Minimal periodic realizations of transfer matrices

Periodic controllers designed based on the so-called lifting technique are usually represented by transfer matrices. Real operations require that the controllers be implemented as periodic systems. The problem of realizing an Nn_o×Nn_i proper rational transfer matrix as an n_i-input n_o-output N-periodic discrete-time system is studied. An algorithm for obtaining periodic realizations which have a minimal number of states is proposed. The result can also be used to remove any redundant states that exist in a periodic system     

An analytical model for hybrid checkpointing in time warpdistributed simulation

The Time Warp distributed simulation algorithm uses checkpointing to save process states after certain event executions for later recovery at the time of a rollback. Two main techniques have been used for checkpointing: periodic state saving and incremental state saving. The former technique introduces large overheads in reconstructing a desired state by coasting forward from an earlier checkpointed state if the computational granularity is large. The latter technique also has large overheads in applications with large rollback distances. A hybrid checkpointing technique is proposed which uses both periodic and incremental state saving simultaneously in such a way that it reduces checkpointing time overheads. A detailed analytical model is developed for the hybrid technique, and comparisons are made using similar analytical models with periodic and incremental state saving techniques. Results show that when the system parameters are chosen to represent large and complex simulated systems, the hybrid approach has less checkpointing time overhead than the other two techniques     

A NEW ALGORITHM FOR DISCRETE‐TIME SLIDING MODE CONTROL USING INFREQUENT OUTPUT OBSERVATIONS

This paper presents a new approach for sliding‐mode control of discrete‐time systems using the reaching law approach together with periodic output feedback technique. This method does not need the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement. A numerical example is presented to illustrate the design technique.     

Pole-assignment problem for discrete-time linear periodic systems

This paper considers the pole-assignment problem for discrete-time linear periodic systems through the use of linear periodic state-variable feedback control. It is shown that if the N-periodic system with m inputs and n states is completely reachable then the problem can be reduced to the pole-assignment problem for a discrete-time linear invariant system with Nm inputs and n states.     

混沌系统的混合遗传神经网络控制

在小扰动控制技术基础上,将暂态误差预测方法和遗传算法结合起来,提出了一种混合遗传神经网络控制非线性混沌系统的新方法(简称HyGANN).通过增强学习训练,HyGANN可产生控制混沌状态的小扰动时间序列信号,Henon映射的计算机仿真结果表明,它不仅有效镇定混沌周期1,2等低周期轨道,还可成功将高周期混轨道变成期望周期行为.     

Subspace controllability of Boolean networks

Many Boolean control networks contain independent uncontrollable subnetworks, which may affect other nodes; and the rest of the system is called subspace of sub‐controllable states. This paper investigates the problem of subspace controllability under free input sequences, while the presumption that the initial states of those independent subnetworks are designable is canceled. An algorithm based on the common asymptotic periodic properties of the states is developed to find the reachable sets. Accordingly, the existing controllability criteria for subspaces when initial states of subnetworks are designable is improved, and a necessary and sufficient condition of subspace controllability via subnetworks and free inputs is derived. A design technique involving a kind of newly defined addition is presented to construct desired controls.     

单层树型网格下独立任务的周期性调度

提出单层树型网格下单位独立任务的周期性调度方法,单位独立任务是大小相等的独立任务.首先,为单层树型网格下的单位独立任务调度建立线性规划模型,通过分析整数线性规划求解过程,发现一个单层树型网格平台在节点构成不同时,分别具有非饱和态、临界态或冗余态特征;并且,随着网格节点上任务数的增多,线性规划最优解呈线性增长,任务调度具有周期性特性.据此给出非饱和态、临界态或冗余态网格的定义、性质和判定方法,推导出单位独立任务调度的周期长度.最后,分析了周期性调度的时间复杂性,提出一种周期性调度算法Periodic-Sched.实验结果表明,周期性调度是有效的.单位独立任务的周期性调度将大规模的任务调度问题简化为一个周期内的任务调度,降低了调度问题的复杂度.该调度方法适用于对Hadoop平台的Map任务进行调度.     

Global output-feedback stabilization for a class of uncertain time-varying nonlinear systems

This paper investigates the global output-feedback stabilization for a class of uncertain time-varying nonlinear systems. The remarkable structure of the systems is the presence of uncertain control coefficients and unmeasured states dependent growth whose rate is inherently time-varying and of unknown polynomial-of-output, and consequently the systems have heavy nonlinearities, serious uncertainties/unknowns and serious time-variations. This forces us to explore a time-varying plus adaptive methodology to realize the task of output-feedback stabilization, rather than a purely adaptive one. Detailedly, based on a time-varying observer and transformation, an output-feedback controller is designed by skillfully combining adaptive technique, time-varying technique and well-known backstepping method. It is shown that, with the appropriate choice of the design parameters/functions, all the signals of the closed-loop system are bounded, and furthermore, the original system states globally converge to zero. It is worth mentioning that, the heavy nonlinearities are compensated by an updating law, while the serious unknowns and time-variations are compensated by a time-varying function. The designed controller is still valid when the system has an additive input disturbance which, essentially different from those studied previously, may not be periodic or bounded by any known constant.     

Vector field editing and periodic orbit extraction using Morse decomposition

Design and control of vector fields is critical for many visualization and graphics tasks such as vector field visualization, fluid simulation, and texture synthesis. The fundamental qualitative structures associated with vector fields are fixed points, periodic orbits, and separatrices. In this paper, we provide a new technique that allows for the systematic creation and cancellation of fixed points and periodic orbits. This technique enables vector field design and editing on the plane and surfaces with desired qualitative properties. The technique is based on Conley theory, which provides a unified framework that supports the cancellation of fixed points and periodic orbits. We also introduce a novel periodic orbit extraction and visualization algorithm that detects, for the first time, periodic orbits on surfaces. Furthermore, we describe the application of our periodic orbit detection and vector field simplification algorithms to engine simulation data demonstrating the utility of the approach. We apply our design system to vector field visualization by creating data sets containing periodic orbits. This helps us understand the effectiveness of existing visualization techniques. Finally, we propose a new streamline-based technique that allows vector field topology to be easily identified.     

Stability and Control of a Parametrically Excited Rotating System. Part II: Controls

In Part-I of this paper, the stability of a parametrically excited rotating system was analyzed. In this part the design of a feedback controller and an observer for the same mechanical system is considered. First, the time periodic system equations are transformed to a time invariant form which is suitable for an application of the standard techniques of linear control theory. A full-state feedback controller is designed in the transformed domain using the pole placement technique. Next, a Luenberger observer is constructed for estimating the unmeasurable states. Robustness of the observer is tested under the assumption that white noise is present in the measured states. Simulations for several combination of excitation and rotation parameters are provided.     

State probability of a series-parallel repairable system with two-types of failure states

This paper presents a method for the analysis of a series-parallel safety-critical system where the system states can be distinguished into failure-safe and failure-dangerous. The method incorporates the Markov chain and universal generating function technique. In the model considered, both periodic inspection and repair (perfect and imperfect) of system elements are taken into account. The system state distributions and the overall system safety function are derived, based on the developed model. The proposed method is applicable to complex systems for analysing state distributions and it is also useful in decision-making such as determining the optimal proof-test interval or repair resource allocation. An illustrative example is given.     

Attractor switching by neural control of chaotic neurodynamics

Chaotic attractors of discrete-time neural networks include infinitely many unstable periodic orbits, which can be stabilized by small parameter changes in a feedback control. Here we explore the control of unstable periodic orbits in a chaotic neural network with only two neurons. Analytically, a local control algorithm is derived on the basis of least squares minimization of the future deviations between actual system states and the desired orbit. This delayed control allows a consistent neural implementation, i.e. the same types of neurons are used for chaotic and controlling modules. The control signal is realized with one layer of neurons, allowing selective switching between different stabilized periodic orbits. For chaotic modules with noise, random switching between different periodic orbits is observed.     

Detectability of Discrete Event Systems

In this note, we investigate the detectability problem in discrete event systems. We assume that we do not know initially which state the system is in. The problem is to determine the current and subsequent states of the system based on a sequence of observations. The observation includes partial event observation and/or partial state observation, which leads to four possible cases. We further define four types of detectabilities: strong detectability, (weak) detectability, strong periodic detectability, and (weak) periodic detectability. We derive necessary and sufficient conditions for these detectabilities. These conditions can be checked by constructing an observer, which models the estimation of states under different observations. The theory developed in this note can be used in feedback control and diagnosis. If the system is detectable, then the observer can be used as a diagnoser to diagnose the failure states of the system.     

Implementation of repetitive controller for rejection of position-based periodic disturbances

Time-varying periodic motions have appeared in many industrial processes, such as cam-follower systems, in that the control system has to operate at a periodic variable velocity specified in terms of the angular position-domain. This paper employs a repetitive control for rejecting the time-varying periodic disturbances, and presents an implementation technique based on angular position which can generate a fixed number of cycles in real-time. This control technique can accommodate the period variation in a time-varying periodic signal such that variable samples per period for synchronization can be achieved by the regular fixed-time sampling rate. A technique using position information to manipulate the delayed data and an interpolation scheme to properly access data in the buffer memory is proposed. An anti-vibration control system with time-varying periodic disturbances is studied to illustrate control performance. The experimental results are given to illustrate that time-varying repetitive control can effectively eliminate steady-state errors within a few cycles.     

线性离散周期系统满意估计

针对线性离散周期系统的状态估计问题,运用提升原理提取期望极点指标,同时期望估计误差系统满足稳态误差方差/H_∞混合指标,采用代数Riccati矩阵不等式法与数值递推算法对误差系统进行了上述指标的满意估计设计,并根据满意控制的基本理论将上述满意估计问题转化为线性矩阵不等式(LMI)的线性规划问题,从而运用LMI技术求解并设计了可行的满意估计,数值算例验证了相关算法.     

A numerical technique to predict periodic and quasi-periodic response of nonlinear dynamic systems

A frequency domain based algorithm using Fourier approximation and Galerkin error minimization has been used to obtain the periodic orbits of large order nonlinear dynamic systems. The stability of these periodic response is determined through a bifurcation analysis using Floquet theory. This technique is applicable to dynamic systems having both analytic and nonanalytic nonlinearities. This technique is compared with numerical time integration and is found to be much faster in predicting the steady state periodic response.     

Periodic disturbance cancellation with uncertain frequency

This paper presents a new algorithm to cancel periodic disturbances with uncertain frequency. The disturbances are cancelled using an internal model structure with adaptive frequency, in parallel with a stabilizing controller. The time-varying internal model controller's states, in steady state, can be mapped to two time-invariant variables: the magnitude or energy of the internal model and frequency of the disturbance. An additional integral controller then can be used to reduce the difference between the internal model controller (IMC) and disturbance frequency to zero. The stability of the feedback control system with this algorithm and convergence of the algorithm to the correct frequency with exact disturbance cancellation are justified by singular perturbation and averaging theories. The algorithm is locally exponentially stable, rather than asymptotically stable. Simulations demonstrate the performance of the algorithm, the ability of this algorithm to identify the frequency of periodic disturbances and to reject periodic disturbances with uncertain frequency.     

Recursive Harmonic Estimation

Recursive Harmonic Estimation is a technique for modeling almost periodic random processes. A distinguishing feature of this technique is that the number of harmonics which are estimated is predetermined independently of the length of the data interval. Consequently, the Recursive Harmonics (RH) define a small set of features which characterize the waveform. Moreover, under the null hypothesis of a truly periodic waveform the RH have energies which are very sensitive functions of period errors. Hence, they can be used in a recognition scheme to distinguish small periodic aberrations such as might occur in the motion of a faulty rotating machine.     

LMI tools for eventually periodic systems

This paper is focused on the concept of an eventually periodic linear discrete-time system. We derive a necessary and sufficient analysis condition for checking open-loop stability and performance of such systems, and use this to derive exact controller synthesis conditions given eventually periodic plants. All the conditions derived are provided in terms of semi-definite programming problems. The motivation for this work is controlling nonlinear systems along prespecified trajectories, notably those which eventually settle down into periodic orbits and those with uncertain initial states.     

MPC of constrained discrete-time linear periodic systems — A framework for asynchronous control: Strong feasibility, stability and optimality via periodic invariance

State-feedback model predictive control (MPC) of discrete-time linear periodic systems with time-dependent state and input dimensions is considered. The states and inputs are subject to periodically time-dependent, hard, convex, polyhedral constraints. First, periodic controlled and positively invariant sets are characterized, and a method to determine the maximum periodic controlled and positively invariant sets is derived. The proposed periodic controlled invariant sets are then employed in the design of least-restrictive strongly feasible reference-tracking MPC problems. The proposed periodic positively invariant sets are employed in combination with well-known results on optimal unconstrained periodic linear-quadratic regulation (LQR) to yield constrained periodic LQR control laws that are stabilizing and optimal. One motivation for systems with time-dependent dimensions is efficient control law synthesis for discrete-time systems with asynchronous inputs, for which a novel modeling framework resulting in low dimensional models is proposed. The presented methods are applied to a multirate nano-positioning system.