70)分。结论线上工作坊模式对内科专业住培指导医师DOPS师资培训的短期效果满意,可进一步在住培形成性评价师资培训中推广应用。

ESPON实践及其对CSPON建设的启示

国土空间规划实施监测网络(CSPON)是建立健全国土空间实施监督体系的重要载体,对推动国土空间数字化发展及提升国土空间现代化治理水平具有重要意义。欧洲空间监测网络(ESPON)为欧洲空间规划和政策的制定提供了坚实的技术支撑,其实践经验对我国CSPON建设具有重要借鉴意义。文章首先比较分析ESPON 2006、ESPON 2013、ESPON 2020、ESPON 2030计划在实施背景、主要目标和核心内容等方面的差异和联系;然后从目标内涵、组织模式、功能结构和监测系统四个维度深入解析ESPON的特点;最后结合我国当前国土空间规划实施监测的实际需求,参考ESPON的实施背景、演进逻辑和系统特征,提出CSPON的建设应服务支撑国家重大战略、政策导向和规划需求,构建多主体参与、共建共享的组织模式,完善全域、全要素、多目标、多场景的功能结构,创新动态、公开、可比较、有前瞻性的数智化监测系统。

Mini-CEX结合DOPS教学在产科护理教学中的应用

目的探讨对于产科护理实习生的教学工作,采用迷你临床演练评估(mini-clinical exercise evaluation,Mini-CEX)、操作技能直接观察评估(direct observation of procedural skills,DOPS)教学的应用效果。方法选择2022年2—12月接收的112名产科护理实习生,按随机数字表法分为研究组和对照组,每组56名。对照组采取常规护理教学方式,研究组采取Mini-CEX结合DOPS教学,经过2个月实习,对2组实习生进行Mini-CEX考核和DOPS考核,并且应用自制的满意度问卷来调查实习生的意见,评价教学满意度情况。结果研究组的产科护理实习生Mini-CEX考核的各项分值高于对照组,差异有统计学意义(P<0.001);研究组产科护理实习生的DOPS考核总分[(90.12±3.26)分]高于对照组DOPS考核总分[(81.15±3.12)分],差异有统计学意义(P<0.001);研究组的产科实习生满意度(94.64%)高于对照组满意度(78.57%),差异有统计学意义(P<0.05)。结论产科护理教学中应用Mini-CEX结合DOPS教学的效果满意,可提高实习生的满意度。

以DOPS为工具的形成性评价在免疫检验实习带教中的效果

目的探讨以操作技能直接观察评估(DOPS)为工具的形成性评价在免疫检验实习带教中的效果。方法选取2022年度和2023年度在浙江大学医学院附属第一医院免疫检验科实习的同学,2022年度的45名实习同学为对照组,2023年度的34名实习同学为实验组,对照组的同学在实习过程中使用传统教学终结性评价方法,实验组同学实习中使用以DOPS量表为工具的形成性评价方法。分析比较两组实习同学的出科考核成绩、教学的效果、实习收获调查、满意度调查。结果实验组的理论成绩和操作考核成绩明显高于对照组,差异均有统计学意义(t分别=-3.26、-4.31,P均<0.05);实验组的教学效果明显优于对照组,差异均有统计学意义(t分别=-6.31、-13.03、-12.01、-7.82、-10.22、-11.11,P均<0.05);实验组的实习收获评分高于对照组,差异均有统计学意义(t分别=-9.31、-8.33、-9.21、-7.76、-5.93,P均<0.05);实验组的满意度高于对照组。结论应用DOPS作为形成性评价工具能够帮助学生更好地掌握技能,带教老师也可以从中获得教学过程中的持续反馈,从而进一步提升免疫检验实习带教的效果和质量。

基于对数型障碍Lyapunov函数的俯仰驾驶仪设计

相控阵雷达制导拦截弹在拦截高速大机动目标时,弹体气动参数剧烈非线性变化影响控制系统对大攻角的响应效果,应设计考虑攻角指令跟踪误差约束的鲁棒自动驾驶仪控制律。基于双幂次趋近律和对数型障碍李雅普诺夫函数设计了鲁棒非线性自动驾驶仪控制律,可将攻角指令的跟踪误差快速收敛于约束范围内。通过降阶扩张状态观测器对系统中存在的气动参数不确定性和系统外部扰动进行在线估计和补偿。稳定性分析和数值仿真表明,攻角可在1 s内达到稳态且攻角响应的稳态误差<10-4°,所提出的自动驾驶仪控制律具有较强的鲁棒性,能够准确稳定地跟踪攻角指令,控制导弹产生所需过载进而精准拦截目标。

基于ESO分数阶滑模调节的PMSM模型预测转矩控制

为了提高永磁同步电机调速系统的性能,提出一种基于扩张状态观测器的分数阶滑模预测转矩控制策略。采用扩张状态观测器对电机的综合扰动项、定子电流和反电动势进行实时观测,可快速准确得到它们的估计值并进行补偿;利用估计值构建分数阶滑模控制器来削弱系统抖振并提高鲁棒性;利用转矩和磁链无差拍预测控制,减少了遍历次数并降低了计算复杂度。通过仿真和半实物平台进行了验证,所得结果表明,所提出的方法能有效提升系统的鲁棒性,使电机具有良好的动态和静态性能。

Mini-CEX联合DOPS在疼痛科住院医师规范化培训中的应用

目的:探讨迷你临床演练评估体系(Mini-CEX)和操作技能直接观察评估体系(DOPS)在疼痛科住院医师规范化培训中的应用效果。方法:将32名住院医师随机分为试验组和对照组,分别采用Mini-CEX联合DOPS教学法和传统教学法进行带教,比较两组住院医师的出科考试成绩。结果:试验组Mini-CEX和DOPS成绩较入科时均显著提升,出科考试成绩明显高于对照组(P<0.05)。结论:在疼痛科住院医师规范化培训中应用Mini-CEX联合DOPS可以显著提高带教效果。