Adaptive switching control of uncertain fractional systems: Application to Chua's circuit

Since the introduction of fractional‐order differential equations, there has been much research interest in synthesis and control of oscillatory, periodic, and chaotic fractional‐order dynamical systems. Therefore, in this article, the problem of stabilization and control of nonlinear three‐dimensional perturbed fractional nonlinear systems is considered. The major novelty of this article is handling partially unknown dynamics of nonlinear fractional‐order systems, as well as coping with input saturation along the existence of model variations and high‐frequency sensor noises via just one control input. The method supposes no known knowledge on the upper bounds of the uncertainties and perturbations. It is assumed that the working region of the input saturation function is also unknown. After the introduction of a simple finite‐time stable nonlinear sliding manifold, an adaptive control technique is used to reach the system variables to the sliding surface. Rigorous stability discussions are adopted to prove the convergence of the developed sliding mode controller. The findings of this research are illustrated using providing computer simulations for the control problem of the chaotic unified system and the fractional Chua's circuit model.     

A convex optimization approach to adaptive stabilization of discrete‐time LTI systems with polytopic uncertainties

This paper suggests a simple convex optimization approach to state‐feedback adaptive stabilization problem for a class of discrete‐time LTI systems subject to polytopic uncertainties. The proposed method relies on estimating the uncertain parameters by solving an online optimization at each time step, such as a linear or quadratic programming, and then, on tuning the control law with that information, which can be conceptually viewed as a kind of gain‐scheduling or indirect adaptive control. Specifically, an admissible domain of stabilizing state‐feedback gain matrices is designed offline by means of linear matrix inequality problems, and based on the online estimation of the uncertain parameters, the state‐feedback gain matrix is calculated over the set of stabilizing feedback gains. The proposed stabilization algorithm guarantees the asymptotic stability of the overall closed‐loop control system. An example is given to show the effectiveness of the proposed approach. Copyright © 2014 John Wiley & Sons, Ltd.     

An adaptive regulation method for a class of uncertain time‐delay systems

In this paper, a new adaptive robust stabilization scheme is proposed for uncertain neutral time‐delay systems. No upper bounds on the uncertainties are assumed to be available. An update law is first used to find estimates of these upper bounds. A state‐feedback controller is then designed, which is shown to stabilize the underlying system under some mild conditions. The asymptotic stability of the state trajectories is proved using the Lyapunov–Krasovskii approach. An example is provided, which demonstrates the efficacy of the proposed adaptive control scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

Hyperchaotic behaviour of two bi‐directionally coupled Chua's circuits

In this paper, a non‐linear bi‐directional coupling of two Chua's circuits is presented. The coupling is obtained by using polynomial functions that are symmetric with respect to the state variables of the two Chua's circuits. Both a transverse and a tangent system are studied to ensure a global validity of the results in the state space. First, it is shown that the transverse system is an autonomous Chua's circuit, which directly allows the evaluation of the conditions on its chaotic behaviour, i.e. the absence of synchronization between the coupled circuits. Moreover, it is demonstrated that the tangent system is also a Chua's circuit, forced by the transverse system; therefore, its dynamics is ruled by a time‐dependent equation. Thus, the calculus of conditional Lyapunov exponents is necessary in order to exclude antisynchronization along the tangent manifold. The properties of the transverse and tangent systems simplify the study of the coupled Chua's circuits and the determination of the conditions on their hyperchaotic behaviour. In particular, it is shown that hyperchaotic behaviour occurs for proper values of the coupling strength between the two Chua's circuits. Finally, numerical examples are given and discussed. Copyright © 2002 John Wiley & Sons, Ltd.     

Boost结构太阳能收集电路的MPPT控制方法研究

针对太阳能收集电路的收集效率和可实现性问题,提出一种Boost结构太阳能收集电路的MPPT控制方法。利用Boost电路PWM工作时的升压作用将光伏电池生成的电能强制性储存于大容量电容中,为光伏电池生成电能的最大化收集提供实现可能。通过实时检测光伏电池等效状态和收集电路等效负载确定Boost电路的MPPT控制脉冲最优占空比,迫使收集电路实时工作在光伏电池的MPPT工作点附近,尽可能达到提高太阳能电收集效率的目的。通过分析收集电路工作过程,给出了光伏电池等效状态和收集电路等效负载的实时检测方法以及MPPT控制脉冲最优占空比的确定方法。理论分析和实验结果表明,该控制方法下的Boost结构太阳能收集电路的收集效率高、实现容易。     

Robust adaptive control for non‐linear systems in generalized output‐feedback canonical form

Design of global robust adaptive output‐feedback dynamic compensators for stabilization and tracking of a class of systems that are globally diffeomorphic into systems in generalized output‐feedback canonical form is investigated. This form includes as special cases the standard output‐feedback canonical form and various other forms considered previously in the literature. Output‐dependent non‐linearities are allowed to enter both additively and multiplicatively. The system is allowed to contain unknown parameters multiplying output‐dependent non‐linearities and, also, unknown non‐linearities satisfying certain bounds. Under the assumption that a constant matrix can be found to achieve a certain property, it is shown that a reduced‐order observer and a backstepping controller can be designed to achieve practical stabilization of the tracking error. If this assumption is not satisfied, it is shown that the control objective can be achieved by introducing additional dynamics in the observer. Sufficient conditions under which asymptotic tracking and stabilization can be achieved are also given. This represents the first robust adaptive output‐feedback tracking results for this class of systems. Copyright © 2003 John Wiley & Sons, Ltd.     

Global adaptive finite‐time stabilization of a class of switched nonlinear systems with parametric uncertainty

This paper investigates the global adaptive finite‐time stabilization of a class of switched nonlinear systems, whose subsystems are all in p (p≤1) normal form with unknown control coefficients and parametric uncertainties. The restrictions on the power orders and the nonlinear perturbations are relaxed. By using the parameter separation technique, the uncertain parameters are separated from nonlinear functions. A systematic design procedure for a common state feedback controller and a switching adaptive law is presented by employing the backstepping methodology. It is proved that the closed‐loop system is finite‐time stable under arbitrary switching by utilizing the common Lyapunov function. Finally, with the application to finite‐time control of chemical reactor systems, the effectiveness of the proposed method is demonstrated. Copyright © 2015 John Wiley & Sons, Ltd.     

A design of multivariable,self‐tuning PID controllers with an internal model structure

Self‐tuning control schemes (STC) are useful for systems with unknown or slowly time‐varying parameters. Some single‐input/single‐output PID control schemes based on STCs have been proposed for such systems. However, there are a lot of multivariable systems in real process industries. And these systems often have relatively large time delays. In this paper, a design scheme of self‐tuning PID control system is proposed for multivariable systems with unknown parameters and time delays. The controlled object is equipped with an internal model in order to compensate the time delay and also unstable zeros. Subsequently, a multivariable PID controller is designed for the augmented or compensated system. The PID parameters are calculated recursively based on the relationship between the minimum variance control law and the PID control law. A simulation example is presented to demonstrate the effectiveness of the proposed scheme. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 146(4): 58–64, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10241     

Functional adaptive controller for multivariable stochastic systems with dynamic structure of neural network

The article deals with a challenging problem of adaptive control design for multivariable stochastic systems with a functional uncertainty. Model of the system is based on multi‐layered perceptron neural networks where both the unknown parameters and the structure are found in real time without a necessity of any off‐line training process. The unknown parameters are estimated by a global estimation method, the Gaussian sum filter, and the structure of the neural network model is optimized by a proposed pruning method. The control law is based on a bicriterial approach to the suboptimal dual control. Two individual criteria are designed and used to introduce conflicting efforts between the estimation and control; probing and caution. A comparison of the proposed dual control and its alternative with an implementation of the pruning algorithm is shown in a numerical example. Copyright © 2011 John Wiley & Sons, Ltd.     

电网不平衡下模块化多电平变换器无源一致性控制方法

针对采用传统矢量控制的模块化多电平变换器(MMC)在电网发生单相短路时易发生系统运行失稳的问题,从能量角度出发,提出形式简单、稳定性较好的无源一致性控制方法.以电网不平衡情形下正序电流期望轨迹快速跟踪与负序电流快速抑制为第1目标,通过建立MMC端口受控耗散哈密顿模型,求取不影响全局能量耗散的"无功力",简化无源性控制器...     

直驱型波浪发电系统的混沌运动及反步滑模变控制

为研究直驱式波浪发电系统的混沌现象及混沌控制问题,根据直线电机双轴数学模型,将系统转化为类Lorenz混沌方程。通过数值法计算最大Lyapunov指数谱,证明在特定参数和工况下,电机系统会出现混沌运动。通过构造状态反馈解耦,降低混沌系统阶数。采用反步法构造虚拟控制量,针对虚拟控制量设计滑模控制器,构造控制律进行混沌控制,提出反步滑模变控制方案。稳定性分析中,根据Lyapunov稳定性理论,证明了系统的全局一致渐进收敛。仿真结果表明,所设计反步滑模变控制器能使直线电机系统迅速脱离混沌状态,在抑制传统滑模控制中抖振现象的同时,保留了滑模变结构的强鲁棒性,具有一定的优越性。     

Hyperchaotic signal generation via DSP for efficient perturbations to liquid mixing

This paper presents the design, simulation, hardware implementation and an application in liquid mixing of some hyperchaotic circuits, based on the digital signal processing (DSP) technology. The hyperchaotic Chen's system is used as an example to show the system discretization and variable renormalization in the design process. Numerical simulation is given to verify the hardware signal generator. The implemented hardware of Chen's system generates outputs in good agreement with the numerical simulation. The hyperchaotic signal output from the DSP is applied to generate complex perturbations in liquid mixing experiments. Dye dispersion experiments show that the induced hyperchaotic motion effectively helps enhance the mixing homogeneity in the stirred‐tank‐based mixer in our laboratory. Copyright © 2008 John Wiley & Sons, Ltd.     

Stabilization of controlled positive discrete‐time T‐S fuzzy systems by state feedback control

This paper deals with sufficient conditions of asymptotic stability and stabilization for nonlinear discrete‐time systems represented by a Takagi–Sugeno‐type fuzzy model whose state variables take only nonnegative values at all times t for any nonnegative initial state. This class of systems is called positive systems. The conditions of stabilizability are obtained with state feedback control. This work is based on multiple Lyapunov functions. The results are presented in linear matrix inequalities form. A real plant is studied to illustrate this technique. Copyright © 2010 John Wiley & Sons, Ltd.     

Devil's staircase route to chaos in a non-linear circuit

A driven second-order negative-resistance oscillator circuit has been observed experimentally to exhibit infinitely many distinct chaotic states in addition to infinitely many subharmonic responses of all orders. Each chaotic state is found to be born out of a devil's staircase whose steps are spaced in accordance with a definite period-adding law. Each devil's staircase emerges at some level of frequency-tuning resolution, where each level is embedded within an outer level, ad infinitum. The global bifurcation structure is self-similar in the sense that upon rescaling, the devil's staircases appear to be clones of each other.     

Decentralized adaptive multi‐dimensional Taylor network tracking control for a class of large‐scale stochastic nonlinear systems

This paper investigates the problem of adaptive multi‐dimensional Taylor network (MTN) decentralized tracking control for large‐scale stochastic nonlinear systems. Minimizing the influence of randomness and complex nonlinearity, which increases computational complexity, and improving the controller's real‐time performance for the stochastic nonlinear system are of great significance. With combining adaptive backstepping with dynamic surface control, a decentralized adaptive MTN tracking control approach is developed. In the controller design, MTNs are used to approximate nonlinearities, the backstepping technique is employed to construct the decentralized adaptive MTN controller, and the dynamic surface control technique is adopted to avoid the “explosion of computational complexity” in the backstepping design. It is proven that all the signals in the closed‐loop system remain bounded in probability, and the tracking errors converge to a small residual set around the origin in the sense of a mean quartic value. As the MTN contains only addition and multiplication, the proposed control method is more simplified and of good real‐time performance, compared with the existing control methods for large‐scale stochastic nonlinear systems. Finally, a numerical example is presented to illustrate the effectiveness of the proposed design approach, and simulation results demonstrate that the method presented in this paper has good real‐time performance and control quality, and the dynamic performance of the closed‐loop system is satisfactory.     

A switching periodic adaptive control approach for time‐varying parameters with unknown periodicity

Periodic variations are encountered in many real systems, which can exist in the system parameters, as a disturbance or as the tracking objective. However, there exist a great number of situations where the periodicity is not known in advance. Hence, how to compensate for the effects of time‐varying parameters with unknown periodicity remains a challenge for the controller design. In this paper, we proposed a switching periodic adaptive control approach for continuous‐time nonlinear parametric systems with periodic uncertainties in which the period and bound are not known in advance. We utilized a fully saturated periodic adaptation law to identify the unknown periodic parameters in a pointwise manner. In addition, we provided a logic‐based switching scheme to estimate the unknown period and bound online simultaneously. By virtue of Lyapunov stability analysis, we show that the asymptotic convergence can be guaranteed irrespective of the initial conditions. Finally, we carried out numerical simulations to demonstrate the efficacy of the switching periodic adaptive control algorithm. The proposed approach can be applied to parametric nonlinear systems with time‐varying parameters of unknown periodicity irrespective of the types of periodic uncertainties. Copyright © 2015 John Wiley & Sons, Ltd.     

基于Smith预估控制的温度传感器检测装置的研制

针对矿井胶带运输系统中温度传感器运行情况不能进行实时现场检测的问题,设计了一种基于Smith预估补偿控制的便携式井下运输机温度传感器检测装置。详细介绍了该装置的工作原理,阐述了恒温箱、本安电源电路的硬件设计及基于Smith预估控制的驱动系统的设计,并给出了装置的软件主程序流程图。实验结果和现场运行结果表明该装置具有携带方便、测量准确、实时现场检测等特点。     

Adaptive finite-time control for output regulation of nonlinear systems with completely unknown control directions

This article studies the finite-time output regulation problem for nonlinear strict-feedback systems with completely unknown control directions and unknown functions. First, according to the necessary conditions for the solvability of the output regulation problem, the output regulation problem of nonlinear strict-feedback systems and the external system is transformed into a stabilization problem of nonlinear systems. Second, an internal model with external signals is designed. Third, based on finite time, fuzzy control, output feedback control, and Nussbaum gain functions, the control law is designed so that all signals of the closed-loop system are the semi-global practically finite-time stable (SGPFS), and the tracking error converges to a small neighborhood of the origin in a finite-time. Finally, the proposed algorithm is applied to the finite-time tracking problem of Chua's oscillator system.     

Analogue portable electrooculogram real‐time signal processor

We present an analogue signal‐processing circuit suitable for applications in a portable, wearable, non‐invasive electrooculogram‐based human–computer interface. Behavioural model and preliminary experimental results confirm that the proposed circuit, while operating in real time, correctly detects and decodes signals generated by the subject's eye movements. The total power consumption is measured at 145 mW (excluding the RF link) with a 3 V power supply voltage, and the unit size is approximately 5 cm × 3 cm printed circuit board. Copyright © 2012 John Wiley & Sons, Ltd.     

Lyapunov‐based backward‐horizon adaptive stabilization

In this paper we develop a discrete‐time adaptive stabilization algorithm based on a one‐step backward‐horizon cost criterion. By optimizing the cost with respect to the update step size, we obtain a gain update law that guarantees convergence of the plant states. The convergence proof is based on a modified Lyapunov technique. We extend the algorithm to include integral control for rejecting constant disturbances and we present an experimental application to DC motor positioning system. Copyright © 2003 John Wiley & Sons, Ltd.