开销敏感的多处理器最优节能实时调度算法

嵌入式多处理器系统的能耗问题变得日益重要,如何减少能耗同时满足实时约束成为多处理器系统节能实时调度中的一个重要问题.目前绝大多数研究基于关键速度降低处理器的频率以减少动态能耗,采用关闭处理器的方法减少静态能耗.虽然这种方法可以实现节能,但是不能保证最小化能耗.而现有最优的节能实时调度未考虑处理器状态切换的时间和能量开销,因此在切换开销不可忽视的实际平台中不再是最优的.文中针对具有独立动态电压频率调节和动态功耗管理功能的多处理器系统,考虑处理器切换开销,提出一种基于帧任务模型的最优节能实时调度算法.该算法根据关键速度来判断系统负载情况,确定具有最低能耗值的活跃处理器个数,然后根据状态切换开销来确定最优调度序列.该算法允许实时任务在处理器之间任意迁移,计算复杂度小,易于实现.数学分析证明了该算法的最优性.     

Control of constrained linear systems using fast sampling rates

This paper addresses the problem of optimal control of constrained linear systems when fast sampling rates are utilised. We show that there exists a well-defined limit as the sampling rate increases. An immediate consequence of this result is the existence of a finite sampling period such that the achieved performance is arbitrarily close to the limiting performance.     

Robust discrete time dynamic average consensus

This paper deals with the problem of average consensus of a set of time-varying reference signals in a distributed manner. We propose a new class of discrete time algorithms that are able to track the average of the signals with an arbitrarily small steady-state error and with robustness to initialization errors. We provide bounds on the maximum step size allowed to ensure convergence to the consensus with error below the desired one. In addition, for certain classes of reference inputs, the proposed algorithms allow arbitrarily large step size, an important issue in real networks, where there are constraints in the communication rate between the nodes. The robustness to initialization errors is achieved by introducing a time-varying sequence of damping factors that mitigates past errors. Convergence properties are shown by the decomposition of the algorithms into sequences of static consensus processes. Finally, simulation results corroborate the theoretical contributions of the paper.     

Robust and perfect tracking of discrete-time systems

We study in this paper the problem of robust and perfect tracking for discrete-time linear multivariable systems. By robust and perfect tracking, we mean the ability of a controller to track a given reference signal with arbitrarily small settling time in the face of external disturbances and initial conditions. A set of necessary and sufficient conditions under which the proposed problem is solvable is obtained and, under these conditions, constructive algorithms are given that yield the required solutions. As is general to discrete-time systems, the solvability conditions to the above problem are quite restrictive. To relax these conditions, we propose an almost perfect tracking scheme, which is capable of tracking references precisely after certain initial steps.     

卫星编队飞行的鲁棒自适应控制方法

研究了主从式框架下编队飞行的相对控制问题.首先推导了描述主从星相对运动的完整非线性动力学模型, 利用完整模型的无摄动形式提出了最优参考轨迹生成问题,并应用高斯伪谱法将此问题转换成非线性规划问题,使其可以数值求解; 基于Lyapunov 方法设计了闭环系统的鲁棒自适应控制器,在存在未知干扰、未知主星轨道参数与控制以及未知从星质量的情况下, 仅利用相对状态测量即能够保证闭环系统的参考轨迹跟踪误差和参数估计误差全局一致最终有界,并证明了跟踪误差的最终界可以 通过选取合理的控制器参数使其任意小;最后给出了具体的仿真场景验证了本文主要结果的有效性.     

On the generalised stock–cutting problem

In this paper, we formulate the two-stage stock-cutting problem, according to which a set of rectangular pieces of prespecified dimensions are to be cut from an arbitrarily shaped object with arbitrarily shaped holes or defective regions. We show how mathematical morphological operators can be used in order to determine the optimal shifting for a given cutting pattern. It is then proved that the problem of obtaining the optimal cutting pattern is -hard and a solution to the unconstrained problem using mathematical programming is proposed. However, for the general problem, good sub-optimal solutions can be obtained using the technique of simulated annealing. Experimental results are also included. Received: 28 July 1997 / Accepted: 25 August 1999     

Linear-quadratic discrete-time control and constant directions

The general linear-quadratic discrete-time minimization problem is studied, in which no restrictions are placed on the singularity or otherwise of certain matrices, or the appearance of cross-product terms in the performance indices. Constant directions are characterized in a number of ways, and an algorithm is presented for replacing a prescribed problem with constant directions by one of lower state and/or control dimension, lacking constant directions. The replacement is achieved using a series of state and input co-ordinate basis changes, and allows simplification of the calculations obtaining the optimal control law and performance index of the original problem.     

Optimal Control of Nonlinear Systems Using Experience Inference Human-Behavior Learning

Safety critical control is often trained in a simulated environment to mitigate risk. Subsequent migration of the biased controller requires further adjustments. In this paper, an experience inference human-behavior learning is proposed to solve the migration problem of optimal controllers applied to real-world nonlinear systems. The approach is inspired in the complementary properties that exhibits the hippocampus, the neocortex, and the striatum learning systems located in the brain. The hippocampus defines a physics informed reference model of the real-world nonlinear system for experience inference and the neocortex is the adaptive dynamic programming (ADP) or reinforcement learning (RL) algorithm that ensures optimal performance of the reference model. This optimal performance is inferred to the real-world nonlinear system by means of an adaptive neocortex/striatum control policy that forces the nonlinear system to behave as the reference model. Stability and convergence of the proposed approach is analyzed using Lyapunov stability theory. Simulation studies are carried out to verify the approach.      

A Survey on the Control Lyapunov Function and Control Barrier Function for Nonlinear-Affine Control Systems

This survey provides a brief overview on the control Lyapunov function(CLF) and control barrier function(CBF) for general nonlinear-affine control systems.The problem of control is formulated as an optimization problem where the optimal control policy is derived by solving a constrained quadratic programming(QP) problem.The CLF and CBF respectively characterize the stability objective and the safety objective for the nonlinear control systems.These objectives imply important properties including...     

Optimal control of linear systems with large and variable input delays

This paper proposes an optimal control law for linear systems affected by input delays. Specifically we prove that when the delay functions are known it is possible to generate the optimal control for arbitrarily large delay values by using a DDE without distributed terms. The solution can be seen as a chain of predictors whose size depends on the maximum delay.     

Terminal sliding mode control of second-order nonlinear uncertain systems

In this paper, a terminal sliding mode control scheme is proposed for second-order nonlinear uncertain systems. By using a function augmented sliding hyperplane, it is guaranteed that the output tracking error converges to zero in finite time which can be set arbitrarily. In addition, the proposed scheme eliminates the reaching phase problem so that the closed-loop system always shows the invariance property to parameter uncertainties. Copyright © 1999 John Wiley & Sons, Ltd.     

Hierarchical Decomposition of Production and Capacity Investment Decisions in Stochastic Manufacturing Systems

This paper is concerned with hierarchical decisions regarding production and investment in capacity in manufacturing systems with production subject to breakdown and repair. The production capacity can be increased by investing continuously in new capacity which is available upon completion. The decision variables are the rates of production and investment in capacity. The investment rate is assumed to have an upper bound. If, as assumed, the rates of breakdown and repair of production equipment are much larger than the rate of discounting of costs, the given problem can be approximated by a simpler problem in which the stochastic production capacity is replaced by the average capacity. Asymptotically optimal controls for the given problem are constructed from nearly optimal controls of the limiting problem. In addition, we analyse the behaviour of the solution as the investment rate is allowed to become arbitrarily large.     

Control of an unstable reaction–diffusion PDE with long input delay

A Smith Predictor-like design for compensation of arbitrarily long input delays is available for general, controllable, possibly unstable LTI finite-dimensional systems. Such a design has not been proposed previously for problems where the plant is a PDE. We present a design and stability analysis for a prototype problem, where the plant is a reaction–diffusion (parabolic) PDE, with boundary control. The plant has an arbitrary number of unstable eigenvalues and arbitrarily long delay, with an unbounded input operator. The predictor-based feedback design extends fairly routinely, within the framework of infinite-dimensional backstepping. However, the stability analysis contains interesting features that do not arise in predictor problems when the plant is an ODE. The unbounded character of the input operator requires that the stability be characterized in terms of the H₁ (rather than the usual L₂) norm of the actuator state. The analysis involves an interesting structure of interconnected PDEs, of parabolic and first-order hyperbolic types, where the feedback gain kernel for the undelayed problem becomes an initial condition in a PDE arising in the compensator design for the problem with input delay. Space and time variables swap their roles in an interesting manner throughout the analysis.     

Leader‐following attitude consensus of multiple uncertain spacecraft systems subject to external disturbance

The attitude consensus problem of multiple rigid spacecraft systems is one of the key issues in spacecraft formation flying and has been extensively studied. In this paper, we further consider the leader‐following attitude consensus problem of multiple rigid uncertain spacecraft systems subject to a class of multi‐tone sinusoidal disturbances with arbitrarily unknown amplitudes, initial phases, frequencies, and constant biases. In contrast to the existing results, in order to achieve asymptotic reference tracking and disturbance rejection by smooth control, we have integrated the distributed observer approach with internal model and adaptive control techniques. Simulation results are shown to validate the effectiveness of the proposed control law. Copyright © 2016 John Wiley & Sons, Ltd.     

An Optimal Tracking Performance of MIMO NCS with Quantization and Bandwidth Constraints

This paper presents an optimal tracking performance of multiple‐input multiple‐output (MIMO) networked control systems (NCSs) with quantization and bandwidth constraints. In this study, we simultaneously consider the encoding‐decoding, quantization and bandwidth of communication channel. The optimal tracking performance of NCSs is obtained by spectral factorization technique and partial fraction. The obtained results demonstrate that the optimal tracking performance is influenced by the nonminimum phase zeros and unstable poles as well as their directions for a given plant. In addition, it is shown that characteristics of reference signal, encoding‐decoding, quantization, and bandwidth of communication channel are also closely related to tracking performance. Finally, the efficiency of proposed tracking performance is verified by typical examples.     

A DIRECT APPROACH TO THE DESIGN OF ROBUST TRACKING CONTROLLERS FOR UNCERTAIN DELAY SYSTEMS

The robust tracking and model following problem of linear uncertain time‐delay systems is investigated in this paper. By using the solution of the algebraic Riccati equation, this paper presents a direct approach to the design of robust tracking controllers. The system is controlled to track dynamic inputs generated from a reference model. In the case of matched uncertainties, the proposed controller ensures uniform ultimate boundedness of tracking errors and, furthermore, the bounds can be made arbitrarily small. In the case of mismatched uncertainties, a sufficient condition is presented such that the controller guarantees uniform ultimate boundedness of tracking errors. Compared with existing results, the main feature of the approach proposed in this paper is that it does not require any precompensator even for the non‐Hurwitz nominal system and, obviously, it is a direct method. It also employs linear controllers rather than nonlinear ones. Therefore, the designing method is simple for use and the resulting controller is easy to implement. Numerical examples show that this scheme can accommodate larger uncertainties and is likely to produce less conservative results.     

Adaptive tracking of switched nonlinear systems with prescribed performance using a reference-dependent reparametrisation approach

In this paper, adaptive tracking control of switched nonlinear systems in the parametric strict-feedback form is investigated. After defining a reparametrisation lemma in the presence of a non-zero reference signal, we propose a new adaptive backstepping design of the virtual controllers that can handle the extra terms arising from the reparametrisation (and that the state-of-the-art backstepping designs cannot dominate). The proposed adaptive design guarantees, under arbitrarily fast switching, an a priori bound for the steady-state performance of the tracking error and a tunable bound for the transient error. Finally, the proposed method, by overcoming the need for subsystems with common sign of the input vector field, enlarges the class of uncertain switched nonlinear systems for which the adaptive tracking problem can be solved. A numerical example is provided to illustrate the proposed control scheme.     

Optimal solution and approximation to thel1/H∞ control problem

This paper addresses the l₁/H_∞ optimal control problem for a system described by linear time-invariant finite dimensional discrete-time equations. It is shown that a solution to this problem exists and can be approximated arbitrarily by real-rational transfer matrices. Perhaps more interesting from a computational point of view, a bound on the order of a δ-suboptimal solution is also given     

线性时滞系统基于观测器的最优输出跟踪控制器近似设计

研究线性时滞系统的最优输出跟踪控制器近似设计过程.首先根据原系统最优输出跟踪控制问题构造了两个分别具有已知初始条件和终端条件的微分方程迭代序列,并证明它们一致收敛于原问题的最优解.然后通过对该解序列的有限次迭代,得到最优输出跟踪控制问题的一个近似解,进一步给出一个计算近似最优输出跟踪控制律的算法.最后通过构造降维参考输入观测器解决了最优输出跟踪控制器中前馈项的物理可实现问题.仿真结果表明该方法是有效的,且易于实现.     

Adaptive learning control of linear systems by output error feedback

This paper addresses the problem of designing an output error feedback tracking control for single-input, single-output uncertain linear systems when the reference output signal is smooth and periodic with known period T. The considered systems are required to be observable, minimum phase, with known relative degree and known high frequency gain sign. By developing in Fourier series expansion a suitable unknown periodic input reference signal, an output error feedback adaptive learning control is designed which ‘learns’ the input reference signal by identifying its Fourier coefficients: bounded closed-loop signals and global exponential tracking of both the input and the output reference signals are obtained when the Fourier series expansion is finite, while global exponential convergence of the input and output tracking errors into arbitrarily small residual sets is achieved otherwise. The structure of the proposed controller depends only on the relative degree, the reference signal period, the high frequency gain sign and the number of estimated Fourier coefficients.