Singular observer approach for chaotic synchronization and private communication

Based on the singular system observer, this paper proposes an effective approach for chaotic synchronization and private communication. When the useful information is modulated in a chaotic system and its dynamic equation is not available, we can consider the transmitted signal as an external system state. Then we can design a singular observer which has higher dimension. The advantage of such a design is that we can avoid using the derivation information of the transmitted signal. By adopting the singular system observer approach, the transmitted signal can be recovered successfully by the observer. Numerical simulations show the effectiveness of the proposed method.     

Arbitrary observer scaling of all chaotic drive system states via a scalar synchronizing signal

This paper introduces a straightforward method to arbitrarily scale a drive system attractor using a synchronized linear observer. This scaling is controlled by a single observer parameter. Theoretical and simulation results for both continuous- and discrete-time systems demonstrate that linear observers can duplicate all chaotic system states in any desired scale using only a scalar synchronizing signal.     

Model recovery for Hammerstein systems using the auxiliary model based orthogonal matching pursuit method

This article investigates parameter and order identification of a block-oriented Hammerstein system by using the orthogonal matching pursuit method in the compressive sensing theory which deals with how to recover a sparse signal in a known basis with a linear measurement model and a small set of linear measurements. The idea is to parameterize the Hammerstein system into the linear measurement model containing a measurement matrix with some unknown variables and a sparse parameter vector by using the key variable separation principle, then an auxiliary model based orthogonal matching pursuit algorithm is presented to recover the sparse vector.The standard orthogonal matching pursuit algorithm with a known measurement matrix is a popular recovery strategy by picking the supporting basis and the corresponding non-zero element of a sparse signal in a greedy fashion. In contrast to this, the auxiliary model based orthogonal matching pursuit algorithm has unknown variables in the measurement matrix. For a K-sparse signal, the standard orthogonal matching pursuit algorithm takes a fixed number of K stages to pick K columns (atoms) in the measurement matrix, while the auxiliary model based orthogonal matching pursuit algorithm takes steps larger than K to pick K atoms in the measurement matrix with the process of picking and deleting atoms, due to the gradually accurate estimates of the unknown variables step by step.The auxiliary model based orthogonal matching pursuit algorithm can simultaneously identify parameters and orders of the Hammerstein system, and has a high efficient identification performance.     

A Soft-Computing Algorithm-based Cognitive Observer for an Elastic Robotic Arm

This paper proposes the use of Support Vector Machine (SVM) algorithm for modeling and states estimation of an elastic robotic arm. Due to the complexity of the elastic robotic arm, an accurate mathematical model and large number of sensors are needed to achieve accurate estimation. Initially, it is assumed that all system states are measurable for a short period of time. Additionally, the system output and input signals are being continuously measured. The modeling module builds two models, the internal model which will capture the dynamics of the elastic robotic arm and the data-driven observer model which will estimate the system states. The internal model and data-driven observer are obtained based on the experimental measurements using SVM algorithm in contrast to classical methods that uses the mathematical system model to drive an observer. The internal model is able to make multi-steps ahead predictions of all system states; therefore it can be used to generate a suitable control strategy. Once the models are ready, the main sensors can be removed or turned off. The proposed modeling module will eliminate the need for mathematical modeling and reduces the number of permanent sensors needed. If the main sensors are removed completely, the hardware price can be radically reduced. The simulation result demonstrates the efficiency and high performance of the modeling module. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Observer-based synchronization of uncertain chaotic system and its application to secure communications

Within the drive-response configuration, this paper considers the synchronization of uncertain chaotic systems based on observers and chaos-based secure communication. Even if there are unknown disturbances and parameters in the drive system, a robust adaptive observer can be used as response system to realize chaotic synchronization. The proposed method is then applied to secure communication. The transmitter is constructed by injecting the information into the drive system with proper manner and one of the transmitting signal is the sum of one of the output and the information signal. The Lur’e chaotic system is considered as an illustrative example to demonstrate the effectiveness of the proposed approaches.     

Cauchy中值定理与Leibniz公式的推广

引入辅助函数的方法可将Cauchy中值定理推广到高阶形式,即两函数n阶Taylor展开误差的比值等于在某点两函数(n+1)阶导数比值的形式;用数学归纳法可将Leibniz公式中函数的个数推广至任意有限多个.     

Adaptive output feedback asymptotic stabilization of nonholonomic systems with uncertainties

A global adaptive output feedback control strategy is presented for a class of nonholonomic systems in generalized chained form with drift nonlinearity and unknown virtual control parameters. The purpose is to design a nonlinear output feedback switching controller such that the closed-loop system is globally asymptotically stable. By using the input-state scaling technique and an integrator back-stepping approach, an output feedback controller is given. A filter of observer gain is introduced for state and parameter estimates. Meanwhile, in order to avoid the over-parameters, a tuning function technique is utilized. A novel switching control strategy based on the output measurement of the first subsystem rather than time is used to overcome the uncontrollability of the x₀-subsystem in the origin. The proposed controller can guarantee that all the system states globally converge to the origin, while other signals maintain bounded. The numerical simulation testifies the effectiveness.     

Adaptive robust synchronization of Rossler systems in the presence of unknown matched time-varying parameters

This paper deals with the problem of adaptive robust synchronization of chaotic systems based on the Lyapunov theory. A controller is designed for a feedback linearizable error system with matched uncertainties. The proposed method shows that the drive and response systems are synchronized and states of the response system track the states of the drive system as time tends to infinity. Since this approach does not require any information about the bound of uncertainties, this information is not needed in advance. In order to prevent the frequent switching phenomenon in the control signal, the method is modified such that the norm of tracking error is bounded. Numerical simulations on two uncertain Rossler systems with matched uncertainties show fast responses of tracking error, while the errors are Uniformly Ultimately Bounded, and the control signal is reasonably smooth.     

The signal model: A model for competing risks of opportunistic maintenance

This paper presents a competing risks reliability model for a system that releases signals each time its condition deteriorates. The released signals are used to inform opportunistic maintenance. The model provides a framework for the determination of the underlying system lifetime from right-censored data, without requiring explicit assumptions about the type of censoring to be made. The parameters of the model are estimated from observational data by using maximum likelihood estimation. We illustrate the estimation process through a simulation study. The proposed signal model can be used to support decision-making in optimising preventive maintenance: at a component level, estimates of the underlying failure distribution can be used to identify the critical signal that would trigger maintenance of the individual component; at a multi-component system level, accurate estimates of the component underlying lifetimes are important when making general maintenance decisions. The benefit of good estimation from censored data, when adequate knowledge about the dependence structure is not available, may justify the additional data collection cost in cases where full signal data is not available.     

Study on chaos control of second-order non-autonomous phase-locked loop based on state observer

With system parameters falling into a certain area, the second-order non-autonomous phase locked loop (PLL) is experiencing chaotic behavior which is undesirable in system, where it is necessary to estimate the phase of a received signal. In order to control chaos in PLL and drive it to the locked state, dynamical equation for phase error model of PLL is firstly derived. Then, the state values of phase and transient frequency errors were estimated by a state observer. Moreover, by exploiting these state estimations, a non-linear feedback controller is designed. Since the presented controller does not need to change the controlled system structure and not to use any information of system except the system state variables, the designed controller is simple and desirable. Simulation results show that the presented control law is very effective.     

非线性系统的一种模糊滑模变结构控制方案

基于HM模型对非线性系统进行描述，采用Lyapunov方法设计出确保系统全局渐近稳定的滑模变结构控制器。对满足匹配条件和不满足匹配条件的情况均适用。并用一级倒立摆系统进行仿真验证。成功的将变结构控制应用于非线性控制系统中。     

Design,modelling and simulation of a new nonlinear and full adaptive backstepping speed tracking controller for uncertain PMSM

In this study, a new nonlinear and full adaptive backstepping speed tracking control scheme is developed for an uncertain permanent magnet synchronous motor (PMSM). Except for the number of pole pairs, all the other parameters in both PMSM and load dynamics are assumed unknown. Three phase currents and rotor speed are supposed to be measurable and available for feedback in the controller design. By designing virtual control inputs and choosing appropriate Lyapunov functions, the final control and parameter estimation laws are derived. The overall control system possesses global asymptotic stability; all the signals in the closed loop system remain bounded, according to stability analysis results based on Lyapunov stability theory. Further, the proposed controller does not require computation of regression matrices, with the result that take the nonlinearities in quite general. Simulation results clearly exhibit that the controller guarantees tracking of a time varying desired reference speed trajectory under all the uncertainties in both PMSM and load dynamics without singularity and overparameterization. The results also show that all the parameter estimates converge to their true values on account of the fact that reference speed signal chosen to be sufficiently rich ensures persistency of excitation condition. Consequently, the proposed controller ensures strong robustness against all the parameter uncertainties and unknown bounded load torque disturbance in the PMSM drive system. Numerical simulations demonstrate the performance and feasibility of the proposed controller.     

Adaptive synchronization of chaotic systems and its application to secure communications

This paper addresses the adaptive synchronization problem of the drive–driven type chaotic systems via a scalar transmitted signal. Given certain structural conditions of chaotic systems, an adaptive observer-based driven system is constructed to synchronize the drive system whose dynamics are subjected to the system’s disturbances and/or some unknown parameters. By appropriately selecting the observer gains, the synchronization and stability of the overall systems can be guaranteed by the Lyapunov approach. Two well-known chaotic systems: Rössler-like and Chua’s circuit are considered as illustrative examples to demonstrate the effectiveness of the proposed scheme. Moreover, as an application, the proposed scheme is then applied to a secure communication system whose process consists of two phases: the adaptation phase in which the chaotic transmitter’s disturbances are estimated; and the communication phase in which the information signal is transmitted and then recovered on the basis of the estimated parameters. Simulation results verify the proposed scheme’s success in the communication application.     

Computation of the observer gain for extended Luenberger observers using automatic differentiation

For a given nonlinear system, the extended Luenberger observerprovides nearly exact error dynamics. In contrast to the normalform observer, the extended Luenberger observer exists evenif the associated integrability condition is violated. Up tonow, Lie derivatives and Lie brackets required by the designprocedure have been computed symbolically. Even for systemswith moderate size and complexity, one usually obtains extremelylarge expressions for the observer gain. The design of an extendedLuenberger observer based on symbolic differentiation is not feasible for complicated or large-scale systems. In this paperwe discuss a new approach to compute the observer gain. Ourapproach is based on a computation method for derivatives calledautomatic differentiation. In contrast to numeric differentiationby means of divided differences, automatic differentiationincurs no truncation errors.     

Interval techniques for enclosures of regions of reachability and controllability and for guaranteed state and parameter estimation of dynamical systems

Interval techniques are a powerful means for calculation of enclosures of the regions of reachability and controllability of dynamical systems with uncertainties during analysis and design of controllers. In this contribution, both discrete-time and continuous-time dynamical systems are considered. Using suitable algorithms, guaranteed state enclosures can be determined for systems with uncertain parameters, uncertain initial conditions, nonlinearities, and time-varying characteristics. Although both uncertain system parameters and bounded control variables are assumed to be represented by interval boxes in the following, they have to be distinguished in reachability and controllability analysis. Typically, robustness specifications for controllers of dynamical systems are given in terms of bounds on the system's time response which must not be violated for any possible operating condition. Hence, reachability as well as controllability of states have to be proven for all possible parameter values but for at least one admissible control sequence. Robust control strategies for nonlinear systems usually rely on knowledge of all current states. However, the complete state vector is not always directly accessible for measurement. In this case, observers are applicable to reconstruct non-measurable state variables. Furthermore, they can reduce the uncertainties of the measured quantities by model-based recursive computation of estimates and fusion of information gathered by different measurement devices. If guaranteed bounds of all uncertain parameters of a dynamical system (including the sensor characteristics) and conservative bounds of all disturbances can be specified, the presented interval observer provides guaranteed enclosures of all reachable states. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

On an inhomogeneous Tricomi problem for a parabolic-hyperbolic equation

We consider an inhomogeneous Tricomi problem for a parabolic-hyperbolic equation with noncharacteristic type change line and with Frankl type matching condition for the normal derivatives on the type change line. The auxiliary function method is used to establish an a priori estimate of the solution. The existence of the solution is proved by the spectral method.     

The Mortar Element Method with Lagrange Multipliers for Stokes Problem

In this paper,we propose a mortar element method with Lagrange multiplier for incompressible Stokes problem,i.e.,the matching constraints of velocity on mortar edges are expressed in terms of Lagrange multipliers.We also present P_1 noncon- forming element attached to the subdomains.By proving inf-sup condition,we derive optimal error estimates for velocity and pressure.Moreover,we obtain satisfactory approximation for normal derivatives of the velocity across the interfaces.     

Synthesis of minimum-order robust inverters

In the present paper, we consider the inversion problem for dynamical systems, that is, the problem of reconstruction of the unknown input signal ξ(t) of a given system on the basis of known information (about either the complete phase vector or a measurable output of the system). An auxiliary dynamical system forming the desired estimate of the signal ξ(t) is called an inverter.In earlier papers of the authors, attention was mainly paid to the possibility of inversion of a dynamical system in different cases in principle. In this relation, a model of dynamical systems with some stabilizing control was used as an inverter for the solution of the problem; moreover, this control was often designed with the use of an additional dynamical system, an observer of the phase vector of the original system or the system in deviations. Thus, a dynamical system whose dimension either coincides with the dimension of the original system or exceeds it was considered as an inverter.In the solution of practical problems, it is often required to synthesize inverters of minimal order. (This requirement is related to constraints on the complexity, cost, and operation speed of automated control systems.) In the present paper, we consider the problem on the possible reduction of the order of the inverter in various cases and the problem on the construction of inverters of minimal order.     

基于Hilbert变换的LFM检测与估计

LFM(线性调频)信号是一类重要的非平稳信号,其完全被初始频率和调频斜率两个参量表征,而LFM信号的检测与估计问题是信号处理中最为重要的研究热点之一.由于调频信号在时频平面内有较好的聚集性,通常使用时频分析的方法对其进行检测和估计.线性正则变换是经典时频分布的广义形式,对LFM信号具有很好的能量聚集特性,在现有的线性正则域Hilbert变换的基础上,提出了一种不需要谱峰搜索而快速检测LFM信号和估计其参数的方法,并且通过仿真实例验证了所提出方法的优越性.     

Restoration of controls under conditions of incomplete information on the dynamics of the system

The inverse dynamical problem of the restoration of the controls or parameters of a dynamical system which are unknown in advance is considered, using results from the observation of the motion of the system under conditions when there is incomplete information on the phase states of the system. It is assumed that, at appropriate actual instants of time, the observer only obtains certain information sets containing the actual phase states of the system. It is well known that this problem is ill posed. Constructive dynamic regularizing algorithms for solving the problem are constructed which posses the property of physical feasibility and are capable of working under real-time conditions while processing incoming information during the motion of the system and producing a result in dynamics as the motion develops.