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.

Observer design and output feedback stabilization for linear singular time-delay systems with unknown inputs

The design of a functional observer and reduced-order observer with internal delay for linear singular timedelay systems with unknown inputs is discussed. The sufficient conditions of the existence of observers, which are normal linear time-delay systems, and the corresponding design steps are presented via linear matrix inequality（LMI）. Moreover, the observer-based feedback stabilizing controller is obtained. Three examples are given to show the effectiveness of the proposed methods.

Observer-based H-infinity output feedback control with feedback gain and observer gain variations for Delta operator system

Considering that the controller feedback gain and the observer gain are of additive norm-bounded variations, a design method of observer-based H-infinity output feedback controller for uncertain Delta operator systems is proposed in this paper. A sufficient condition of such controllers is presented in linear matrix inequality （LMI） forms. A numerical example is then given to illustrate the effectiveness of this method, that is, the obtained controller guarantees the closed-loop system asymptotically stable and the expected H-infinity performance even if the controller feedback gain and the observer gain are varied.

Observer-based Output-feedback Stabilization Control Design for a Class of Nonlinear Uncertain Systems

The output-feedback stabilization control problem is investigated for a class of nonlinear uncertain systems. Based on the multivariable analog of circle criterion, an observer is designed to estimate the system states and hence the dynamical equations that the estimation error satisfies are derived first. Then, by using integral backstepping approach together with completing square technique, the output-feedback stabilization control is constructively designed such that the closed-loop system is asymptotically stable. Finally, an example is given to illustrate the main results of this paper.

Powertrain Torque Control Based on Torque Observer

To reduce shock during transmission gear shift, a transmission torque feedback closed loop control system is proposed based on the powertrain system model and a torque observer. The ignition time of engine was delayed to reduce transmission output shaft torque during gear shift. In contrast to traditional control method, the closed loop control system based on torque observer can obviously reduce the transmission output shaft torque during gear shift. It can be concluded that by way of torque feedback closed loop control, transmission shift shock can be reduced.

Pattern-Moving-Based Parameter Identification of Output Error Models with Multi-Threshold Quantized Observations

This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.

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.

Exponential Stabilization and Estimation for Sampled Observer Design of Surface Mounted Permanent Magnet Synchronous Motor

A nonlinear state observer design with sampled and delayed output measurements for variable speed and external load torque estimations of SPMSM drive system has been addressed, successfully. Sampled output state predictor is re-initialized at each sampling instant and remains continuous between two sampling instants. Throughout this study, a positive constant to satisfy an upper limit of the sampling period between sampling instants and allowable timing delay in terms of observer parameters has been prepared such that the exponential stable of the closed-loop system is guaranteed, based on Lyapunov stability tools. In order to validate the theoretical results introduced by main fundamental theorem to prove the observer convergence, the proposed sampled-data observer is demonstrated through a sample study application to variable speed SPMSM drive system.

Observer-Based Nonlinear Feedback Controls for Heartbeat ECG Tracking Systems

The analysis and design of observed-based nonlinear control of a heartbeat tracking system is investigated in this paper. Two of Zeeman’s heartbeat models are investigated and modified by adding the control input as a pacemaker, thereby creating the control-affine nonlinear system models that capture the general heartbeat behavior of the human heart. The control objective is to force the output of the heartbeat models to track and generate a synthetic electrocardiogram (ECG) signal based on the actual patient reference data, obtained from the William Beaumont Hospitals, Michigan, and the PhysioNet database. The formulations of the proposed heartbeat tracking control systems consist of two phases: analysis and synthesis. In the analysis phase, nonlinear controls based on input-output feedback linearization are considered. This approach simplifies the difficult task of developing nonlinear controls. In the synthesis phase, observer-based controls are employed, where the unmeasured state variables are estimated for practical implementations. These observer-based nonlinear feedback control schemes may be used as a control strategy in electronic pacemakers. In addition, they could be used in a software-based approach to generate a synthetic ECG signal to assess the effectiveness of diagnostic ECG signal processing devices.

Function Observer Based Event-triggered Control for Linear Systems with Guaranteed L_∞-Gain

This paper is devoted to event-triggered control design for linear systems based on function observer. More specifically, the main purpose is to design event-triggered mechanisms that trigger transmissions when the difference between the current value of the system and its previously transmitted value which includes the plant output or the function observer output exceeds an additional threshold. For such an eventtriggered mechanism, we derive conditions in terms of matrix inequality to guarantee the stability as well as longer inter-event time. We propose two approaches to investigate the closed-loop model, namely, reformulating the event-triggered control system as a hybrid system and interpreting the event-induced error as exogenous disturbance. Furthermore, the minimum inter-event time is guaranteed to be strictly positive. An example is presented to illustrate the feasibility and efficiency of the theoretic results. © 2014 Chinese Association of Automation.

基于自适应分布式滤波观测器的多智能体系统编队控制

本文考虑了全局指令系统输出信息受到信道扰动情况下线性多智能体系统的编队控制问题.首先,基于协作式输出调节理论框架对线性多智能体系统的编队控制问题进行数学建模.其次,针对受到信道扰动的全局指令系统输出信息,提出了一类基于受扰输出的自适应分布式滤波观测器,在降低网络信息交换量的同时消除扰动的影响.最后,设计了输出反馈确定等价控制律,解决了线性多智能体系统的分布式编队控制问题.给出了数值仿真结果检验控制性能.

考虑输出约束及外部干扰的柔性航天器振动控制

针对具有输出约束及外部干扰的柔性航天器系统,提出一种直接关节力矩输入的振动控制方法。利用哈密顿原理,系统动力学特性由偏微分方程(PDE)和常微分方程(ODE)耦合组成的分布参数模型来描述。设计了非线性干扰观测器补偿外界干扰,并基于正切型障碍李雅普诺夫函数解决了航天器姿态角度误差和振动误差的多输出约束问题。利用扩展的拉塞尔不变集原理和半群理论证明了系统的渐近稳定性。不仅实现了姿态角的位置控制,还抑制了柔性航天器的弹性振动。通过对比仿真验证了所提方法的有效性。

基于未知多智能体系统的新型增益控制策略

针对一类具有未知状态与磁滞输入的多智能体系统稳定性问题,提出了一种基于新型时变增益的自适应控制方案。该方案包括构建新型高增益观测器、整合所有未知项并在微分控制环节中进行统一处理,以及调整时变增益信号中的补偿参数实现输入信号的波形降噪与上、下限约束。通过应用这一控制方案,可以实现系统的一致稳定性,还可有效降低微分控制环节中的计算量。除此之外,在系统频率响应的允许范围内调整补偿参数,可以实现输入降噪与上、下限约束。仿真实验结果表明,该方案成功实现了系统输入波形的上、下限约束和降噪优化,同时能够降低微分控制环节的计算量,提高系统的鲁棒性和适应性。

Lipschitz非线性离散系统基于观测器的鲁棒镇定控制设计

本文研究Lipschitz非线性离散时间系统的基于观测器的鲁棒镇定控制问题.首先,针对Lipschitz非线性离散系统,应用微分中值定理和线性参变系统理论,以线性矩阵不等式(LMI)的形式给出基于观测器的鲁棒镇定控制设计的充分条件.随后,将设计结果进一步推广,针对含干扰的Lipschitz非线性离散系统进行H∞性能分析,实现了基于观测器的鲁棒H∞镇定控制,同时给出观测器增益矩阵和控制器增益矩阵的一步求解算法.最后,通过两个数值例子验证了所提方法的有效性.

CLLLC谐振变换器抗扰控制算法研究

CLLLC谐振变换器具有由于具有传输效率高和功率密度高的特点,被广泛应用于直流微电网系统当中。然而,负载突变与参数摄动会使输出电压发生波动,输出电压的稳定控制成为难题。基于扫频法获得降阶模型,模型精度较高,验证了扩展描述函数法(EDF)小信号模型的准确性,具有很好的工程实践意义。提出的改进型线性扩张状态观测器(LESO),可以对包括负载突变及模型偏差等在内的总扰动进行实时估计并加以补偿,且调参简单,解决了传统LESO需要高增益调节跟踪误差,以及存在稳态误差的问题。通过与PI控制和传统线性自抗扰控制(LADRC)的仿真对比,验证了改进型LESO能更有效地控制输出电压的稳定。

光伏并网系统的建模与仿真

根据光伏电池数学模型,在Matlab软件中建立光伏电池的仿真模型并进行了仿真,仿真结果表明,光伏电池的输出呈明显的非线性特性,并随环境温度和光照的变化而变化。在光伏电池最大功率点跟踪方面,提出了一种变步长扰动观察法,可根据外界环境变化,使光伏阵列快速、准确地跟踪最大功率点,同时也能保证系统的稳定。此外,对于逆变器模块,由建模仿真验证了三电平逆变器并网控制策略,得到了稳定的三相正弦电压和电流,为光伏系统稳定并网提供了支撑。

Topology identification for a class of complex dynamical networks using output variables

A problem of topology identification for complex dynamical networks is investigated in this paper. An adaptive observer is proposed to identify the topology of a complex dynamical networks based on the Lyapunov stability theory. Here the output of the network and the states of the observer are used to construct the updating law of the topology such that the communication resources from the network to its observer are saved. Some convergent criteria of the adaptive observer are derived in the form of linear inequality matrices. Several numerical examples are shown to demonstrate the effectiveness of the proposed observer.

Fault diagnosis of time-delay complex dynamical networks using output signals

This paper proposes a novel approach for fault diagnosis of a time-delay complex dynamical network. Unlike the other methods, assuming that the dynamics of the network can be described by a linear stochastic model, or using the state variables of nodes in the network to design an adaptive observer, it only uses the output variable of the nodes to design an observer and an adaptive law of topology matrix in the observer of a complex network, leading to simple design of the observer and easy realisation of topology monitoring for the complex networks in real engineering. The proposed scheme can monitor any changes of the topology structure of a time-delay complex network. The effectiveness of this method is successfully demonstrated by virtue of a complex networks with Lorenz model.

Adaptive Attitude Control for Multi-MUAV Systems With Output Dead-Zone and Actuator Fault

Many mechanical parts of multi-rotor unmanned aerial vehicle(MUAV)can easily produce non-smooth phenomenon and the external disturbance that affects the stability of MUAV.For multi-MUAV attitude systems that experience output dead-zone,external disturbance and actuator fault,a leader-following consensus anti-disturbance and fault-tolerant control(FTC)scheme is proposed in this paper.In the design process,the effect of unknown nonlinearity in multi-MUAV systems is addressed using neural networks(NNs).In order to balance out the effects of external disturbance and actuator fault,a disturbance observer is designed to compensate for the aforementioned negative impacts.The Nussbaum function is used to address the problem of output dead-zone.The designed fault-tolerant controller guarantees that the output signals of all followers and leader are synchronized by the backstepping technique.Finally,the effectiveness of the control scheme is verified by simulation experiments.

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

In this paper, a new fuzzy-neural adaptive control approach is developed for a class of single-input and single-output （SISO） nonlinear systems with unmeasured states. Using fuzzy neural networks to approximate the unknown nonlinear functions, a fuzzy- neural adaptive observer is introduced for state estimation as well as system identification. Under the framework of the backstepping design, fuzzy-neural adaptive output feedback control is constructed recursively. It is proven that the proposed fuzzy adaptive control approach guarantees the global boundedness property for all the signals, driving the tracking error to a small neighbordhood of the origin. Simulation example is included to illustrate the effectiveness of the proposed approach.