Boundedness conjecture for an output error adaptive algorithm

This paper compares conditions for instability with conditions for global asymptotic stability of a discretetime output error adaptive estimation algorithm. This comparison leads to a boundedness conjecture which states that all signals within this adaptive system as well as the output error and parameter estimates remain globally bounded for all time despite any unstable behaviour. The investigation into the stability properties of this algorithm begins with a global stability criterion applied to a transfer function which is not strictly positive real. This criterion states that for large enough adaptation gain and/or input signal magnitude the system will be asymptotically stable. Then a local result is applied which states that for small enough adaptation gain and/or input signal magnitude the same system is unstable. The result is a bifurcation due to the decrease of the adaptation gain and/or input signal magnitude as the system goes from asymptotic stability to instability which remains bounded. The results suggested by the computer simulations are verified by an exact analysis of a linearized periodic version of the adaptive system.     

A rapidly converging filtered‐error algorithm for multichannel active noise control

In this paper, a multichannel adaptive control algorithm is described which has good convergence properties while having relatively small computational complexity. This complexity is similar to that of the filtered‐error algorithm. In order to obtain these properties, the algorithm is based on a preprocessing step for the actuator signals using a stable and causal inverse of the minimum‐phase part of the transfer path between actuators and error sensors, the secondary path. The latter algorithm is known from the literature as postconditioned filtered‐error algorithm, which improves convergence rate for the case that the minimum‐phase part of the secondary path increases the eigenvalue spread. However, the convergence rate of this algorithm suffers from delays in the adaptation path because adaptation rates have to be reduced for larger delays. The contribution of this paper is to modify the postconditioned filtered‐error scheme in such a way that the adaptation rate can be set to a higher value. Consequently, the scheme also provides good convergence if the system contains significant delays. Furthermore, a regularized extension of the scheme is given which can be used to limit the actuator signals. Copyright © 2006 John Wiley & Sons, Ltd.     

Directly computable L2 and L∞ performance bounds for morse's dynamic certainty equivalence adaptive controller

In this paper we consider a model reference adaptive control scheme where the classical error augmentation and standard tuning error normalization are avoided through the use of Morse's high-order tuner. We consider the particular scheme of Morse where the concept of dynamic certainty equivalence is used to reduce the error equation to one that involves only first-order dynamics. With such an error equation, it is first shown that one can directly obtain computable L∞ and L∞ bounds on the tracking error. This is an improvement over some earlier results where either only local L∞ bounds were obtained or the calculation of the global bounds required additional computation. Second, inserting an adaptive gain into Morse's high-order tuner, we show that fast adaptation improves both the L₂ and L∞ bounds on the tracking error, in the sense that the effect of the parametric uncertainty on these bounds is attenuated. Finally, using a simple example, we demonstrate how an earlier attempt to use the adaptive gain to simultaneously attenuate the effect of the parametric uncertainty as well as the initial conditions on the L₂ bound for the tracking error has led to an incorrect result.     

水情自动测报系统VHF无线链路设计研究

基于水情自动测报系统应用环境,为了获得稳定、可靠的数据传输信道,保证系统在恶劣气候环境中通信畅通,分析了VHF无线组网设计中需考虑的主要因素,提出了一套完整、实用、可行的设计方法,特别是在链路预测中,提出了主要影响信道质量因素取值的方法,解决了衰落储备预留取值、绕射损耗定量计算在实际应用中的难题。利用本研究结果设计的无线系统获得广泛应用,设计的链路稳定,信号误码率优于规范指标。     

基于数字预失真技术的功放线性化方法研究

针对现代通信技术对功率放大器高线性化的需求,提出了基于数字预失真技术的优化方案,使用记忆多项式功放行为建模逼近真实的非线性特性,并在间接学习结构上采用递归预测误差训练算法迭代预失真权向量,实现对基带信号的校正处理。仿真结果表明该方案对功放非线性起到优化作用,减弱了频谱的泄露。同时,在实测过程中适当引入功率回退,该方案能获得更快的收敛速度和较好的稳定性,对需求高线性度的功放设计有一定的参考价值。     

Precision motion control of a small launching platform with disturbance compensation using neural networks

A kind of launching platform driven by two permanent magnet synchronous motors which is used to launch kinetic load to hit the target always faces strong parameter uncertainties and strong external disturbance such as the air current impulsion which would degrade their tracking accuracy greatly. In this paper, a practical method which combines adaptive robust control with neural network‐based disturbance observer is proposed for high‐accuracy motion control of the launching platform. The proposed controller not only accounts for the parametric uncertainties but also takes the external disturbances into account. Adaptive control is designed to compensate the former, while neural network‐based disturbance observer is designed to compensate the latter respectively and both of them are integrated together via a feedforward cancellation technique. A new kind of parametric adaptation and weight adaptation strategy is designed by using the linear combination of the system's tracking error and the weight estimation error as a driving signal for parametric adaptation and disturbance approximation. The stability of the novel control scheme is analyzed via a Lyapunov method and this method presents a prescribed output tracking performance in the presence of both parameter uncertainties and unmodeled nonlinearities. Extensive comparative simulation and experimental results are obtained to verify the high‐performance of the proposed control strategy. Copyright © 2016 John Wiley & Sons, Ltd.     

Robust method to provide exponential convergence of model parameters solving linear time-invariant plant identification problem

The scope of this research is a problem of parameters identification of a linear time-invariant plant, which (1) input signal is not frequency-rich, (2) is subjected to initial conditions and external disturbances. The memory regressor extension (MRE) scheme, in which a specially derived differential equation is used as a filter, is applied to solve the above-stated problem. Such a filter allows us to obtain a bounded regressor value, for which a condition of the initial excitation (IE) is met. Using the MRE scheme, the recursive least-squares method with the forgetting factor is used to derive an adaptation law. The following properties have been proved for the proposed approach. If the IE condition is met, then: (1) the parameter error of identification is bounded and converges to zero exponentially (if there are no external disturbances) or to a set (in the case of them) with an adjustable rate, (2) the parameters adaptation rate is a finite value. The above-mentioned properties are mathematically proved and demonstrated via simulation experiments.     

Adaptive neural finite-time output-feedback tracking control for nonlinear stochastic nonstrict-feedback systems with input saturation

In this paper, an observer-based adaptive neural output-feedback control scheme is developed for a class of nonlinear stochastic nonstrict-feedback systems with input saturation in finite-time interval. The mean value theorem and the property of the smooth function are applied to cope with the difficulties caused by the existence of input saturation. According to the universal approximation capability of the radial basis function neural network, it will be utilized to compensate the unknown nonlinear functions. Based on the state observer, the finite-time Lyapunov stability theorem, we propose an adaptive neural output-feedback control scheme for nonlinear stochastic systems in nonstrict-feedback form. The developed controller guarantees that the system output signal can track the given reference signal trajectory, and all closed-loop signals are semi-globally finite-time stability in probability. The observer errors and the tracking error can converge to a small neighborhood of the origin. Finally, simulation results demonstrate the effectiveness of the developed control scheme.     

A method of designing ac/dc thyristor converter current control systems by using discrete time MRAC with deterministic disturbances

Two design methods of ac/dc thyristor converter current control systems with MRAC (Model Reference Adaptive Control) have been designed. To linearize the input/output relation of the systems, the constant term of the model is considered in different ways. In the first method, a linear transformation of the control input is made while in the second method, the constant term and compensated modeling error are neglected by integral adaptation. Computer simulations and experiments have shown that the control performances of the MRAC systems are much better than that of PI controllers. However, in the first method, since the variable vector is not persistently spanning, the convergence rate of estimated parameters is not as high as expected. The second method has better dynamic characteristics but its stability has not been proved in theory. This paper suggests a new design method in which the constant term is considered as a deterministic disturbance. The feature of this method is that by introducing an equality equation which makes the term of disturbances apparently unobservable, the effect of disturbances can be eliminated and the existing adaptive control scheme without disturbances whose stability has been proved theoretically can be used. Computer simulations and experiments show that the new method can obtain better responses than the old ones.     

A dual filtering scheme for nonlinear active noise control

Active noise control problems are often affected by nonlinear effects such as distortion and saturation of measurement and actuation devices, which call for suitable nonlinear models and algorithms. The active noise control problem can be interpreted as an indirect model identification problem, due to the secondary path dynamics that follow the control filter block. This complicates the weight update mechanism in the nonlinear case, in that the error gradient depends on the secondary path gradient through nonlinear recursions. A simpler and computationally less demanding approach is here proposed that employs the updating scheme of the standard filtered‐x least mean squares (LMS) or filtered‐u LMS algorithm. As in those schemes, the calculation of the error gradient requires a signal filtering through an auxiliary system, here obtained through a secondary adaptation loop. The resulting dual filtering LMS algorithm performs the adaptation of the controller parameters in a direct identification mode and can therefore be easily coupled with adaptive model structure selection schemes to provide online tuning of the model structure, for improved model robustness. Copyright © 2013 John Wiley & Sons, Ltd.     

Algorithms of adaptive tracking of unknown multisinusoidal signals in linear systems with arbitrary input delay

The problem of adaptive tracking control is addressed for the class of linear time‐invariant plants with known parameters and arbitrary known input delay. The reference signal is a priori unknown and is represented by a sum of biased harmonics with unknown amplitudes, frequencies, and phases. Asymptotic tracking is provided by predictive adjustable control with parameters generated by one of three designed adaptation algorithms. The first algorithm is based on a gradient scheme and ensures zero steady‐state tracking error with all signals bounded. The other two algorithms additionally involve the scheme with fast parametric convergence improving the closed‐loop system performance. In all the algorithms, the problem of delay compensation is resolved by special augmentation of tracking error. The adjustable control law proposed do not require identification of the reference signal parameters.     

Improved synergetic excitation control for transient stability enhancement and voltage regulation of power systems

This paper proposes decentralized improved synergetic excitation controllers (ISEC) for synchronous generators to enhance transient stability and obtain satisfactory voltage regulation performance of power systems. Each generator is considered as a subsystem, for which an ISEC is designed. According to the control objectives, a manifold, which is a linear combination of the deviation of generator terminal voltage, rotor speed and active power, is chosen for the design of ISEC. Compared with the conventional synergetic excitation controller (CSEC), a parameter adaptation scheme is proposed for updating the controller parameter online in order to improve the transient stability and voltage regulation performance simultaneously under various operating conditions. Case studies are undertaken on a single-machine infinite-bus power system and a two-area four-machine power system, respectively. Simulation results show the ISEC can provide better damping and voltage regulation performance, compared with the CSEC without parameter adaptation scheme and the conventional power system stabilizer.     

基于参数化镇定控制器和误差信号H2范数的LCL型并网逆变器电流控制方法

在LCL型并网逆变系统中,通常为了满足系统性能会对闭环结构进行调整,而这种调整与保证系统内部稳定性之间存在较大矛盾.为解决此问题,提出一种基于参数化镇定控制器和误差信号H2范数的并网电流控制方法.该方法利用参数化镇定控制器保证系统的内部稳定,进而通过设计误差信号的H2范数和开环增益来确定镇定控制器的自由参数和开环增益系...     

ZigBee网络按需干扰攻击检测方案

针对ZigBee网络中存在按需干扰攻击破坏网络正常通信的问题,提出一种按需干扰攻击检测方案,通过设计多级序列分配机制和错误比特检测算法,在确定接收信号强度(RSSI)异常错误比特的基础上,对错误比特RSSI进行序贯概率比检验,进而完成按需干扰攻击检测。实验结果表明,该方案可实现95%以上的检测成功率,并具有较小的通信开销和能量消耗。该方案避免了测量网络报文投递率(PDR)、网络拓扑变化等网络参数,实现了对按需干扰攻击的有效检测,增强了ZigBee网络安全性能。     

Adaptive output regulation for one-dimensional parabolic equation with nonlocal term

In this article, we develop the adaptive error feedback regulator design for one-dimensional heat equation with a nonlocal term and disturbances which are located all the channels. First, we construct a transformation to transform the original system into the first auxiliary system, and in this system the measurable tracking error becomes output, both the disturbances located at the in-domain and the control end are transformed to the uncontrolled end. Next, we design an observer for the first auxiliary system and an estimation mechanism for unknown parameters based on measurable tracking error. Then, by another transformation, we obtain the second auxiliary system, in which the disturbances and the reference signal are collocated with the control. Finally, the adaptive error feedback regulator is designed by using the backstepping method. The simulation results show that the regulator makes the tracking error asymptotically tend to zero and the state of the closed-loop system is bounded.     

Discontinuous pole assignment control of uncertain systems using only input/output measurements

This paper deals with the combined use of continuous and discontinuous adaptation mechanisms in order to control uncertain linear time-invariant systems described by I/O relationships. the complexity of the combined schemes proposed in the literature up to now relies on both the complexity of the underlying linear structure, i.e. the structure of the controller designed under the assumption of perfect knowledge of the plant parameters in order to attain the prescribed control objective, and the complexity of the additional scheme which needs to be introduced in the uncertain case so as to guarantee the stability of the relevant error equation as well as the convergence of the adjusted parameters. In the present paper it is shown how, by choosing a pole assignment control objective, it is possible to conceive a new combined variable structure-adaptive control scheme which on the whole results in being simpler than those previously proposed in the literature.     

An adaptive feedback linearized model predictive controller design for a nonlinear multi-input multi-output system

In this work, an adaptive feedback linearized model predictive control (AFLMPC) scheme is proposed to compensate system uncertainty for a class of nonlinear multi-input multi-output system. Initially, a feedback linearization technique is used to transform the nonlinear dynamics into an exact linear model, thereafter, a model predictive control scheme is designed to obtain the desired tracking performance. A suitable constraint mapping algorithm has been developed to map input constraints to the new virtual input of the proposed control scheme. The proposed control scheme utilizes multiple estimation model and the concept of second-level adaptation technique Pandey et al. (2014) to handle the parametric uncertainty in real-time. Hence, the adaptive term in the control scheme is used to counteract the effect of model uncertainties and parameter adaptation errors. The effectiveness of the proposed AFLMPC control algorithm has been verified successfully in simulation as well as the experimental setup of the TRMS model. The unavailable states of the nonlinear system have been estimated using an extended Kalman filter based state observer. The performance of the proposed control algorithm has been compared with other existing nonlinear control techniques in simulation and experimental validation.     

基于DFT算法的地埋金属管线探测仪研究

为了解决传统地埋金属管线探测仪硬件设计复杂,探测频率相对固定的问题,提高管线探测仪的扩展性、灵活性、稳定性和精确性,通过对管线仪的工作原理和探测技术的探讨,提出了一种基于DFT算法的地埋金属管线探测仪设计方案.该系统利用数字信号处理技术,能够同时检测多个频率的信号,采用DFT算法（离散傅里叶变换）计算接收信号能量,选取与发射信号频率相近的信噪比（SNR）较高的频率信号,可以获得更精确的探测结果.经过实际测试,测量误差小于5％,从而验证了本设计的合理性和系统的精确性.     

A gain‐scheduled control algorithm for input constrained systems to track time‐varying references using controller state resets

In this paper, we propose a control law for a discrete‐time linear system with actuator saturation to track time‐varying reference signals. The proposed control law consists of a feedback controller and a target recalculation mechanism. The feedback controller includes an integrator to achieve zero steady‐state error in the case where the reference signal is constant. The feedback gains of the controller are parameterized by a single scheduling parameter. In the proposed control algorithm, when the tracking error is large, a modified reference signal is computed by the target recalculation mechanism so that feasibility of the algorithm and stability of the control system are guaranteed at all times. At this stage, the controller state is modified online so that the tracking control performance is improved. Further, when the tracking error becomes small, the scheduling parameter and the controller state are updated simultaneously so that the tracking control performance is improved. The problems of determining the scheduling parameter, the controller state, and the modified reference signal are reduced to convex optimization problems with linear matrix inequality constraints. The effectiveness of the proposed control method is shown through an experiment. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

应用DI极性与信号处理的UHVDC输电线路保护新方案

行波传输延时、干扰信号直接影响到基于比幅式的直流输电线路电流突变保护的可靠性。为解决此问题,提出增加纵联电流差值作为启动判据,利用两端电流突变量构成极性判据,并基于极性的比较构成新的保护判据。为解决行波传输延时问题,详细分析了延时机理,提出了一种在正常及区外故障时完全补偿延时的误差修正方案。为解决直流特征谐波、双极间的电磁耦合以及雷电高频脉冲等干扰信号的影响,通过采取Chebyshev数字滤波器得到较好的信号提取结果。基于PSCAD/EMTDC的仿真验证,该保护方案原理简单、可靠性高、采样率低。仿真结果显示,该方案具有很强的耐过渡电阻能力。