Output feedback stabilizability and passivity in nonstationary and nonlinear systems

Passivity properties and passivity conditions have been shown to be very important for the stability of various methodologies of control with uncertainty in linear‐time‐invariant (LTI) systems. Many publications have defined the conditions that allow LTI systems to become strictly passive (and their transfer function strictly positive real) via constant or dynamic output feedback. As beyond the usual uncertainty, real‐world systems are not necessarily invariant, this paper expands the applicability of previous results to nonstationary and nonlinear systems. The paper first reviews a few pole–zero dynamics definitions in nonstationary systems and relates them to stability and passivity of the systems. The paper then finds the sufficient conditions that allow nonstationary systems to become stable and strictly passive via static or dynamic output feedback. Applications in robotics and adaptive control are also presented. Copyright © 2009 John Wiley & Sons, Ltd.     

Smooth switching control for transfer from the Automatic Traveling Mode to the Power Assist Mode of the Skill‐Assist

The objective of this study is to verify a smooth switching control method for transfer from the automatic traveling mode (ATM) to the power assist mode (PAM) of Skill‐Assist. A control law including time‐varying impedance parameters is utilized to attain the objective. The experimental result shows that the transfer from ATM to PAM was successfully performed by the smooth switching control method. © 2007 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

三轴飞行仿真转台自适应复合控制方法

针对三轴飞行仿真转台高精确度伺服系统中存在的由于系统模型参数变化,以及外部扰动、摩擦引起的不确定性和非线性,提出基于模型参考自适应的复合控制方案.该方案具有连续自适应、离散自适应和复合控制方法的优势,通过自适应增益的调整及数字前馈控制的引入,能够消除内外部干扰产生的误差,保证系统在宽频带范围内的跟踪性能和控制精确度.实...     

应用于直线电机的平滑切换模糊PID控制方法

为了适应直线电机的快速动态特性,抑制由于直接驱动使参数摄动和负载扰动等不确定因素对伺服特性的影响,提出了一种新的平滑函数模型,设计了平滑切换式模糊PID复合控制器,并应用于直线电机位置伺服控制。通过模糊控制提高伺服系统的动态性能,用PID控制保证系统的稳态性能,利用平滑函数改善控制切换过程。在PRS-XY型混联机床上的应用表明,该控制算法明显提高了伺服系统的动态性能,减小了位置跟随误差,对非线性扰动因素具有良好的适应性。     

一种并联逆变器自适应下垂控制方法

在逆变器并联系统中,由于线路阻抗的差异,传统下垂控制功率分配精度不高,并且复杂工况下输出电压控制精度低。为了解决以上问题,提出一种基于自适应参数的改进下垂控制方法。该方法在传统P-V下垂控制的基础上,代入基于Lyapunov函数的自适应参数控制,降低原有线路阻抗的影响,保证输出电压在任意负载工况下均保持在一定的约束范围内。此外,在控制回路中加入虚拟阻抗,通过有功功率反馈调节虚拟阻抗比例系数,进一步提高功率分配精度。仿真和实验结果验证了所提出的改进下垂控制方法的有效性。     

永磁同步电机模糊自适应变开关次数权重系数模型预测转矩控制

针对永磁同步电机(PMSM)传统模型预测转矩控制(MPTC)中逆变器开关频率较高的问题,提出将减小开关次数也作为成本函数控制目标之一,构建包括定子磁链控制、转矩控制和开关次数控制在内的多目标成本函数,通过搜索法确定了开关次数权重系数.提出自适应变权重系数控制策略:系统动态下,将开关次数权重系数设置为零,静态下,使用固定...     

Reachability of the sliding mode control for multimachine power systems

This paper presents conditions of reachability of a switching plane for the sliding mode control of phase shifters in multimachine power systems. Sliding mode controllers are usually synthesized so as to satisfy only the existence condition of a sliding mode. However, there is the border of an asymptotically stable region and a system state cannot reach a switching plane unless a state at the beginning of control (initial state) exists in that region. Hence, reachability is defined as an asymptotic stability of the initial state. A sufficient condition to reach onto a switching plane is given by an energy‐type Lyapunov function. It is described by control parameters that are introduced to find required control gains rather than feedback gains themselves. This allows us to straightforwardly evaluate an asymptotic stability. A phase‐shift control system is numerically tested in a 2‐machine 1‐infinite‐bus power system. The simulation results show that the improved control system offers faster transient stability and achieves the reachability of a switching plane. © 2000 Scripta Technica, Electr Eng Jpn, 131(3): 43–50, 2000     

Fuzzy adaptive optimal control for nonlinear switched systems with actuator hysteresis

This article considers the issue of fuzzy adaptive dynamic programming control of nonlinear switched systems with arbitrary switchings and unknown uncertain functions and actuator hysteresis nonlinearities. The whole control approach is made of switching feedforward controller and optimal switching feedback controller. To get over the hardness of arbitrary switching structure and the issue of “explosion of complexity”, the common Lyapunov function theory and dynamic surface control method are utilized in the recursive design technique. By using fuzzy logic systems to model unknown inner dynamics and unknown cost functions, a novel fuzzy adaptive optimal switching control strategy is developed. Meanwhile, uniformly ultimately boundedness of all weights in the controlled systems are proved by the proposed control method, and the tracking performance is guaranteed in an optimal manner. Subsequently, a numerical simulation study is used to test the effectiveness of the presented control strategy.     

Adaptive control of non‐linear systems with unknown virtual control coefficients

This paper deals with state feedback adaptive control of parametric‐strict‐feedback (triangular) non‐linear systems with unknown virtual control coefficients. A priori knowledge of the signs of the virtual coefficients is not required, and control signals and adaptive laws are smooth. Asymptotic tracking of smooth reference signals is achieved while all the variables remain bounded. The proposed algorithms make use of backstepping and tuning functions, and enlarge the class of non‐linear systems with unknown parameters for which asymptotic output tracking can be achieved. Copyright © 2000 John Wiley & Sons, Ltd.     

Adaptive neural dynamic surface control of MIMO stochastic nonlinear systems with unknown control directions

In this paper, an adaptive neural output‐feedback control approach is considered for a class of uncertain multi‐input and multi‐output (MIMO) stochastic nonlinear systems with unknown control directions. Neural networks (NNs) are applied to approximate unknown nonlinearities, and K‐filter observer is designed to estimate unavailable system's states. Due to utilization of Nussbaum gain function technique in the proposed approach, the singularity problem and requirement to prior knowledge about signs of high‐frequency gains are removed, simultaneously. Razumikhin functional method is employed to deal with unknown state time‐varying delays, so that the offered control approach is free of common assumptions on derivative of time‐varying delays. Also, an adaptive neural dynamic surface control is developed; hence, explosion of complexity in conventional backstepping method is eliminated, effectively. The boundedness of all the resulting closed‐loop signals is guaranteed in probability; meanwhile, convergence of the tracking errors to adjustable compact set in the sense of mean quartic value is also proved. Finally, simulation results are shown to verify and clarify efficiency of the offered approach. Copyright © 2016 John Wiley & Sons, Ltd.     

A small‐gain approach for adaptive output‐feedback NN control of switched pure‐feedback nonlinear systems

This paper investigates the problem of adaptive output‐feedback neural network (NN) control for a class of switched pure‐feedback uncertain nonlinear systems. A switched observer is first constructed to estimate the unmeasurable states. Next, with the help of an NN to approximate the unknown nonlinear terms, a switched small‐gain technique‐based adaptive output‐feedback NN control scheme is developed by exploiting the backstepping recursive design scheme, input‐to‐state stability analysis, the common Lyapunov function method, and the average dwell time (ADT) method. In the recursive design, the difficulty of constructing an overall Lyapunov function for the switched closed‐loop system is dealt with by decomposing the switched closed‐loop system into two interconnected switched systems and constructing two Lyapunov functions for two interconnected switched systems, respectively. The proposed controllers for individual subsystems guarantee that all signals in the closed‐loop system are semiglobally, uniformly, and ultimately bounded under a class of switching signals with ADT, and finally, two examples illustrate the effectiveness of theoretical results, which include a switched RLC circuit system.     

Stabilizing switching control for nonlinear system based on quasi‐ARX RBFN model

In this paper, a fuzzy switching adaptive control approach is presented for nonlinear systems. The proposed fuzzy switching adaptive control law is composed of a quasi‐ARX radial basis function network (RBFN) prediction model and a fuzzy switching mechanism. The quasi‐ARX RBFN prediction model consists of two parts: a linear part used for a linear controller to ensure boundedness of the input and output signals; and an RBFN nonlinear part used to improve control accuracy. By using the fuzzy switching scheme between the linear and nonlinear controllers to replace the 0/1 switching, it can realize a better balance between stability and accuracy. Theoretical analysis and simulation results show the effectiveness of the proposed control method on the stability, accuracy, and robustness. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Decentralized robust adaptive-output feedback controller for power system load frequency control

In this paper, a new model reference-decentralized robust adaptive-output feedback controller is proposed for the load frequency control (LFC) of large-scale power systems with unknown parameters. This control strategy requires only local input–output data and can follow random changes in the operating conditions. The controller is designed such that the trajectory errors and the control gains of each area remain uniformly bounded. In the proposed method, firstly an adaptive observer is designed to estimate the state variables and system parameters using local data only. Then a locally linear combination of the estimated states and the model reference states are used to design a robust adaptive-output feedback controller for each area. Simulation results for a three-area power system show that the proposed controller achieves good performance even in the presence of plant parameter changes and system non-linearities. Received: 18 October 2001/Accepted: 24 October 2001     

轧机液压伺服位置系统的自适应输出反馈控制

针对具有不可测状态、未知参数和非线性的轧机液压伺服位置系统,提出一种基于高增益观测器和参数估计器的自适应输出反馈控制算法.所构造的高增益观测器不依赖于系统输入和参数估计值,它只用于估计系统状态,所设计的动态反馈控制器包括:用于保证系统稳定性的主反馈部分和抵消外部扰动和一些不确定性的补偿部分.理论分析表明,所提出的控制算法能够保证闭环系统的所有信号有界,且系统状态及其估计误差的最终收敛边界依赖于观测器的高增益值.以某650 mm可逆冷带轧机液压伺服位置系统为例进行仿真,仿真结果验证了所提出算法的有效性.     

Nonstationary optimal servo control realizing smooth switching from velocity servo to position servo—experimental study

In mechanical structures such as information precision machinery, the switching from a Velocity Servo controller to a Position Servo controller is often utilized. The author has already proposed a unified design method for both the servo controllers on the basis of a single time‐varying criterion function. Its effectiveness has been verified by numerical calculations. This letter demonstrates the effectiveness of the method experimentally. © 2006 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Adaptive robust H∞ state feedback control for linear uncertain systems with time‐varying delay

This paper considers the problem of adaptive robust H_∞ state feedback control for linear uncertain systems with time‐varying delay. The uncertainties are assumed to be time varying, unknown, but bounded. A new adaptive robust H_∞ controller is presented, whose gains are updating automatically according to the online estimates of uncertain parameters. By combining an indirect adaptive control method and a linear matrix inequality method, sufficient conditions with less conservativeness than those of the corresponding controller with fixed gains are given to guarantee robust asymptotic stability and H_∞ performance of the closed‐loop systems. A numerical example and its simulation results are given to demonstrate the effectiveness and the benefits of the proposed method. Copyright © 2008 John Wiley & Sons, Ltd.     

轧机液压伺服位置系统的自适应反步滑模控制

针对轧机液压伺服位置系统存在非线性特性、参数不确定性以及控制输入前具有不确定系数的问题,提出了一种自适应反步滑模控制方法.通过对系统非线性模型的等价变换和选择合适的Lyapunov函数,有效解决了由于控制输入前具有不确定系数导致的所设计的控制量与自适应律互相嵌套的难题.把自适应反步法和滑模控制方法相结合,有效克服了系统...     

模糊自适应滑模变结构控制及其在功率放大器中应用

针对目前使用的电力电子器件构成的功率放大器,提出一种新的基于模糊自适应的滑模变结构控制方法。该方法不仅充分体现了滑模控制的优势,克服了其他控制方法动态响应性能不好、总谐波畸变率较大、鲁棒性差等缺陷,而且因为增加了模糊自适应理论,改善了滑模变结构控制方法中的切换控制所产生的抖振。模糊自适应控制器由模糊化、规则库、模糊推理和反模糊化4部分组成。选择可解决学习算法收敛速度慢问题的模糊基函数作为模糊自适应控制函数,在非线性函数的基础上,对系统进行一系列基函数展开,通过参考值和反馈输出之间的误差不断修正基函数的权,从而达到学习的目的。仿真和试验结果表明该控制策略对系统参数和负载扰动具有很强的鲁棒性,系统动、静态性能良好。     

电气伺服系统的自适应模糊积分滑模控制

针对外界扰动及不确定性等因素对电气伺服系统性能的影响,将具有积分滑模面的自适应模糊控制器引入电气伺服系统的位置控制,利用滑模控制克服不确定性因素影响,通过自适应律与模糊规则的结合削弱滑模控制引起的抖振,通过参数自适应估计方法保证滑模变结构控制增益的合理性,提高了电气伺服系统的稳定性与位置跟踪性能.仿真实验结果表明,这种控制系统具有控制结构简单,稳态性能好等优点,并对不确定性等因素具有良好的鲁棒性.     

开关型电磁铁控制比例伺服阀的方法及实验研究

提出利用开关电磁铁构成单电磁铁式电液比例伺服阀的方案。在闭环控制基础上,提出自适应前馈补偿方法,解决开关电磁铁的非线性问题;采用抗饱和积分控制方法,在消除稳态误差的基础上,减小电磁铁动态响应时间。在理论上解释2种方法的原理,试验验证2种控制方法的效果。另外,利用电磁铁心速度反馈,增大闭环回路增益,进一步减小电磁铁的动态响应时间。结果表明,与现有采用比例电磁铁的技术相比,新方案具有设计简单、成本低的优点。