基于预测控制的直接侧向力气动力复合控制方法研究

针对大气层内拦截导弹直接侧向力与气动力复合控制系统设计问题, 首先, 根据发动机的配置建立了复合控制系统模型;其次, 提出了复合控制策略, 包括动态分配算法、直接力控制子系统、气动力控制子系统3部分; 然后, 在考虑两套执行机构动态特性差别的情况下,基于预测控制思想给出了过载误差动态分配算法; 在此基础上, 根据直接侧向力的离散特性, 基于预测控制方法设计了直接力控制规律, 考虑到直接力控制作用对弹体产生的扰动, 基于自抗扰方法设计了气动力子系统; 最后, 通过仿真验证了直接力气动力复合控制策略与方法的有效性.     

A numerical method for an optimal control problem with minimum sensitivity on coefficient variation

In this paper, we consider a class of optimal control problem involving an impulsive systems in which some of its coefficients are subject to variation. We formulate this optimal control problem as a two-stage optimal control problem. We first formulate the optimal impulsive control problem with all its coefficients assigned to their nominal values. This becomes a standard optimal impulsive control problem and it can be solved by many existing optimal control computational techniques, such as the control parameterizations technique used in conjunction with the time scaling transform. The optimal control software package, MISER 3.3, is applicable. Then, we formulate the second optimal impulsive control problem, where the sensitivity of the variation of coefficients is minimized subject to an additional constraint indicating the allowable reduction in the optimal cost. The gradient formulae of the cost functional for the second optimal control problem are obtained. On this basis, a gradient-based computational method is established, and the optimal control software, MISER 3.3, can be applied. For illustration, two numerical examples are solved by using the proposed method.     

基于测量质量损失函数的控制图控制界限的优化

控制界限和抽样间隔是控制图的两个基本参数。常规控制图是基于3σ原理确定的控制界限,该控制界限是在大量试验基础上依据经验确定的,并没有精确的公式推导.对于抽样间隔,常规控制图也没有明确的规定。田口博士的质量损失函数可以很好的解决质量经济性方面的一些问题.利用田口博士的理论,通过确定适宜的二次测量质量损失函数,可以确定控制图的最佳控制界限和最佳抽样间隔.文章简要介绍了常规控制图原理和田口博士的质量损失函数,重点叙述了田口博士反馈控制系统的测量质量损失函数,在此基础上,研究了控制图最佳控制界限和最佳抽样间隔,并且通过具体实例验证了该控制图良好的经济性.     

Robust ISS-satisficing variable universe indirect fuzzy control for chaotic systems

In the conventional robust input to state stable (ISS)-satisficing control system, all parameters of the system must be known beforehand, so the application area is limited. In this paper, an attempt is made to create a bridge between two important design techniques, i.e., the robust ISS-satisficing control strategy and the fuzzy control strategy, and the new control method we first proposed has both the inverse optimality of robust ISS-satisficing control and the robust and predictive performance of fuzzy control. By control Lyapunov method, the overall closed-loop system is shown to be stable. In this work, we combine these two control methods, make them learn from the other’s strong points, offset its weakness. The simulation results are given to confirm the control algorithm is feasible and performances well.     

Sufficient and necessary conditions for absolute stability of time-delayed Lurie control systems

In this paper, we present some sufficient and necessary conditions for the absolute stability of time-delayed Lurie control systems, which improve the results we obtained before for the absolute stability of direct control, indirect control and critical control of Lurie systems. We also derived certain simple and easy applicable algebraic sufficient conditions for the absolute stability of time-delayed Lurie control systems, which provide a convenient tool for practical control engineers in designing absolutely stable systems or stabilizing nonlinear control systems.     

Three control strategies for the Lorenz chaotic system

This paper suggests three strategies of the dislocated feedback control, so that enhancing feedback control and speed feedback control of the Lorenz chaotic system to its unstable equilibrium points can be enhanced. When the coefficients of enhancing feedback control and speed feedback control are smaller than those of ordinary feedback control, the complexity and cost of the system control are reduced. Theoretical analysis and numerical simulation are given, revealing the effectiveness of these strategies.     

On the time transformation of mixed integer optimal control problems using a consistent fixed integer control function

Nonlinear control systems with instantly changing dynamical behavior can be modeled by introducing an additional control function that is integer valued in contrast to a control function that is allowed to have continuous values. The discretization of a mixed integer optimal control problem (MIOCP) leads to a non differentiable optimization problem and the non differentiability is caused by the integer values. The paper is about a time transformation method that is used to transform a MIOCP with integer dependent constraints into an ordinary optimal control problem. Differentiability is achieved by replacing a variable integer control function with a fixed integer control function and a variable time allows to change the sequence of active integer values. In contrast to other contributions, so called control consistent fixed integer control functions are taken into account here. It is shown that these control consistent fixed integer control functions allow a better accuracy in the resulting trajectories, in particular in the computed switching times. The method is verified on analytical and numerical examples.     

Stochastic optimal time-delay control of quasi-integrable Hamiltonian systems

A nonlinear stochastic optimal time-delay control strategy for quasi-integrable Hamiltonian systems is proposed. First, a stochastic optimal control problem of quasi-integrable Hamiltonian system with time-delay in feedback control subjected to Gaussian white noise is formulated. Then, the time-delayed feedback control forces are approximated by the control forces without time-delay and the original problem is converted into a stochastic optimal control problem without time-delay. After that, the converted stochastic optimal control problem is solved by applying the stochastic averaging method and the stochastic dynamical programming principle. As an example, the stochastic time-delay optimal control of two coupled van der Pol oscillators under stochastic excitation is worked out in detail to illustrate the procedure and effectiveness of the proposed control strategy.     

多元自相关过程的VAR控制图

为了解决多元自相关过程的残差T~2控制图对小偏移不灵敏的问题,本文利用批量-均值法的思想,结合VAR模型的渐近分布,设计了多元自相关过程的向量自回归(VAR)控制图.只要子组样本量足够大,VAR控制图可以对过程出现的各种偏移进行有效控制.通过对比残差T~2控制图的控制效果,得出VAR控制图对小偏移灵敏、残差T~2控制图对大偏移灵敏的结论,联合使用VAR控制图和残差T~2控制图可更有效地监控多元自相关过程。     

Event-triggered impulsive control of lower-triangular large-scale nonlinear systems based on gain scaling technique

This paper investigates the event-triggered impulsive control problem for a class of large-scale nonlinear systems in lower-triangular form. Based on gain scaling technique and impulsive control theory, a novel decentralized event-triggered impulsive control strategy is first put forward by introducing a static scaling gain, where no control input exists between two consecutive triggering points. Moreover, when the large uncertainties exist in system nonlinearities, we further develop a new control strategy by introducing a time-varying scaling gain. It is proved that the proposed closed-loop control strategies exclude the Zeno behavior without sacrificing the global convergence of system states. Compared with the existing results, it is the first time to apply impulsive control to lower-triangular large-scale nonlinear systems, and the advantages of event-triggered impulsive control and gain scaling technique are subtly combined in the proposed control strategies. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed schemes.     

从工程应用看模糊逻辑控制

本文简要回顾了模糊控制的历史发展,结合模糊工程实践和新近理论成果,就模糊控制的实质、基本模糊控制模型的局限性、模糊控制与经典控制理论的关系以及可供工程应用的模糊控制方法等发表了看法。     

Suboptimal Control of Time-Varying Neutral Control Systems

In this paper,the optimal control of time-varying neutral control systems is investigated by means of the Maxmium Principle of time-delay systems.optimal control law is given. Then sub-optimal control of time-varying neutral control systems is studied by using sensitivity approach. Algorithm for suboptimal control is given.     

Simplex sliding mode control for nonlinear uncertain systems via chaos optimization

As an emerging effective approach to nonlinear robust control, simplex sliding mode control demonstrates some attractive features not possessed by the conventional sliding mode control method, from both theoretical and practical points of view. However, no systematic approach is currently available for computing the simplex control vectors in nonlinear sliding mode control. In this paper, chaos-based optimization is exploited so as to develop a systematic approach to seeking the simplex control vectors; particularly, the flexibility of simplex control is enhanced by making the simplex control vectors dependent on the Euclidean norm of the sliding vector rather than being constant, which result in both reduction of the chattering and speedup of the convergence. Computer simulation on a nonlinear uncertain system is given to illustrate the effectiveness of the proposed control method.     

基于组合智能控制的柔性臂微机控制系统研究

针对难以控制的柔性机械臂，设计了强鲁棒性、强自适应能力的模糊滑模控制策略；并针对控制对象与控制算法的复杂性，设计了基于DSP＋FPGA的控制系统，保证了系统的实时性和精确度。     

Research on mean square exponential stability of networked control systems with multi-step delay

A new control mode is proposed for networked control systems whose network-induced delay is longer than a sampling period. The proposed control mode can make full use of control information and improve the performance of the system. Under the control mode, the mathematical model of networked control systems is obtained. Markov characteristic of the transfer delay is discussed. Based on Markov chain theory, the infinite horizon controller is designed, which is shown to render corresponding networked control systems mean square exponentially stable. Simulation results show the validity of the proposed theory.     

Algorithms for adaptive stochastic control for a class of linear systems

This paper is concerned with the control of linear, discrete-time, stochastic systems with unknown control gain parameters. Two suboptimal adaptive control schemes are derived: One is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single-input, third-order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known.     

Three Controls are Better than One: A Computational Model of Complex Control Systems

This paper investigates theories that integrate and extend currently accepted agency- and transaction-based approaches to organizational control. We use a computational model to build three forms of control systems (market, bureaucratic, clan) and three forms of control targets (input, behavior, output). Using these models, we examine relationships between control systems and both singular and multiple control targets. Results of this study support the emerging broader perspective on organizational control research and suggest that managers can improve organizational performance by focusing attention on multiple control targets. In addition, findings partially support posited relationships between control systems and singular control targets. The authors suggest that results of this study should direct scholars to refocus control research from examinations of singular forms of control to evaluations of more complex control systems.     

A study on time-limited control of single-pest with stage-structure

Two kinds of time-limited pest control models of single-pest with stage-structure, which can be described by the boundary value problem of ordinary differential equation and impulsive differential equation, are presented according to the ways of artificial control (continuous control and impulsive control). The conditions under which the corresponding model has a solution are given. If the model has a solution, the corresponding aim of pest control can be achieved. The theoretical results show that both the mature and the immature pest should be controlled synchronously, otherwise the aims of pest control can not be achieved in a finite time. Finally, some discussions and numerical simulations show that the impulsive control is more practical than the continuous control.     

创业企业控制权模式选择研究

创业企业家和风险投资家因为控制权模式不合理所导致的矛盾在我国普遍存在。为解决该问题,本文通过研究创业企业家与风险投资家在博弈过程中的控制权策略选择及由此决定的控制权模式,运用演化博弈理论中复制动态的方法分析发现:(1)创业企业家和风险投资家在选择是否争取控制权的博弈结果是联合控制或相机控制;(2)项目成功概率、风险投资家获取的剩余索取权增加时收敛于联合控制,反之则收敛于相机控制;当项目成功的概率大于50%时,固定收益减少收敛于联合控制,创业企业产出增加收敛于联合控制,反则收敛于相机控制。最后,通过CV Source数据库样本数据对模型结论进行了实证检验,检验结果与理论模型的主要结论相一致。研究结论对于指导我国创业企业控制权模式合理选择具有一定的实践意义。     

水泥回转窑的模糊控制模型

水泥回转窑由于其控制量的迟滞性及不敏感性难以用传统的方法进行控制 .本文讨论用模糊控制的方法来模拟水泥回转窑的人工控制