Anti-Disturbance Control for Tethered Aircraft System With Deferred Output Constraints

In this paper,we investigate the peaking issue of extended state observers and the anti-disturbance control problem of tethered aircraft systems subject to the unstable flight of the main aircraft,airflow disturbances and deferred output constraints.Independent of exact initial values,a modified extended state observer is constructed from a shifting function such that not only the peaking issue inherently in the observer is circumvented completely but also the accurate estimation of the lumped disturbance is guaranteed.Meanwhile,to deal with deferred output constraints,an improved output constrained controller is employed by integrating the shifting function into the barrier Lyapunov function.Then,by combining the modified observer and the improved controller,an anti-disturbance control scheme is presented,which ensures that the outputs with any bounded initial conditions satisfy the constraints after a pre-specified finite time,and the tethered aircraft tracks the desired trajectory accurately.Finally,both a theoretical proof and simulation results verify the effectiveness of the proposed control scheme.

Adaptive Control Based on Neural Networks for an Uncertain 2-DOF Helicopter System With Input Deadzone and Output Constraints

In this paper, a study of control for an uncertain2-degree of freedom(DOF) helicopter system is given. The2-DOF helicopter is subject to input deadzone and output constraints. In order to cope with system uncertainties and input deadzone, the neural network technique is introduced because of its capability in approximation. In order to update the weights of the neural network, an adaptive control method is utilized to improve the system adaptability. Furthermore, the integral barrier Lyapunov function(IBLF) is adopt in control design to guarantee the condition of output constraints and boundedness of the corresponding tracking errors. The Lyapunov direct method is applied in the control design to analyze system stability and convergence. Finally, numerical simulations are conducted to prove the feasibility and effectiveness of the proposed control based on the model of Quanser's 2-DOF helicopter.

Adaptive neural tracking control for upper limb rehabilitation robot with output constraints

The authors investigate the trajectory tracking control problem of an upper limb reha-bilitation robot system with unknown dynamics.To address the system's uncertainties and improve the tracking accuracy of the rehabilitation robot,an adaptive neural full-state feedback control is proposed.The neural network is utilised to approximate the dy-namics that are not fully modelled and adapt to the interaction between the upper limb rehabilitation robot and the patient.By incorporating a high-gain observer,unmeasurable state information is integrated into the output feedback control.Taking into consider-ation the issue of joint position constraints during the actual rehabilitation training process,an adaptive neural full-state and output feedback control scheme with output constraint is further designed.From the perspective of safety in human–robot interaction during rehabilitation training,log-type barrier Lyapunov function is introduced in the output constraint controller to ensure that the output remains within the predefined constraint region.The stability of the closed-loop system is proved by Lyapunov stability theory.The effectiveness of the proposed control scheme is validated by applying it to an upper limb rehabilitation robot through simulations.

Dynamic Constraint-Driven Event-Triggered Control of Strict-Feedback Systems Without Max/Min Values on Irregular Constraints

This work proposes an event-triggered adaptive control approach for a class of uncertain nonlinear systems under irregular constraints.Unlike the constraints considered in most existing papers,here the external irregular constraints are considered and a constraints switching mechanism(CSM)is introduced to circumvent the difficulties arising from irregular output constraints.Based on the CSM,a new class of generalized barrier functions are constructed,which allows the control results to be independent of the maximum and minimum values(MMVs)of constraints and thus extends the existing results.Finally,we proposed a novel dynamic constraint-driven event-triggered strategy(DCDETS),under which the stress on signal transmission is reduced greatly and no constraints are violated by making a dynamic trade-off among system state,external constraints,and inter-execution intervals.It is proved that the system output is driven to close to the reference trajectory and the semi-global stability is guaranteed under the proposed control scheme,regardless of the external irregular output constraints.Simulation also verifies the effectiveness and benefits of the proposed method.

Adaptive neural network based boundary control of a flexible marine riser system with output constraints

In this study,we develop an adaptive neural network based boundary control method for a flexible marine riser system with unknown nonlinear disturbances and output constraints to suppress vibrations.We begin with describing the dynamic behavior of the riser system using a distributed parameter system with partial differential equations.To compensate for the effect of nonlinear disturbances,we construct a neural network based boundary controller using a radial basis neural network to reduce vibrations.Under the proposed boundary controller,the state of the riser is guaranteed to be uniformly bounded based on the Lyapunov method.The proposed methodology provides a way to integrate neural networks into boundary control for other flexible robotic manipulator systems.Finally,numerical simulations are given to demonstrate the effectiveness of the proposed control method.

Distributed disturbance-observer-based vibration control for a flexible-link manipulator with output constraints

The issue of output constraints is studied for a flexible-link manipulator in the presence of unknown spatially distributed disturbances. The manipulator can be taken as an Euler-Bernoulli beam and its dynamic is expressed by partial differential equations. On account of the uncertainty of disturbances, we present a disturbance observer to estimate infinite dimensional disturbances on the beam. The observer is proven exponentially stable. Considering the problem of output constraints in the practical engineering, we propose a novel distributed vibration controller based on the disturbance observer to fulfill the position regulation of the joint angle and suppress elastic deflections on the flexible link, while confining the regulating errors of output in a suitable scope that we can assign. The closed-loop system is demonstrated exponentially stable based on an integral-barrier Lyapunov function. Simulations validate the effectiveness of the design scheme.

Control of Nonlinear Systems with Output Tracking Error Constraints

A constructive method is presented to design controllers that force the output of nonlinear systems in a strict feedback form to track a bounded and sufficient smooth reference trajectory asymptotically.Under suitable condition with the initial output tracking error,the proposed controllers guarantee the output tracking error within a symmetric or an asymmetric pre-specified limit range,and boundedness of all signals of the closed loop system.A transformation is introduced to take care of the output tracking error constraint.Smooth and/or p-times differentiable step functions are proposed and incorporated in the output tracking error transformation to overcome difficulties due to the asymmetric limit range on the output tracking error.As a result,there are no switchings in the proposed controllers despite of the asymmetric limit range.

Establishment of Output Models and Constraints Analysis for Independent Wind/PV/Storage System

In remote areas far from the grid, wind/PV/storage generating system is relatively a good choice, whatever in resource configuration, performance or prices. For the independent hybrid power system, the output models of wind turbines, photovoltaic arrays and batteries are built in this paper, and based on the objectives of the capacity configuration optimal model, constraints used in the process of capacity configuration are analyzed. These provide convenient conditions and theoretical basis for the optimal capacity configuration of independent wind/PV/storage system.

考虑输出约束和输入饱和的弹仓自适应控制

针对存在参数不确定性和外部扰动的某链式回转弹仓的位置跟踪控制问题,提出一种自适应控制方案。该方案基于神经模糊系统(Neuro-Fuzzy System,NFS)、非线性扰动观测器(Nonlinear Disturbance Observer,NDO)及障碍Lyapunov函数(Barrier Lyapunov Function,BLF),在实现高精度控制的同时满足输出约束和输入饱和的工程条件。通过BLF的设计,保证弹仓的位移跟踪误差约束在给定范围内。结合神经网络的函数逼近能力和模糊逻辑系统的推理能力,用于估计系统中的不确定性,减小对模型的依赖;两者结合的NFS作为NDO的一部分,进一步补偿估计误差和外部扰动,提高控制性能。此外,控制器设计考虑了运动过程中的执行器输入饱和问题。仿真结果表明,所设计的控制器在3种典型工况以及系统参数变化情况下均可实现弹仓的高精度位置跟踪控制,满足系统的约束条件。

基于全驱系统方法的高阶严反馈系统时变输出约束控制

针对输出受不对称时变约束的不确定高阶严反馈系统,提出一种基于全驱系统方法的高阶自适应动态面输出约束控制方法.所研究的高阶严反馈系统,每个子系统都是高阶形式,通过非线性转换函数将原输出约束系统转换为新的无约束系统,从而将原系统输出约束问题转化为新系统输出有界的问题.进一步结合全驱系统方法和自适应动态面控制,直接将每个高阶子系统作为一个整体进行控制器设计,而不需要将其转化为一阶系统形式,有效简化了设计步骤;同时通过引入一系列低通滤波器来获得虚拟控制律的高阶导数,以代替复杂的微分运算.基于Lyapunov稳定性理论证明闭环系统所有信号是一致最终有界的,系统输出在满足约束的条件下能有效跟踪期望的参考信号,且可通过调整参数使得系统跟踪误差收敛到零附近的足够小的邻域内.最后,通过对柔性关节机械臂系统进行仿真,验证了所提出控制方法的有效性.

Adaptive Decentralized Output-Constrained Control of Single-Bus DC Microgrids

A single-bus DC microgrid can represent a wide range of applications. Control objectives of such systems include high-performance bus voltage regulation and proper load sharing among multiple distributed generators(DGs) under various operating conditions. This paper presents a novel decentralized control algorithm that can guarantee both the transient voltage control performance and realize the predefined load sharing percentages. First, the output-constrained control problem is transformed into an equivalent unconstrained one. Second, a two-step backstepping control algorithm is designed based on the transformed model for bus-voltage regulation. Since the overall control effort can be split proportionally and calculated with locally-measurable signals, decentralized load sharing can be realized. The control design requires neither accurate parameters of the output filters nor load measurement. The stability of the transformed systems under the proposed control algorithm can indirectly guarantee the transient bus voltage performance of the original system. Additionally, the high-performance control design is robust, flexible, and reliable. Switch-level simulations under both normal and fault operating conditions demonstrate the effectiveness of the proposed algorithm.

预设时间性能约束下高超声速飞行器的自适应容错控制

考虑输出误差约束、不确定和执行器故障影响下的高超声速飞行器的跟踪控制问题,提出自适应容错反步控制策略。首先,设计指数型预设时间性能函数,保证输出误差在预设时间内满足约束要求。其次,通过自适应律解决不确定项和升降舵故障。利用跟踪微分器解决“计算爆炸”问题,避免反步控制中对虚拟控制输入的高阶求导。最后,基于Lyapunov理论证明闭环系统的稳定性,并通过仿真验证所提控制策略的有效性。

一种无人机极点区域约束系统输出反馈滤波设计

针对参数变化引起的系统不稳定情况,研究其闭环极点处于区域约束下滤波问题,提出了基于输出反馈的滤波系统设计方法。在被控系统及反馈滤波系统同时存在不确定性的情况下,以线性矩阵不等式形式给出输出反馈滤波系统的可解性条件,使其闭环系统渐近稳定,滤波误差输出对干扰的抑制性能指标小于给定上界,并把闭环系统极点配置于复平面上指定区域。运用该方法对某型警用无人飞行器纵向运动进行仿真验证,闭环系统的极点均分布在预期界限,系统趋于稳定,达到了设计目标,表明了该方法的有效性。

考虑节能减排的分布式光伏储能容量配置研究

分布式光伏电源的工作时间、功耗都不相同,具有储能非正常损耗较快、不易大规模存储的特点。一旦分布式光伏储能节点的容量配置不合理,很容易造成能源浪费。为了使分布式电源持续稳定发挥作用,研究了考虑节能减排的分布式光伏储能容量配置方法。建立分布式光伏发电模型,获取分布式光伏电源的参数以及最大功率点输出功率,以此预测光伏发电量,为解决分布式光伏出力所存在的随机性和不确定性问题提供参考依据。通过估计分布式光伏储能容量,计算每日发电供应量和需求量的差值,并建立储能容量配置模型。以节能减排为目的设定约束条件以及目标函数,完成分布式光伏储能容量配置。经试验论证分析,分布式光伏储能容量估计值与实际值相差较小,结果可信度较高,能够为储能容量配置提供可靠依据。光伏储能的最大输出功率始终处于合理范围内,避免了过度的电量消耗。荷电状态(SOC)始终在有效区间内。全天充放电平衡满足约束条件。该方法达到了节能减排的目的,具有可靠性。

中国区域可持续创新效率影响因素

采用基于非期望产出的数据包络分析法(DEA),评估了中国30个省级行政区的可持续创新效率,进而通过Tobit回归研究了中国区域可持续创新效率的影响因素。结果表明:中国区域可持续创新效率整体偏低,但呈现缓慢上升的趋势;区域间的效率值差异较大,东部地区明显高于中部和西部地区;各因素对中国东中西部地区可持续创新效率影响的显著性差异较大,体现了不同区域创新系统的异质性。

输入时延下约束不确定系统的有限时间控制

针对一类具有非对称时变输出约束和输入时延的不确定非线性系统,提出有限时间反步控制策略.首先,设计新型非线性变换函数将约束系统转化为无约束系统,解决非对称时变输出约束问题;其次,为了处理反步控制的“计算爆炸”问题,构造新型的有限时间滤波器,且通过误差补偿机制消除滤波误差,采用Pade近似法和中间变量补偿输入时延对控制系统的影响;再次,根据Lyapunov理论证明闭环系统的实际有限时间稳定性,且输出不会违反约束;最后,通过滤波器的对比仿真和机械臂系统的仿真验证新型滤波器和有限时间控制策略的有效性.

中国制造业上市公司绿色创新投入与产出关系研究——基于融资约束和战略激进的调节作用

长期以来中国主要依靠丰富资源和大量廉价劳动力的双重优势取得了经济的飞速发展,但同时对整体资源环境也产生了极大的破坏,传统的“先污后治”模式已经成为中国经济发展的绊脚石。本文通过对2015—2020年制造业上市公司的面板数据进行调节效应以及门槛回归检验,探讨融资约束、战略激进对绿色创新投入和产出关系的作用。研究发现:绿色创新投入对绿色创新产出具有显著的正向影响;融资约束及战略激进对绿色创新投入和产出的关系均起到负向调节作用并存在门槛效应。据此,提出相关建议:企业应加大绿色创新活动投入,开展产学研合作,提升绿色创新转化能力;建立相应的融资管控机制,严格管控企业投资方向;制定适合本企业的科学战略,优化现有的企业战略。

具有输出/全状态约束的固定时间滑模控制

本文主要解决具有约束的二阶系统的固定时间跟踪控制问题,分别讨论了具有输出约束与具有全状态约束的控制算法设计.首先,为解决输出约束下的固定时间控制问题,本文构建了具有输出约束的新型终端滑模变量,并设计了具有扰动抑制能力的固定时间滑模控制律,保证系统输出始终满足约束条件,同时跟踪误差在固定时间内收敛到原点的充分小的邻域内.进一步,为了处理具有全状态约束的控制问题,本文构建了具有全状态约束的终端滑模变量并设计了相应的固定时间滑模控制律.鉴于系统控制律的不连续性,文章采用非光滑分析及Lyapunov稳定性理论证明了闭环控制系统的稳定性.最后,在数值仿真中,将本文提出的方法与传统固定时间滑模方法进行对比,验证了所建立算法的有效性.

面向输出约束基于神经网络观测器的发射平台输出反馈控制

一种由两台永磁同步电机驱动的发射平台用于发射动能载荷,但该平台在实际运行中经常面临比较强的参数不确定性和气流冲击等未知的外部干扰,大大降低其跟踪精度。针对这一问题,提出一种用于发射平台高精度运动控制的考虑输出约束的基于自适应神经网络观测器输出反馈控制器。该控制器采用扩展状态观测器估计系统中的参数不确定性,同时利用其观测的系统速度值设计相关控制量,从而达到输出反馈控制的目的;另外设计一种改进的样条小脑模型关节控制器神经网络(Spline CMAC)对系统中的未知扰动进行估计,由此利用前馈补偿技术对参数不确定性和时变扰动进行补偿。考虑到发射平台在实际情况中遇到的输出约束问题,采用障碍Lyapunov函数分析法设计控制率并证明了系统的稳定性。仿真和实验结果表明:在考虑输出约束的条件下,新的复合控制器能够实现系统的一致最终有界稳定,且跟踪性能很好,并具有很强的抗干扰能力,相比于传统的控制方法有很大的提升。

考虑时变输出受限的机械臂自适应容错控制

针对机械臂执行器失效故障,提出了一种基于障碍李雅普诺夫函数的有限时间模糊自适应容错控制方法。该控制方法引入自适应技术用于估计执行器的失效程度,补偿执行器故障带来的损失,保证了控制器的控制效果,并采用模糊逻辑系统使得控制律中无须模型参数,从而增加了控制系统的适用性。该控制方法能够保证闭环系统的所有信号和状态是有限时间有界,关节位置的跟踪误差收敛到原点的一个小邻域内,在机械臂运行过程中不违反时变约束要求。最后,将所提控制方法应用于二自由度刚性机械臂,仿真结果验证了所提控制方法的有效性。