基于干扰估计的高超声速飞行器鲁棒控制方法

针对高超声速飞行器高度与速度跟踪所面临的参数不确定与外界干扰问题,提出基于干扰估计的鲁棒控制律设计方法。首先建立含参数不确定与外界干扰的高超声速飞行器模型;而后基于动态逆思想,将动力学模型进行线性化,并将由参数不确定与外界干扰对系统造成的总效果看作系统总干扰,从而引入线性扩张状态观测器实现对系统状态及总干扰的估计;最后考虑总干扰作用,提出具有鲁棒性能的动态逆控制律与滑模控制律。通过与传统控制律进行对比仿真,结果表明所设计的两种鲁棒控制器只需在原有方法基础上进行简单改进,即可较大程度提高对系统参数不确定与外界干扰的鲁棒性,具有良好的跟踪性能。     

基于H∞鲁棒动态逆的飞行器轨迹跟踪方法

利用非线性动态逆方法的精确线性化功能,结合H_∞控制理论,提出了一种阻力加速度能量标准轨迹的跟踪方法。通过动态逆将非线性的高超声速飞行器系统等效为线性对象,继而考虑非结构不确定性及参数不确定性,采用H_∞控制理论设计外回路鲁棒控制器,实现了标准轨迹的精确跟踪,同时给出了闭环系统的鲁棒稳定性证明。仿真结果验证了该方法的有效性。     

非线性中立型控制系统的鲁棒稳定与鲁棒镇定

研究了一类不确定性的非线性中立型动态系统,系统具有多重时不变状态时滞。其不确定性满足范数有界条件。采用LyapunovV泛函的方法。建立了一类Lyapunov泛函。通过对控制系统(B,D,C)的分析,得出只要矩阵对(B,D)是完全可控的,或者是可稳定的,则在相应的条件下便得出相应的非线性中立型动态控制系统及滞后型动态系统可镇定的充分条件。建立了非线性中立型微分系统的时滞无关的渐近稳定性判别条件,以及非线性中立型动态控制系统的时滞无关鲁棒镇定的判据。同时,给出了相应的非线性滞后微分系统的时滞无关鲁棒稳定性的判据,以及非线性滞后动态控制系统的时滞无关鲁棒镇定性的代数判据。     

飞行转台Backstepping与神经网络并行控制

阐述了飞行仿真转台的Backstepping设计方法及步骤。在Backstepping鲁棒控制的基础上,提出了一种Backstepping鲁棒控制和神经网络并行控制的方案,以Backstepping鲁棒控制为主控制器,神经网络进行动态误差补偿。Backstepping鲁棒控制克服了对象的不确定性,保障系统的鲁棒性;神经网络可以进一步提高系统的跟踪精度。仿真表明,这种方法实现了Backstepping鲁棒控制和神经网络控制的完美结合,很适合高精度飞行仿真转台系统的鲁棒控制。     

Robust decentralized H∞ control of multi-channel systems with norm-bounded parametric uncertainties

A robust decentralized H∞ control problem for uncertain multi-channel systems is considered. The uncertainties are assumed to be time-invariant, norm-bounded, and exist in both the system and control input matrices. The dynamic output feedback is mainly dealt with. A necessary and sufficient condition for the uncertain multi-channel system to be stabilized robustly with a specified disturbance attenuation level is derived based on the bounded real lemma, which is reduced to a feasibility problem of a nonlinear matrix inequality (NMI). A two-stage homotopy method is used to solve the NMI iteratively. First, a decentralized controller for the nominal system with no uncertainty is computed by imposing structural constraints on the coefficient matrices of the controller gradually. Then the decentralized controller is modified, again gradually, to cope with the uncertainties. On each stage, a variable is fixed alternately at the iterations to reduce the NMI to a linear matrix inequality (LMI). A given example shows the efficiency of this method.     

推广匹配非线性系统变结构鲁棒自适应控制

对于一类不确定非线性系统 ,利用推广匹配条件对系统进行反馈线性化 ,将系统变换成一个具有n-2个积分链和两个含有未知参数和不确定项的方程的非线性系统。在利用极点配置法给出鲁棒自适应滑动模态超平面设计的基础上 ,提出了变结构鲁棒自适应控制律的设计方法 ,并将所提出的设计方法应用于下摆加驱动电机系统的控制律。经仿真研究表明 ,控制效果令人满意。     

Robust H∞ control for neutral stochastic uncertain systems with time-varying delay

The problem of robust H∞ control for uncertain neutral stochastic systems with time-varying delay is discussed.The parameter uncertaintie is assumed to be time varying norm-bounded.First,the stochastic robust stabilization of the stochastic system without disturbance input is investigated by nonlinear matrix inequality method.Then,a full-order stochastic dynamic output feedback controller is designed by solving a bilinear matrix inequality(BMI),which ensures a prescribed stochastic robust H∞ performance level for the resulting closed-loop system with nonzero disturbance input and for all admissible uncertainties.An illustrative example is provided to show the feasibility of the controller and the potential of the proposed technique.     

基于神经网络的自由漂浮空间机器人鲁棒控制

针对带有模型误差及外界扰动的自由漂浮空间机器人轨迹跟踪问题,提出了一种基于神经网络的自适应鲁棒控制策略。采用对神经网络状态空间进行划分后与滑模变结构结合的控制器,对不确定非线性进行自适应学习,逼近误差作为外部干扰由鲁棒控制器消除。该方法从整个闭环系统的稳定性出发,利用H_∞理论设计的鲁棒控制器及神经网络权值的在线调整规则保证了系统的稳定性,并能使系统L2增益小于给定的指标,具有较好的控制精度及动态特性。仿真分析进一步证明了该自适应鲁棒控制算法的有效性。     

Robust H∞ control for neutral stochastic uncertain systems with time-varying delay

The problem of robust H∞ control for uncertain neutral stochastic systems with time-varying delay is discussed. The parameter uncertaintie is assumed to be time varying norm-bounded. First, the stochastic robust stabilization of the stochastic system without disturbance input is investigated by nonlinear matrix inequality method. Then, a full-order stochastic dynamic output feedback controller is designed by solving a bilinear matrix inequality (BMI), which ensures a prescribed stochastic robust H∞ performance level for the resulting closed loop system with nonzero disturbance input and for all admissible uncertainties. An illustrative example is provided to show the feasibility of the controller and the potential of the proposed technique.     

Robust decentralized H∞ control of multi-channel systems with norm-bounded parametric uncertainties

A robust decentralized H∞ control problem for uncertain multi-channel systems is considered. The uncertainties are assumed to be time-invariant, norm-bounded, and exist in both the system and control input matrices. The dynamic output feedback is mainly dealt with. A necessary and sufficient condition for the uncertain multi-channel system to be stabilized robustly with a specified disturbance attenuation level is derived based on the bounded real lemma, which is reduced to a feasibility problem of a nonlinear matrix inequality (NMI). A two-stage homotopy method is used to solve the NMI iteratively. First, a decentralized controller for the nominal system with no uncertainty is computed by imposing structural constraints on the coefficient matrices of the controller gradually. Then the decentralized controller is modified, again gradually, to cope with the uncertainties. On each stage, a variable is fixed alternately at the iterations to reduce the NMI to a linear matrix inequality (LMI). A given example shows the efficiency of this method.     

不确定关联时滞大系统鲁棒可靠控制设计方法

针对一类具有状态时滞和参数不确定性的不确定关联时滞大系统 ,提出了一种基于状态观测器的鲁棒可靠控制器设计方法。该方法通过求解一组线性矩阵不等式 (LMI) ,给出状态观测器和线性动态输出反馈控制器的设计方法。该控制器对于系统中任意容许的不确定性以及在每一个子系统中预先指定的执行器子集合执行器的失效 ,都可以镇定相应的闭环系统。通过仿真实验证明该设计方法的有效性。     

基于子系统重构的鲁棒滤波算法及其应用

复杂环境下航天器姿态确定系统存在系统参数不确定性,并且可能存在观测数据的间断丢失情况.对此,本文研究了一种新的鲁棒滤波算法.该算法采用线性预测子系统重构补偿丢失的观测信号,并利用其参与到测量更新阶段,采用极小极大理论推导出具有观测数据丢失的不确定性系统的鲁棒状态估计的递推形式.将该方法用于复杂环境下的航天器姿态确定系统中,通过仿真验证了算法的有效性.     

基于神经网络的机械臂分散自适应跟踪控制

提出了一种适用于机械臂的基于神经网络的分散自适应轨迹跟踪控制方法。将机械臂的轨迹跟踪控制系统考虑为由多个非线性关联组成的不确定性复杂系统,采用分散控制方法进行控制器设计。在对每一子系统设计控制器时,采用直接反馈线性化,利用控制器构建伪线性系统,并引入神经网络自适应环节消除干扰、关联及逼近误差,从而使所提出的控制方法能够保证系统状态有较高的跟踪精度,且算法简单,易于实现。仿真表明,该算法能保证较高的跟踪效果。     

线性不确定系统的鲁棒容错H∞控制设计

研究了线性不确定系统的鲁棒容错H∞控制问题.当系统既有状态滞后,又有控制输入滞后,而且状态和控制输入的不确定项均满足匹配条件时,运用线性矩阵不等式(LMI)方法,提出了一种针对不确定系统的鲁棒容错反馈控制设计方法.利用该方法设计的闭环系统,不仅在传感器发生故障时具有完整性,而且对于系统的参数不确定性具有鲁棒性.以设计实例及仿真结果验证了这种方法的有效性.     

Robust data envelopment analysis based MCDM with the consideration of uncertain data

The application of data envelopment analysis (DEA) as a multiple criteria decision making (MCDM) technique has been gaining more and more attention in recent research. In the practice of applying DEA approach, the appearance of uncertainties on input and output data of decision making unit (DMU) might make the nominal solution infeasible and lead to the efficiency scores meaningless from practical view. This paper analyzes the impact of data uncertainty on the evaluation results of DEA, and proposes several robust DEA models based on the adaptation of recently developed robust optimization approaches, which would be immune against input and output data uncertainties. The robust DEA models developed are based on input-oriented and outputoriented CCR model, respectively, when the uncertainties appear in output data and input data separately. Furthermore, the robust DEA models could deal with random symmetric uncertainty and unknown-but-bounded uncertainty, in both of which the distributions of the random data entries are permitted to be unknown. The robust DEA models are implemented in a numerical example and the efficiency scores and rankings of these models are compared. The results indicate that the robust DEA approach could be a more reliable method for efficiency evaluation and ranking in MCDM problems.     

基于干扰估计的BTT导弹鲁棒方差姿态控制

针对存在非线性和不确定性的倾斜转弯(bank-to-turn, BTT)导弹姿态控制问题,提出基于干扰估计的鲁棒方差控制方法。将姿态运动中非线性项和不确定项作为总干扰,采用干扰观测器进行估计,并引入控制系统进行补偿。干扰观测器的观测误差作为BTT导弹姿态运动的干扰输入,为了保证控制系统具有良好的动态和稳态性能,采用鲁棒方差控制理论设计了线性反馈控制器,将闭环极点配置在特定圆盘区域,同时将状态变量的稳态方差保持在给定的范围内。仿真结果表明,所提出的鲁棒方差姿态控制器能够保证良好的控制效果,鲁棒性强。     

一种解决全球地形绘制抖动问题的方法

抖动问题是大规模虚拟场景经常遇到的一个问题,它会导致场景绘制出现非常严重的错误。全球地形环境是一个典型的大场景系统,因此也会遇到抖动问题。针对全球地形环境中的抖动问题,我们改进目前的动态局部坐标系统反抖动方法,提出一种更合适全球地形环境的新反抖动方法。这种方法使用视点在球面上的投影点代替视点作为动态局部坐标系统的原点,使得地形顶点有更高地精度。经过实验证明,这种方法比以视点为原点的反抖动方法有更好地反抖动效果。     

基于T-S模糊模型的混沌系统鲁棒控制器设计

研究具有参数不确定混沌系统基于T S(Takagi Sugeno)模糊模型的鲁棒控制器设计。首先利用IF THEN模糊规则把不确定非线性系统的状态空间分成不同的区域,构建具有参数不确定性的T S模糊模型;然后提出使得系统在平衡点渐近稳定的鲁棒模糊控制器设计。该方法通过解一组线性矩阵不等式分别设计局部控制器,通过并行分布补偿的方法设计T S模糊系统的鲁棒控制器,渐近稳定性的条件更为宽松,能够有效降低鲁棒控制器设计的保守性。最后以Lorenz混沌系统为例,研究混沌系统的鲁棒控制器设计,仿真研究结果表明所设计的鲁棒控制器对参数不确定Lorenz混沌系统具有良好的控制效果。     

考虑滞回非线性的飞行姿态backstepping全局滑模控制

针对存在不确定性和滞回非线性的三代战机姿态稳定控制问题,提出一种基于非线性干扰观测器的backstepping全局滑模控制策略。利用非线性干扰观测器对系统不确定性和滞回非线性部分进行观测补偿,取消了不确定项变化缓慢的限制条件。借鉴动态面控制思想,引入一阶滤波器降低了backstepping控制器的复杂程度。利用Lyapunov定理证明了系统的稳定性。仿真结果表明了该控制方案对不确定干扰的有效抑制和闭环系统良好的跟踪性能。     

Adaptive Robust Control for A Class of Nonlinear Systems with Unknown Uncertainties

CONTROL THEORY AND APPLICATION1. INTRODUCTIOnThe practical systems inevitably contain some kinds of uncertain elements. With the existence of uncertainties,the performance of systems may be changed, even may cause the systems stableless. Under such imperfectknowledge of the model, controllers are tried to design so that the controlled system has certain satisfactoryproperties. In the past, robust controller design generally hinges on three main assumptions: 1) the systemstate ve…