Distributed Adaptive Output Consensus of Unknown Heterogeneous Non-Minimum Phase Multi-Agent Systems

This article addresses the leader-following output consensus problem of heterogeneous linear multi-agent systems with unknown agent parameters under directed graphs.The dynamics of followers are allowed to be non-minimum phase with unknown arbitrary individual relative degrees.This is contrary to many existing works on distributed adaptive control schemes where agent dynamics are required to be minimum phase and often of the same relative degree.A distributed adaptive pole placement control scheme is developed,which consists of a distributed observer and an adaptive pole placement control law.It is shown that under the proposed distributed adaptive control scheme,all signals in the closed-loop system are bounded and the outputs of all the followers track the output of the leader asymptotically.The effectiveness of the proposed scheme is demonstrated by one practical example and one numerical example.

Output-feedback Dynamic Surface Control for a Class of Nonlinear Non-minimum Phase Systems

In this paper, an output-feedback tracking controller is proposed for a class of nonlinear non-minimum phase systems.To keep the unstable internal dynamics bounded, the method of output redefinition is applied to let the stability of the internal dynamics depend on that of redefined output, thus we only need to consider the new external dynamics rather than internal dynamics in the process of designing control law. To overcome the explosion of complexity problem in traditional backstepping design, the dynamic surface control(DSC) method is firstly used to deal with the problem of tracking control for the nonlinear non-minimum phase systems. The proposed outputfeedback DSC controller not only forces the system output to asymptotically track the desired trajectory, but also drives the unstable internal dynamics to follow its corresponding bounded and causal ideal internal dynamics, which is solved via stable system center method. Simulation results illustrate the validity of the proposed output-feedback DSC controller.

AN IMPROVEMENT OF THE RECURSIVE CLOSED-FORM ALGORITHM FOR NON-MINIMUM PHASE FIR SYSTEM IDENTIFICATION

An improved algorithm which is based on the recursive closed-form algorithm fornon-minimum phase FIR system identification via higher order statistics is presented.In order toincrease the parametric estimation accuracy,the improved algorithm uses the optimal iterativemethod to seek the nonlinear least-square solution.Finally,the simulation examples are alsogiven.

Adaptive fault-tolerant control for non-minimum phase hypersonic vehicles based on adaptive dynamic programming

In this paper,a novel adaptive Fault-Tolerant Control(FTC)strategy is proposed for non-minimum phase Hypersonic Vehicles(HSVs)that are affected by actuator faults and parameter uncertainties.The strategy is based on the output redefinition method and Adaptive Dynamic Programming(ADP).The intelligent FTC scheme consists of two main parts:a basic fault-tolerant and stable controller and an ADP-based supplementary controller.In the basic FTC part,an output redefinition approach is designed to make zero-dynamics stable with respect to the new output.Then,Ideal Internal Dynamic(IID)is obtained using an optimal bounded inversion approach,and a tracking controller is designed for the new output to realize output tracking of the nonminimum phase HSV system.For the ADP-based compensation control part,an ActionDependent Heuristic Dynamic Programming(ADHDP)adopting an actor-critic learning structure is utilized to further optimize the tracking performance of the HSV control system.Finally,simulation results are provided to verify the effectiveness and efficiency of the proposed FTC algorithm.

Robust Stabilization of Non-minimum Phase Switched Nonlinear Systems with Uncertainty

This paper investigates the problem of robust stabilization of a class of switched nonlinear system with uncertain dynamics where each subsystem represents a non-minimum phase.The authors first construct a stabilizing sliding mode controller for each subsystem to stabilize individually its own unstable internal dynamics.Then,a switching strategy is introduced to select the most appropriate diffeomorphism through an infinity of diffeomorphisms.Sufficient conditions are specifically given for the exponential stability and the exponential upper bound of the trajectory of the switched subsystem,which guarantees the global asymptotical stability of the resulting switched system.Obviously,the proposed control approach can improvemore the transient state,compared to a feedback linearization based on only one diffeomorphism.Simulation studies illustrate the effectiveness of the suggested approach.

Multiple Models Direct Adaptive Controller for a Stochastic Non-minimum Phase System

For a stochastic non-minimum phase multivariable system,a multiple models direct adaptive controller is presented.It is composed of multiple fixed models with two adaptive models.The fixed models are used to cover the region where the system parameters jump and improve the transient response,while another two adaptive models are used to guarantee the stability.Utilizing generalized minimum variance design method,it adopts the stochastic system estimation algorithm with optimal controller design method to identify the controller parameter directly.Finally,the global convergence is given.The simulation proves the effectives of the controller proposed.

A benchmark system to investigate the non-minimum phase behaviour of multi-input multi-output systems

In this paper,the problem of designing a multi-input multi-output(MIMO)systemfor studying the non-minimum phase(NMP)behaviour is considered.For this purpose,a NMP MIMO circuit is proposed and studied under different conditions.The main reason for designing this circuit is the lack of a simple and flexible benchmark for examining different control methods.Due to the simple structure and capability of showing different NMP characteristics,our proposed system is a suitable choice to study the behaviour of these systems.Also,our proposed system can be extended by series and parallel connections to generate more complicated benchmarks.The other advantages of this system are the large number of tunable parameters,adjustable interaction,variable number of poles and zeros,and inexpensive cost.Moreover,this benchmark can be used as a tool for hardware simulation.Finally,an optimal H∞decoupling control is applied to this benchmark to verify its effectiveness.

基于非值乘时间成本的乘务排班计划优化编制方法研究

乘务排班计划是城市轨道交通运输计划的重要组成部分,其编制方案优劣直接影响企业运营安全与乘务支出。在班制规定工作时间内,非值乘时间占比越高,工作所需人力资源越多,运营支出效益越低。文章通过缩减乘务人员非值乘时间中的非必要整备时间,从时间成本角度出发,构建最小费用模型。同时设计以爬山算法作为局部搜索策略的文化基因算法,用于优化传统遗传算法对于解的早熟或不收敛导致局部最优的潜在可能。最后以上海市轨道交通某条线路作为案例研究,结果表明模型能够在满足运营需求的前提下,优化乘务人员数量,从而降低乘务支出。其研究结果可为城市轨道交通精细化管理提供理论依据和参考。

On ADRC for non-minimum phase systems： canonical form selection and stability conditions

活跃骚乱拒绝控制(ADRC ) 由韩静清教授求婚了首先把植物动力学归结为它的正规形式，通常在串联综合者，标准控制器能为被采用遇见设计说明形式。这份报纸为非最小的阶段系统与正规形式的选择担心。特别地，由采用众所周知的可控制的正规形式，如此的系统的无常能在输出隧道在州的空格模型，在控制隧道的模型和其它被划分成二项条款，这被显示出。必要、足够的条件与建议正规形式和 ADRC 为靠近环的系统的稳定性被获得。另外，由显示出扩大系统的 detectability 以及系统的某些信息的必要性零，我们在场为非最小的阶段的设计 ADRC 的基本指南不明确的系统。

Optimized Model Based Controller with Model Plant Mismatch for NMP Mitigation in Boost Converter

In this paper,an optimized Genetic Algorithm(GA)based internal model controller-proportional integral derivative(IMC-PID)controller has been designed for the control variable to output variable transfer function of dc-dc boost converter to mitigate the effect of non-minimum phase(NMP)behavior due to the presence of a right-half plane zero(RHPZ).This RHPZ limits the dynamic performance of the converter and leads to internal instability.The IMC PID is a streamlined counterpart of the standard feedback controller and easily achieves optimal set point and load change performance with a single filter tuning parameterλ.Also,this paper addresses the influences of the model-based controller with model plant mismatch on the closed-loop control.The conventional IMC PID design is realized as an optimization problem with a resilient controller being determined through a genetic algorithm.Computed results suggested that GA–IMC PID coheres to the optimum designs with a fast convergence rate and outperforms conventional IMC PID controllers.

欠驱动VTOL飞行器的自耦PID控制方法

针对非最小相位欠驱动垂直起降(vertical taking-off and landing, VTOL)飞行器的控制难题,提出了一种自耦PID(auto-coupling proportional-integral-differrential, ACPID)控制理论方法.首先通过坐标变换将VTOL飞行器的质心映射为Huygens振动中心,不仅能实现新系统控制输入解耦,而且也能避免非最小相位VTOL飞行器零动态不稳定的问题;然后对Huygens振动中心分别设计纵横向位置的ACPID控制器,并分别获得VTOL飞行器底部推力和滚转姿态角虚拟指令,进而设计滚转姿态角的ACPID控制器形成滚转力矩,从而实现VTOL飞行器系统的位置跟踪控制;最后通过复频域分析理论证明闭环控制系统的鲁棒稳定性和抗扰动鲁棒性.理论分析和仿真结果都表明了本文方法的有效性,在非最小相位欠驱动控制系统领域具有重要的科学意义和广泛的应用前景.

襟翼控制的欠驱动飞行器自抗扰/鲁棒控制系统设计

针对含不稳定内动态的襟翼控制欠驱动高超声速飞行器现有控制策略普遍存在的机动性能不足、工程应用困难等问题,设计欠驱动飞行器的自抗扰/鲁棒控制系统。提出一种基于通道级联的欠驱动控制策略,令偏航通道作为滚转通道的内回路,利用±1.5°的侧滑角合法波动范围,提升滚转角的指令跟踪速度。结合自抗扰与鲁棒控制理论设计自动驾驶仪,该自动驾驶仪不仅适用于过载反馈/欠驱动的非最小相位对象,还在摆脱自抗扰系统对关键模型参数依赖的同时减小了鲁棒控制器的降阶难度,有广阔的工程应用前景。为验证方案有效性,以参数存在±20%随机摄动的欠驱动高超声速飞行器模型为对象进行了1000次蒙特卡洛仿真,结果表明新的欠驱动策略能够在保证侧滑角不越界的同时提高滚转通道的响应速度,自抗扰/鲁棒控制系统在面对模型摄动与复合干扰时均有较好的鲁棒性。

基于最小范数的系统侧谐波变阻抗求解技术

准确计算系统侧谐波阻抗对新型电力系统的安全稳定运行有至关重要的意义。在现有谐波阻抗估计算法中,通常假设系统侧谐波阻抗在测量周期中恒定不变。然而,系统侧电压会随着电网运行方式或负荷端大电源用户的接入而发生变化,从而导致系统侧谐波阻抗大小呈现波动的状态。但系统侧谐波阻抗在相邻采样时间间隔内变化并不大,基于此,文中提出一种新的非干预式系统侧谐波变阻抗求解技术,以测量周期内相邻采样时间间隔谐波阻抗二阶变化量和电压二阶变化量的范数为目标函数,通过最小化目标函数求解系统侧谐波阻抗。经过仿真和实际案例分析,验证了该方法在较强背景谐波和用户侧谐波阻抗并非远大于系统侧谐波阻抗条件下的准确性和可靠性。

单电感双输出Buck-Boost变换器的非最小相位特性分析及控制策略

单电感双输出(SIDO)Buck-Boost变换器其中一条支路控制/输出的暂态数学模型含有右半平面零点(RHPZ),因此,该变换器属于非最小相位系统,这使得变换器参数设计及控制变得复杂。针对此问题,首先,利用状态空间平均法建立SIDO Buck-Boost变换器电感电流连续导电模式控制/输出的暂态数学模型,发现变换器先导通支路控制/输出的暂态数学模型含有RHPZ。分析该变换器占空比突变暂态过程可知,先导通支路的输出电压存在负调现象。其次,建立含有负调现象的支路的内动态数学模型。基于此,该文提出对存在负调现象的支路采用电流控制,另一支路采用电压控制的方法。然后,以工作模式和输出纹波电压为约束条件,得到电感和电容的参数设计方法,进而结合劳斯-赫尔维兹判据得到控制参数的取值范围,同时应用特征根灵敏度对控制参数进行优化。最后,搭建仿真与实验平台。仿真及实验结果表明,该文所提控制方法较传统电压控制具有更优的暂态性能,且有效地抑制了输出支路间的交叉影响。

基于ENMSSFMPC-PID的原油稳定加热炉温度控制

为实现对非线性和时变系统的更精准建模和控制,适应系统动态变化和参数变化,应对系统变化和外部干扰,实现更可靠和安全的过程生产控制,提出一种新型模型预测控制策略。基于分数阶微积分运算的扩展非最小状态空间模型预测控制(ENMSSFMPC)算法,状态空间模型包含状态变量和输出跟踪误差,通过分数阶定义将系统模型离散化,利用ENMSSFMPC对比例—积分—微分(PID)控制器进行参数滚动优化,获得实时最优控制参数。原油稳定加热炉模型仿真结果表明,该控制策略优于传统的模型预测控制、非最小状态空间模型预测控制和分数阶模型预测控制。

热工非最小相位对象工程控制及整定方法

含有不稳定零点的非最小相位对象在电力生产过程中广泛存在,由于存在非最小相位特性,要求控制系统在确保输出跟踪的同时还要兼顾内部稳定性,在克服系统负调的同时,要尽量提高其响应速度,普通的PID控制难以满足工程应用的需要。基于此,首先,提出了一种非最小相位对象工程控制及其整定方法,设计鲁棒PID控制器实现系统无差控制,提高系统稳定性,同时克服系统负调;然后,设计二阶滤波器,并引入系统位置误差、速度误差、加速度误差信息,以提高系统的响应速度,改善系统动态性能。该方法原理简单,整定方便,易于在DCS中组态实现,且对模型不确定性有较强的鲁棒性,具有较好工程应用价值。

数据驱动的线性离散系统自学习H_(∞)跟踪控制

针对线性离散系统的H_(∞)跟踪控制问题,提出了一种新的脱策Q-学习方法。首先,采用数学变换,构建非最小状态空间模型,并且给出H_(∞)跟踪控制问题;其次,利用动态规划和强化学习技术,提出脱策Q-学习算法,自学习H_(∞)跟踪控制策略。所提方法的优势在于,仅利用系统输入和输出增量数据,采用构建增广的非最小状态空间方程模型转化方法,自学习H_(∞)跟踪控制策略,使系统稳定地跟踪参考信号,且具有抗干扰能力。最后,使用一般系统及SC-1乙烯裂解炉系统进行仿真实验,实验结果验证了所提方法的有效性。

抗水产病原非O1/O139霍乱弧菌的中草药筛选及抑菌效果分析

为筛选能有效抑制水产病原非O1/O139霍乱弧菌(non-O1/O139 Vibrio cholerae)生长的中草药,本研究通过水煎法获得黄柏、五倍子等23味中草药的提取物,采用琼脂打孔法测定其对非O1/O139霍乱弧菌的抑制作用,并用试管二倍稀释法测定了抑制效果较强的8种中草药对非O1/O139霍乱弧菌的最小抑菌浓度(Minimum Inhibitory Concentration,MIC)和最小杀菌浓度(Minimum Bactericidal Concentration,MBC)。结果表明:五倍子、白芍、黄柏、诃子、山楂、石榴皮、地榆、木瓜等8种草药对非O1/O139霍乱弧菌具有较强的抑制作用,其中非O1/O139霍乱弧菌对五倍子、白芍和黄柏高度敏感,其抑菌圈直径分别为(19.92±1.24)mm、(19.50±0.74)mm和(18.92±2.12)mm。五倍子抑菌和杀菌作用最强,MIC和MBC均为7.81 mg/mL,其次是白芍,MIC为15.63 mg/mL,MBC为31.25 mg/mL。本研究为中草药防治由非O1/O139霍乱弧菌引起的水产动物疾病提供了理论参考。

舰船目标非网格多散射点距离副瓣迭代抑制算法

针对舰船目标非网格多散射点的距离副瓣高、难以有效抑制的问题,采用改进空间谱估计算法——Multiple Signal Classification(MUSIC)对目标多散射点网格偏移量进行解相干和超分辨估计,在此基础上构建目标非网格多散射点模型,提出一种基于最小均方误差(Minimum Mean Squared Error, MMSE)准则的非网格强散射点距离副瓣抑制算法。仿真和实测数据结果表明,该算法在准确估计非网格偏移量的基础上,能够有效抑制距离非网格多散射点目标的副瓣。

基于非理想信道状态信息的高通量卫星预编码算法

为了抑制频率复用造成的同频干扰,高通量卫星通信系统开始研究地面干扰抑制技术,包括应用于反向链路的多用户检测技术和应用于前向链路的预编码技术,建立考虑自由空间损耗、降雨衰减和波束增益等影响的前向链路模型。在非理想信道状态信息模型的基础上针对最小均方误差预编码算法进行改进,提出一种适用于非理想信道状态信息的改进最小均方误差预编码算法。考虑的卫星预编码算法采用更加精确的具有非理想信道信息的信道模型,将非理想信道状态信息纳入预编码算法并进行消除设计。仿真结果表明,基于高通量卫星预编码算法在非理想信道状态信息条件下能够显著提升系统的吞吐量,并且提高了系统的鲁棒性。