一种最优自适应增益非线性观测器的锂电池SOC估算方法

如今电动汽车的发展十分迅速,其动力电池荷电状态SOC关系到锂电池及整车系统的安全、可靠运行,因为SOC表明了电池剩余电量。由于SOC是一个不可直接测量的非线性变量,因此设计一种精度高、可行性强的算法具有十分重要的意义。提出一种最优自适应增益非线性观测器（OAGNO）,用差分进化算法（DE）对观测器参数进行寻优。为了验证该方法的先进性,对型号为NCR18650GA的三元锂电池进行工况实验,结果表明,相比无迹卡尔曼滤波（UKF）,最优自适应非线性状态观测器具有更高的精度,误差在3%左右。     

一类非线性不确定系统的多通道鲁棒故障诊断

针对一类含有状态时滞和扰动的非线性不确定系统,研究了一种基于状态估计的执行器故障诊断方法。在通过变换得到等价系统的基础上,构造全阶时滞观测器(TDO),削弱外扰影响,并利用神经网络设计的故障估计器在线估计出系统故障,实现多通道诊断,最后采用域值处理技术提高故障估计的鲁棒性。仿真示例表明了该方法的有效性。     

An adaptive strategy for controlling chaotic system

This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems: Duffing oscillator and Rössler chaos.     

Pressure observer based adaptive robust trajectory tracking control of a parallel manipulator driven by pneumatic muscles

This paper presents a pressure observer based adaptive robust controller (POARC) for posture trajectory tracking of a parallel manipulator driven by three pneumatic muscles without pressure sensors. Due to model errors of the static forces and friction forces of pneumatic muscles, simplified average flow rate characteristics of valves, unknown disturbances of entire system, and unmeasured pressures, there exist rather severe parametric uncertainties, nonlinear uncertainties and dynamic uncertainties in modeling of the parallel manipulator. A nonlinear pressure observer is constructed to estimate unknown pressures on the basis of a single-input-single-output (SISO) decoupling model that is simplified from the actual multiple-input-multiple-output (MIMO) coupling model of the parallel manipulator. Then, an adaptive robust controller integrated with the pressure observer is developed to accomplish high precision posture trajectory tracking of the parallel manipulator. The experimental results indicate that the system with the proposed POARC not only achieves good control accuracy and smooth movement but also maintains robustness to disturbances.     

LMI Approach to Mixed H_｜H∞ Fault Detection Observer Design

To investigate the robust fault detection(RFD) observer design for linear uncertain systems,the H_ index and H ∞ norm are used to describe this observer design as optimization problems.Conditions for the existence of such a fault detection observer are given in terms of matrix inequalities.The solution is obtained by new iterative linear matrix inequality(ILMI) algorithms.The RFD observer design over finite frequency range in which D f does not have full column rank for a system is also considered.Numerical example demonstrates that the designed fault detection observer has high sensitivity to the fault and strong robustness to the unknown input.     

Sliding-mode observers for systems with unknown inputs and measurement disturbances

The method to design sliding-mode observers for systems with unknown inputs and measurement disturbances is presented in the paper. An augmented system is constructed by viewing the measurement disturbances as unknow inputs. For such an augmented system, the so-called observer matching condition is not satisfied. Based on the construction of auxiliary outputs, the observer matching condition may be satisfied. High-order sliding-mode differentiators are developed to obtain the estimates of those unmeasurable variables contained in the auxiliary output vector. Employing the estimate of auxiliary output vector, a sliding-mode observer is designed. The simulation results to a real model show that the proposed method is effective.     

Passive control of a class of chaotic dynamical systems with nonlinear observer

A passive control strategy with nonlinear observer is proposed, which can be used to control a class of chaotic dynamical systems to stabilize at different equilibrium points. If the nonlinear function of chaotic system satisfies Lipschitz condition, the nonlinear observer can observe the state variables of the chaotic systems. An important property of passive system is studied to control chaotic systems, that is passive system can be asymptotically stabilized by state feedback controller whose state variables are presented by nonlinear observer. Simulation results indicated that the proposed chaos control method is very effective in a class of chaotic systems.     

Adaptive terminal sliding mode control for high-order nonlinear dynamic systems

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Active suspension control of a one-wheel car model using single input rule modules fuzzy reasoning and a disturbance observer

INTRODUCTION Research and development of active suspensionsystems for car models are increasing much in recentyears because the active suspension systems offergood riding comfort to passengers of high speedground transportation. Investigation of linear activesuspension systems has been mainly developed basedon optimal control theory assuming that the car modelis described by a linear or approximately linear sys-tem (Hác, 1986; Hrovat, 1993; Yoshimura and Su-gimoto, 1990). However,…     

Adaptive terminal sliding mode control for high-order nonlinear dynamic systems

An adaptive terminal sliding mode control (SMC) technique is proposed to deal with the tracking problem for a class of high-order nonlinear dynamic systems. It is shown that a function augmented sliding hyperplane can be used to develop a new terminal sliding mode for high-order nonlinear systems. A terminal SMC controller based on Lyapunov theory is designed to force the state variables of the closed-loop system to reach and remain on the terminal sliding mode, so that the output tracking error then converges to zero in finite time which can be set arbitrarily. An adaptive mechanism is introduced to estimate the unknown parameters of the upper bounds of system uncertainties. The estimates are then used as controller parameters so that the effects of uncertain dynamics can be eliminated. It is also shown that the stability of the closed-loop system can be guaranteed with the proposed control strategy. The simulation of a numerical example is provided to show the effectiveness of the new method. Project supported by the National Outstanding Youth Science Foundation of China (NSFC:69725005) and the Zhejiang, Provincial Natural Science Key Foundation of China (ZD9905)     

基于动态神经网络非线性仿射系统H∞控制（一）

基于神经网络,对一类非线性系统H∞控制进行研究,通过构造动态神经网络来逼近非线性系统,在这个模型基础上,给出系统状态反馈控制方案,利用H∞控制来消除模型误差和外部扰动,使被控系统达到较好的性能,反馈增益矩阵转化为线性矩阵不等式问题,通过LMI来解决.     

一类非线性连续奇异系统降维观测器的设计

讨论了一类非线性时间连续奇异系统观测器的设计问题,通过线性矩阵不等式,给出了一种易于计算的降维观测器的设计方法;仿真数值例子表明了所给设计方法的有效性。     

基于DSC的自适应补偿神经网络控制

针对一类可转化为“标准块控制形”的MIMO非线性系统,基于动态面控制技术,提出一种鲁棒自适应神经网络控制算法。采用径向基函数神经网络逼近不确定性模型,通过引入一阶滤波器,消除后推设计中由于反复对虚拟控制的求导而导致的复杂性问题,同时补偿项的引入可避免反馈线性化方法中可能出现的控制器奇异性问题,无需控制增益矩阵正定、可逆的条件。利用李亚普诺夫方法,证明了闭环系统是半全局一致终结有界,适当选取设计常数,跟踪误差可收敛到原点的一个小邻域内。计算机仿真结果表明此法的有效性。     

Theory and experiment of observer based magnetostrictive self-sensing actuator

Giant magnetostrictive actuators （GMAs） often work in a close-loop feedback system. This system needs independent sensors which may be difficult to be fixed, besides, excessive sensors may cause more unpredicted problems in a large system. This paper aims to develop a self-sensing GMA. An observer based on piezomagnetic equations is constructed to estimate the stress and strain of the magnetostrictive material. The observer based self-sensing approach depends on the facts that the magnetic field is controllable and that the magnetic induction is measurable. Aiming at the nonlinear hysteresis in magnetization, a hysteresis compensation observer based on Preisach model is developed. Experiment verified the availability of the observer approach, and the hysteresis compensation observer has higher tracking precision than linear observer for dynamic force sensing.     

Study on inverter fault-tolerant operation of PMSM DTC

This paper presents an investigation of inverter fault-tolerant operation for a permanent magnet synchronous motor （PMSM） direct torque control （DTC） system under various inverter faults. The performance of a faulty standard 6-switch inverter driven PMSM DTC system is analyzed. To avoid the loss or even disaster caused by the inverter faults, a topology-modified inverter with fault-tolerant capability is introduced, which is reconfigured as a 3-phase 4-switch inverter. The modeling of the 4-switch inverter is then analyzed and a novel DTC strategy with a unique nonlinear perpendicular flux observer and feedback compensation scheme is proposed for obtaining a continuous, disturbance-flee drive system. The simulation and experimental results demonstrate that the proposed inverter fault-tolerant PMSM DTC system is able to operate stably and continuously with acceptable static and pretty good dynamic performance.     

一类不确定非线性切换系统观测器的设计

研究一类非线性切换系统的观测器的设计问题。系统的不确定性满足范数有界,利用共同Lyapunov函数方法,给出了增广系统渐近稳定的充分条件,得到了系统的观测器。     

Active disturbance rejection control for hydraulic width control system for rough mill

The highly nonlinear behavior of the system limits the performance of classical linear proportional and integral (PI) controllers used for hot rolling. An active disturbance rejection controller is proposed in this paper to deal with the nonlinear problem of hydraulic servo system in order to preserve fast response and small overshoot of control system. The active disturbance rejection (ADR) controller is composed of nonlinear tracking differentiator (TD),extended state observer (ESO) and nonlinear feedback (NF) law. An example of the hydraulic edger system case study is investigated to show the effectiveness and robustness of the proposed nonlinear controller,especially,in the circumstance of foreign disturbance and working condition variation,compared with classic PI controller.     

Interval standard neural network models for nonlinear systems

INTRODUCTION Neural networks have been successfully em- ployed for controlling nonlinear systems since the 1990’s (Narendra and Parthasarathy 1990; Hunt et al., 1992; Suykens et al., 1996). In these nonlinear control systems, neural networks have been used either for modelling the system to be controlled, or for design- ing a controller, or both. Recently, the robustness issue has been an important focus of research in neuro-control circles (Suykens et al., 1996; Wams et al., 1999; Aya…     

四旋翼无人机高度控制——基于CNF与自适应非光滑控制

针对受限环境下四旋翼无人飞行器在参数不确定及外部扰动影响下的高性能高度控制问题,设计一种基于复合非线性反馈（CNF）和自适应非光滑轨迹跟踪控制的高度控制方法。通过四旋翼无人飞行器的垂直通道动力学模型分析和变换,将高度轨迹规划问题转换为输入受限的线性系统控制问题,设计CNF控制器实现轨迹生成;建立参数不确定及外部扰动影响下的垂直通道动力学模型,设计一种自适应非光滑轨迹跟踪控制器,并理论证明了闭环系统稳定性。最后,通过仿真实验验证所提出方法的有效性。结果表明,所设计方法能够有效提高参数不确定及外部扰动下的高度控制品质,且简单实用。     

基于广义BP算法的模型参考自适应控制

改进了传统的神经网络BP算法,提出了基于广义BP算法的非线性不确定系统的神经网络模型参考自适应控制方案.并将其用于非线性不确定系统的控制,仿真实验表明了控制器具有良好的非线性控制性能.