基于神经网络的鲁棒自适应逆飞行控制

提出基于在线神经网络的超机动飞行自适应动态逆鲁棒控制方法.超机动飞行的基本控制律采用非线性动态逆方法设计,对于建模误差或者控制面损伤等因素导致的不确定性逆误差采用神经网络进行自适应补偿.通过动态逆控制律简化计算和飞机控制面故障自适应修复的仿真表明,神经网络通过在线补偿逆误差,能够有效降低非线性动态逆对模型准确性的要求,增强控制系统的鲁棒性.     

基于参数估计误差的鲁棒自适应律设计及验证

针对传统自适应控制系统设计的自适应律参数收敛慢进而影响控制系统瞬态性能的问题,研究一类新的基于参数估计误差修正的鲁棒自适应律设计.首先引入滤波操作给出参数估计误差的提取方法,构建出含参数估计误差修正项的自适应律,进而将该自适应律用于控制器设计和分析中,可同时实现控制误差和参数估计误差指数收敛.对比分析了几类传统自适应律和所提出自适应律的收敛性和鲁棒性,并给出了保证参数收敛所需持续激励条件的一种直观、简便的在线判别方法.数值仿真及基于自制三自由度直升机系统俯仰轴实验结果表明,基于参数误差修正的自适应律及控制器可得到优于传统自适应方法的跟踪控制和参数估计性能.     

一类多变量非线性系统的自适应模糊控制

对一类不确定多变量非线性系统提出了自适应模糊控制方法.该方法采用模糊逻辑系统组成的矩阵逼近控制器中的逆矩阵以避免控制器的奇异性问题,同时用误差补偿项对模糊逻辑系统的逼近误差进行补偿.证明该方法不但能使闭环系统的所有信号有界,而且通过适当调整控制器及自适应律中设计参数,可使跟踪误差收敛到原点的小邻域内.仿真结果验证了方法的有效性.     

严格反馈随机非线性系统的自适应逆最优控制

讨论了自适应逆最优控制问题可解定理，基于Ito微分规则和Backstepping方法，给出了具有标准Wiener噪声扰动和未知定常参数的严格反馈随机非线性系统的全局依概率渐近稳定和自适应逆最优控制策略的设计方法，该方法可同时获得控制律和自适应律。仿真结果表明了控制算法的有效性。     

基于自适应逆的鲁棒容错飞行控制方法研究

研究飞行安全控制问题,可采用动态逆与神经网络模型参考自适应控制理论相结合,对飞机纵向自适应鲁棒容错飞行控制律进行设计,同时采用改进的粒子群算法优化神经网络参数,提高了自适应算法的效率.控制策略采用内-外环的控制结构,内控制回路以逆控制消除系统的非线性性和输出耦合;外控制回路基于模型参考自适应控制的思想,利用改进粒子群优化的神经网络设计前向自适应控制器,以消除逆控制的建模误差和对参数变化敏感的缺点,可使系统获得较好的动态性能和较强的鲁棒性.仿真结果表明采用的自适应鲁棒容错飞行控制方法有效抑制了操纵面故障,消除了对飞行任务的不良影响,保证了安全性能.     

基于鲁棒模糊控制理论的BTT导弹动态逆控制

将模糊控制理论应用于BTT导弹动态逆系统控制中,设计了BTT导弹控制系统鲁棒模糊控制器.首先应用动态逆系统方法设计BTT导弹控制器,然后用参数化线性模糊逻辑系统逼近动态逆控制器中的不确定项,并设计了自适应律以调整参数的变化,最后根据Lyapunov稳定性定理,证明了所提出的方法能保证BTT导弹控制系统是渐近稳定的,系统的跟踪误差将收敛到零.仿真结果表明,设计的控制器,对参数和外界扰动等不确定因素具有较强的鲁棒性和自适应性.     

具有不确定Wiener噪声随机非线性系统的自适应逆最优控制

针对一类具有不确定Wiener噪声扰动和未知定常参数的随机非线性系统,采用随 机微分方程描述系统,基于Backstepping算法,利用随机控制Lyapunov函数,研究了自适 应逆最优控制问题的可解定理,系统地给出了全局依概率渐近稳定和自适应逆最优控制策略 的设计方法.这种方法可同时获得控制律和自适应律,仿真结果表明该控制算法的有效性.     

具有不确定噪声的随机非线性系统的鲁棒自适应跟踪

研究了一类随机非线性系统的鲁棒自适应跟踪问题.文中利用随机控制Lyapunov设计方法,对于受方差不确定Wiener噪声干扰的参数严格反馈形式的系统,给出了参数自适应律和控制律,使得跟踪误差在4次均方意义下收敛到一个小范围内.     

非线性离散时间系统的自适应模糊补偿控制

针对一类非线性离散时间系统,提出一种自适应模糊逻辑补偿控制方案.控制律由跟踪控制律和逼近误差补偿控制律两部分组成,利用模糊逻辑系统对系统参数扰动和外界干扰进行自适应补偿,由模糊滑模控制律实现对模糊逻辑系统逼近误差的进一步补偿.所设计的控制器可保证闭环系统一致最终有界.将该控制器用于月球探测车动态转向系统中,仿真结果表明了该方法的有效性.     

基于Duhem前馈逆补偿的压电陶瓷迟滞非线性 自适应滑模控制

针对压电陶瓷的动态迟滞非线性,研究了基于Duhem逆模型前馈补偿的滑模自适应控制策略。首先,利用多项式逼近Duhem模型中的未知分段函数ｆ(.)和ｇ(.),采用递推最小二乘法进行系统辨识,并求取逆模型,将其作为前馈控制器,考虑压电陶瓷迟滞非线性随输入信号频率变化,且难以完全抵消,模型参数存在不确定性等问题,设计一种自适应滑模控制律。利用Lyapunov稳定性定理及仿真实验证明了该控制律可以使系统全局渐进稳定。最后,进行了压电陶瓷迟滞补偿实验和位移跟踪实验。实验结果表明,前馈逆补偿控制下的压电陶瓷位移迟滞量减小了96.1％,与直接控制相比,前馈逆补偿控制下位移跟踪的最大绝对误差减小了27.0％,平均绝对值误差减小了17.9％,具有更好的跟踪精度和动态性能。     

A study on optimal motion of a biped locomotion machine

In this paper we propose a calculation method for the optimal trajectory of a biped locomotion machine which is based on inverse kinematics and inverse dynamics. First, the trajectory of the waist is expressed by a Fourier series, where the bases are selected appropriately so that the periodic boundary conditions are strictly satisfied. A biped locomotion machine establishes optimal walking by using kicking forces to the ground at the moment of switching legs. In order to include the effecs of the kicking forces, additional terms that indicate the impulsive forces at the moment of switching legs are included in the formulation. Then the angles of each joint are determined by inverse kinematics, and using inverse dynamics, the input torques of each joint are expressed in terms of Fourier coefficients. By defining the performance index as a quadratic form of the input torques, the motion planning problem is formulated as an optimization problem of the trajectory of the waist, whose paramaters are Fourier coefficients of the trajactory of the waist. Using the successive quadratic programming (SQP) method, the optimal trajectory of a biped locomotion machine is obtained. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998.     

A constructive approach for an optimal control applied to a class of nonlinear time delay systems

In this contribution, we obtain a nonlinear controller for a class of nonlinear time delay systems, by using the inverse optimality approach. We avoid the solution of the Hamilton Jacobi Bellman type equation and the determination of the Bellman's functional by extending the inverse optimality approach for delay free nonlinear systems to time delay nonlinear systems. This is achieved by combining the Control Lyapunov Function framework and Lyapunov-Krasovskii functionals of complete type. Explicit formulas for an optimal control are obtained. The efficiency of the proposed method is illustrated via experimental results applied to a dehydration process whose model includes a delayed state linear part and a delayed nonlinear part. To give evidence of the good performance of the proposed control law, experimental comparison against an industrial Proportional Integral Derivative controller and optimal linear controller. Additionally experimental robustness tests are presented.     

Stability margins of nonlinear optimal regulators with nonquadratic performance criteria involving cross-weighting terms

In this paper we derive guaranteed gain, sector, and disk margins for nonlinear optimal and inverse optimal regulators that minimize a nonlinear-nonquadratic performance criterion involving cross-weighting terms. Specifically, sufficient conditions that guarantee gain, sector, and disk margins are given in terms of the state, control, and cross-weighting nonlinear-nonquadratic weighting functions. The proposed results provide a generalization of the “meaningful” inverse optimal nonlinear regulator stability margins as well as the classical linear-quadratic optimal regulator gain and phase margins.     

On adaptive inverse dynamics for free-floating space manipulators

This paper is devoted to the investigation of adaptive inverse dynamics for free-floating space manipulators (FFSMs) suffering from parameter uncertainties/variations. To overcome the nonlinear parametric problem of the dynamics of FFSMs, we introduce a new regressor matrix called the generalized dynamic regressor. Based on this regressor, and with Lyapunov stability analysis tools, we obtain a new parameter adaptation law and show that the closed-loop system is stable, and that the joint tracking errors converge asymptotically to zero. Simulation results are provided to illustrate the performance of the proposed adaptive algorithm. Furthermore, we conduct a comparative study between adaptive inverse dynamics, prediction error based adaptation, and passivity based adaptation.     

Adaptive Inverse Control of Excitation System with Actuator Uncertainty

In this paper, we present a new approach of designing adaptive inverse controller for synchronous generator excitation system containing nonsmooth nonlinearities in actuator device. The proposed controller considers not only the dynamics of generator but also nonlinearities in actuator. To address such a challenge, support vector machines (SVM) is adopted to identify the plant and to construct the inverse controller. SVM networks, used to compensate nonlinearities in synchronous generator as well as in actuator, are adjusted online by an adaptive law via back propagation (BP) algorithm. To guarantee convergence and for fast learning, adaptive learning rate and convergence theorem are developed. Simulation results are given, showing satisfactory control performance and illustrate the potential of the proposed adaptive inverse controller as useful for practical purpose.     

同步发电机自适应最优励磁控制

本文针对线性最优励磁控制的缺陷,将自适应控制理论与最优控制理论相结合,通过多变量参数辨识、最优反馈系数计算和控制算法运算三个环节,实现了同步发电机励磁的自适应最优控制.数字仿真实验结果表明,该励磁控制系统能够自动跟踪系统运行工作状况,在线辨识不断变化的系统参数,使控制作用始终处于最优状态,从而改善了控制系统的动态品质,提高了系统的暂态稳定性.     

Optimal blank design based on finite element method for blades of large Francis turbines

Metal pressing process that is widely used in industries has advantages over casting process for producing large Francis turbine blades from thick plates. Prior to the pressing process, blank design is firstly performed to determine flat blanks. The traditional trial and error approach is not applicable to blade design for Francis turbines that are not standard due to hydraulic characteristics of power plant sites. The rapid development of computing technology makes it possible to obtain optimal flat blanks by numerical modelling and simulation. In this paper, inverse finite element approach is investigated for blank design and an elasto-plastic model has been built using the well-known commercial software ANSYS. Numerical simulations for blade unfolding models with thick shell elements, solid elements and shell elements have given results with negligible differences. Unfolding tests with simple geometries have been carried out and the numerical results agree well with the analytical solutions. A large and thick shape of a Francis turbine blade for a hydropower plant has been successfully unfolded by inverse FE model. Sensibility analysis shows that the middle surface of the flat blank is independent of blade thickness. For ensuring the machining of the blade after the pressing process, a new contour is obtained by extending the boundary of the flat blank provided by the numerical model. This research may provide a useful tool for optimal blank design of Francis turbine blades.     

Adaptive inverse dynamics control of robots with uncertain kinematics and dynamics

It has been about two decades since the first globally convergent adaptive tracking controller was derived for robots with dynamic uncertainties. However, not until recently has the problem of concurrent adaptation to both the kinematic and dynamic uncertainties found its solution. This adaptive controller belongs to passivity-based control. Though passivity-based controllers have many attractive properties, in general, they are not able to guarantee the uniform performance of the robot over the entire workspace. Even in the ideal case of perfect knowledge of the manipulator parameters, the closed-loop system remains nonlinear and coupled. Thus the closed-loop tracking performance is difficult to quantify, while the inverse dynamics controllers can overcome these deficiencies. Therefore, in this work, we will develop a new adaptive Jacobian tracking controller based on the inverse manipulator dynamics. Using the Lyapunov approach, we have proved that the end-effector motion tracking errors converge asymptotically to zero. Simulation results are presented to show the performance of the proposed controller.