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In recent years Monte Carlo method has been more and more widely used in solving a variety of engineering problems which are difficult to solve with other mathematical methods. In Refs. [1] [2] the principles of Monte Carlo method generation of random variables, test of random variables, and applica- tion of the Monte Carlo method in some areas are discussed. In Ref. [3] Monte Carlo method is used to study system reliability in frequency domain, but not all nonlinear effects were considered; as a result this... In recent years Monte Carlo method has been more and more widely used in solving a variety of engineering problems which are difficult to solve with other mathematical methods. In Refs. [1] [2] the principles of Monte Carlo method generation of random variables, test of random variables, and applica- tion of the Monte Carlo method in some areas are discussed. In Ref. [3] Monte Carlo method is used to study system reliability in frequency domain, but not all nonlinear effects were considered; as a result this approximate method would very likely introduce big errors. When we consider the nonlinear effects in a nonlinear system, how to analyse system reliability in frequency domain is a problem. The classical method which is used to study the nonlinear system is the describing-function method. This method is a graphical method which fails to analyse systems in which there are several nonlinear elements. In order to analyse the stability of tactical missile control system, in this paper we use a new method which combines Monte Carlo method with functions describing the characteristics of nonlinear elements. In the method the amplitude, X, of the input signal, Χsinωt, in the describing function is simulated by uniformly distributed random variables in the interal (a,b) which is so chosen that the value of amplitude may occur in both the linear range and the nonlinear range. In the course of missile flight, the control system is influenced by a variety of random disturbances. The disturbances often cause random variations of system parameters. Real values always deviate from normal values either computed or obtained from tests. Therefore, we use random variables for simulating these parameters. When there are not enough data for determining the statiscal characteristics of the random deviations, we can in most cases consider that these deviations belong to the standard normal distribution, N(0,σ). In this paper, we take an early tactical missile guidance system as an example. The calculated results show that Monte Carlo method combined with the describing functions of nonlinear element is a very powerful method in the stability analysis of missile control systems with significant nonlinearties. Because in the method not only nonlinearities of control system but also random variations of system parameters are considered, results obtained are more reliable than those obtained by using traditional methods. 本文采用蒙特卡罗法与描述函数相结合的方法,在频域内研究了含有非线性环节的导弹控制系统稳定性。这种分析方法与传统的稳定性分析法相比,所得结论更为可靠。 This paper presents an identification algorithm with auto-regulation forgetting factor for fast time-varying systems. This algorithm is based on Ref[l,2] and perfectly improves the method for choosing forgetting factor, and in the algorithm the auto-regulation factor is introduced so as to cope with parameter estimation of fast time varying systems such as missile control system, etc., Digital simulation results show that this algorithm is satisfactory for identifying the parameters which change in the form... This paper presents an identification algorithm with auto-regulation forgetting factor for fast time-varying systems. This algorithm is based on Ref[l,2] and perfectly improves the method for choosing forgetting factor, and in the algorithm the auto-regulation factor is introduced so as to cope with parameter estimation of fast time varying systems such as missile control system, etc., Digital simulation results show that this algorithm is satisfactory for identifying the parameters which change in the form of some typical functions (e.g., exponential, slide, step, sine, square or their combination). 本文介绍了一种自动调整遗忘因子的快速时变参数辨识方法.这种方法主要是在文献[1,2]的基础上改进了遗忘因子的选取方法,引入了自动调整遗忘因子,以适应导弹控制系统等快速时变系统的参数估计要求.数字仿真结果表明,这种辨识方法对于诸如参数的指数变化、斜坡变化、阶跃变化、正弦变化、方波变化以及由这些变化形式构成的混合变化,都有比较好的辨识效果. The generalized predictive contrller ( GPC) appears to be more robust than conventional adaptive controller in dealing with systems having varying and / or mismodelled dynamics. In this paper, a robust GPC law is combined with a robust parameter estimator to provide a practical adaptive control algorithm, which is applied to a ground air missile autopilot control system having fast time-varying dynamics. The influence of design and tuning parameters on the controller performance is analysed for setpoint tracking... The generalized predictive contrller ( GPC) appears to be more robust than conventional adaptive controller in dealing with systems having varying and / or mismodelled dynamics. In this paper, a robust GPC law is combined with a robust parameter estimator to provide a practical adaptive control algorithm, which is applied to a ground air missile autopilot control system having fast time-varying dynamics. The influence of design and tuning parameters on the controller performance is analysed for setpoint tracking and disturbance rejestion, Aband-pass estimator filter and a controller filter are introduced into the GPC strategy for the purpose of improving the reliability of parameter estimation, providing robustness to model-plant mismatch and tailoring the rejection of disturbances, thus reducing the possibility of input oscillations and indeed saturation. Simulation results illustrate the good performance and the excellent properties of the presented control scheme, particularly its ability to cope with varying and mismodelled dynamics, variations of model order and high level disturbances. 将一种新的广义预测自适应控制算法应用于快速时变的导弹控制系统设计中。讨论了设计参数对控制系统性能的影响;针对自适应控制信号过大,提出了改进方案,增强了系统的鲁棒性和抗干扰能力。大量的数字仿真结果表明:运用该方案设计的导弹控制系统具有很好的跟踪性能和强的抗干扰能力;对系统阶次、参数、时延和采样周期的变化具有很强的鲁棒性;自适应算法中,对验前知识要求少,实现起来也比较简单。
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