基于模糊干扰观测器的轨迹线性化控制研究

针对一类非线性不确定系统,基于轨迹线性化控制(TLC)方法及模糊干扰观测器(FDO)技术研究了一种新的非线性控制结构。利用模糊系统具有以任意精度逼近非线性函数的能力设计FDO对未知干扰和不确定进行估计,并通过鲁棒控制项来提高系统的性能。采用Lyapunov方法,证明了跟踪误差和干扰观测误差一致最终有界。最后利用提出的控制方案针对数值算例进行了仿真验证,仿真结果表明了控制方案的有效性和鲁棒性。     

一类径向基神经网络干扰观测器轨迹线性化控制

利用径向基神经网络(RBFNN)的逼近能力,研究了基于径向基神经网络干扰观测器(RDO)的鲁棒自适应轨迹线性化控制(TLC)策略,以解决空天飞行器复杂飞行条件下系统不确定及干扰的控制问题。分析了系统存在不确定性时轨迹线性化控制方法性能降低甚至失效的原因,设计了自适应调节律,并采用Lyapunov方法严格证明了在该自适应调节律作用下闭环系统所有误差信号最终有界。仿真结果表明,较当前TLC方法的控制性能,新方案在空天飞行器系统上具有更优异的控制性能和鲁棒性。     

Research of robust adaptive trajectory linearization control based on T-S fuzzy system

A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.     

PD-type iterative learning control for nonlinear time-delay system with external disturbance

1 .INTRODUCTIONTheiterativelearning control method was proposedby Ariomoto et al[1]for the control system, whichcan performthe same task repetitively . The basiclearning controller for generating the present con-trol input is based on the previous control historyand a learning mechanism.In the last two decadesiterative learning control has been extensivelystudied and achieved significant progress in boththeory and application,and becomes the one of themost active fields inintelligent cont…     

无人机鲁棒轨迹线性化控制航迹跟踪设计

研究一种鲁棒轨迹线性化控制方法并将其应用于无人机(unmanned aerial vehicle, UAV)航迹跟踪控制设计。通过理论分析指明传统轨迹线性化控制方法对系统中的不确定性存在鲁棒性不足的问题,采用改进隐层自适应神经网络对不确定性进行补偿,并利用Lyapunov理论证明了跟踪误差的有界性,最后将该方法应用到无人机三维航迹跟踪控制中。仿真结果表明,当参数摄动在20%时,该控制方法仍能使UAV很好地跟踪理想航迹,从而验证了该方法的有效性。     

Robust iterative learning control for nonlinear systems with measurement disturbances

The iterative learning control (ILC) has been demon-strated to be capable of considerably improving the tracking perfor-mance of systems which are affected by the iteration-independent disturbance. However, the achievable performance is greatly degraded when iteration-dependent, stochastic disturbances are pre-sented. This paper considers the robustness of the ILC algorithm for the nonlinear system in presence of stochastic measurement disturbances. The robust convergence of the P-type ILC algorithm is firstly addressed, and then an improved ILC algorithm with a decreasing gain is proposed. Theoretical analyses show that the proposed algorithm can guarantee that the tracking error of the nonlinear system tends to zero in presence of measurement dis-turbances. The analysis is also supported by a numerical example.     

不完全驱动船舶航迹控制输入输出线性化设计

针对船舶航迹保持控制系统模型中存在的非线性 ,建立了不完全驱动水面船舶直线航迹控制系统的非线性数学模型 ;基于输入输出线性化技术 ,采用重定义输出变量思想 ,提出了一种状态反馈控制律。该控制律克服了转首角速度不能为零及重定义输出变量中组成元素的收敛性不能保证的局限 ,使得偏航船舶能够渐近镇定于直线参考航迹 ,并以实习船为例 ,利用MatlabSimulink工具箱进行了计算机仿真研究 ,并对所提出的控制器进行了验证。结果表明 ,所提出的控制器具有比较理想的控制效果和良好的瞬态性能。     

TF/TA~2 trajectory tracking using nonlinear predictive control approach

1 .INTRODUCTIONThei mportance of terrain-following,terrain-avoid-ance ,andthreat-avoidance (TF/TA2) guidance forcruise missiles and aircraft is a well-recognized as-pect of military operations . Typically , the TF/TA2guidance system development consists of twomajor steps : (1) opti mal trajectory generationwithin maneuvering constraints considering ter-rain,obstacles and threats toincrease both surviv-ability and mission effectiveness ; (2) control lawdevelopment to followthe opti mal t…     

一类非线性系统的执行器组合故障自适应容错控制

针对一类具有执行器组合故障的多输入单输出非线性最小相位系统提出了自适应容错跟踪控制方案。考虑系统执行器卡死和部分失效组合故障,基于微分几何反馈线性化,设计了模型参考自适应容错控制算法。设计的控制律能够保证系统在执行器故障时闭环系统稳定,而且渐近跟踪给定的参考信号。仿真结果表明了所提方法的有效性。     

一类非线性系统的新型增益调度变结构跟踪控制

针对一类参数不确定非线性系统的增益调度变结构跟踪控制,以切换函数作为调度变量,同时考虑系统稳态误差的指标要求,对滑动平面系数、边界层厚度以及控制器系数进行调度,得到了一种新型的增益调度变结构控制策略。不仅消除了系统颤振,减少了系统能耗,提高了系统的控制性能,使得系统能够快速进入并获取稳定的滑动模态,而且使跟踪系统能够满足稳态误差指标的要求。仿真算例验证了所提控制策略的有效性。     

Global robust optimal sliding mode control for uncertain affine nonlinear systems

The problem of robustifying linear quadratic regulators (LQRs) for a class of uncertain affine nonlinear systems is considered. First, the exact linearization technique is used to transform an uncertain nonlinear system into a linear one and an optimal LQR is designed for the corresponding nominal system. Then, based on the integral sliding mode, a design approach to robustifying the optimal regulator is studied. As a result, the system exhibits global robustness to uncertainties and the ideal sliding mode dynamics is the same as that of the optimal LQR for the nominal system. A global robust optimal sliding mode control (GROSMC) is realized. Finally, a numerical simulation is demonstrated to show the effectiveness and superiority of the proposed algorithm compared with the conventional optimal LQR.     

Tracking control for air-breathing hypersonic cruise vehicle based on tangent linearization approach

This paper is focused on developing a tracking controller for a hypersonic cruise vehicle using tangent linearization approach. The design of flight control systems for air-breathing hypersonic vehicles is a highly challenging task due to the unique characteristics of the vehicle dynamics. Motivated by recent results on tangent linearization control, the tracking control problem for the hypersonic cruise vehicle is reduced to that of a feedback stabilizing controller design for a linear time-varying system which can be accomplished by a standard design method of frozen-time control. Through a proper model transformation, it can be proven that the tracking error of the designed closed-loop system decays exponentially. Simulation studies are conducted for trimmed cruise conditions of 110 000 ft and Mach 15 where the responses of the vehicle to step changes in altitude and velocity are evaluated. The effectiveness of the controller is demonstrated by simulation results.     

TF/TA trajectory tracking using nonlinear predictive control approach

The use of a methodology of nonlinear continuous predictive control to design the guidance control law for the aircraft TF/TA² trajectory tracking problem is emplojed. For the derivation of the predictive control law, by using Taylor series expansion, and based on optimizing a performance index which is a quadratic function of both the predictive value of the state variables and the control inputs, a state variable feedback controller for nonlinear systems is obtained, and it provides a tradeoff between satisfactory tracking performance and the control magnitude requirements. Numerical simulation results for a supersonic fighter aircraft model show the viability of this approach.     

再入机动飞行器最优轨迹设计与跟踪

提出了一种再入机动飞行器（maneuvering reentry vehicle, MRV）的最优制导与控制方案。针对MRV再入机动轨迹优化问题,提出了新的基于Gauss伪谱优化方法的分段优化策略;由产生的最优参考轨迹,生成系统的外环最优制导指令。接着利用轨迹线性化控制（trajectory linearization control, TLC）方法设计系统的内环控制律。基于MRV完整的非线性六自由度模型,仿真表明提出的再入轨迹优化设计方法是有效的,而且内环TLC控制器可以准确地跟踪外环的最优制导指令和最优轨迹,并对系统未建模特性和参数不确定性具有一定的鲁棒性能。     

飞行器自适应反推Terminal滑模轨迹跟踪控制

飞行器非线性动力学模型通常包含由未知外界干扰和未建模动态构成的非匹配不确定性。针对建立的飞行器纵向运动仿射非线性模型,提出了一种基于非线性干扰观测器(nonlinear disturbance observer, NDO)的自适应反推非奇异终端滑模(adaptive backstepping nonsingular terminal sliding mode,AB-NTSM)轨迹跟踪控制方法。设计非线性干扰观测器对未知干扰进行观测补偿,无需干扰上界先验知识。设计未建模动态自适应律,提高控制器对系统不确定性的鲁棒性。对3种不同情况的仿真表明,干扰观测器能够实现对不同干扰精确观测,仅在干扰突变时有较大观测误差。在不确定性影响下,采用提出的控制方法,系统能够实现对指定轨迹的稳定跟踪,并有效消除控制信号的抖振。     

Trajectory linearization control of an aerospace vehicle based on RB F neural network

An enhanced trajectory lineazization control(TLC)structure based on radial basis function neural network(RBFNN)and its application on an aerospace vehicle(ASV)flight control system are presensted.The influence of unknown disturbances and uncertainties is reduced by RBFNN thanks to its approaching ability,and a robustifying item is used to overcome the approximate error of RBFNN.The parameters adaptive adjusting laws are designed on the Lyapunov theory.The uniform ultimate boundedness of all signals of the composite closed-loop system is proved based on Lyapunov theory.Finally,the flight control system of an ASV is designed based on the proposed method.Simulation results demonstrate the effectiveness and robustness of the designed approach.     

Backstepping tracking control for nonlinear time-delay systems

1. INTRODUCTION The presence of time delay has a significant effect on system performance and destroys the stability of closed-loop system[1]. Therefore, the study on time-delay systems has important practical significance. Recen- tly,considerable progress has been made in this field[1~10]. According to the dependency of the designed contr-oller depends on the time delay, the control approa-ches for time-delay systems can be classified into two categories: delay-dependent[2~3,10] and dela…     

一类不确定执行器非线性系统的自适应控制

针对一类带不确定执行器非线性的控制系统,提出了一种自适应神经网络控制方法。建立了包括死区、齿隙和“类齿隙”磁滞特征的非线性执行器模型。通过结合所建立的模型和Nussbaum增益技术,解决了当执行器非线性不确定时的控制问题。所设计的方案不需知道非线性特征参数边界,并且当非线性特征为死区时,其坡度可以为时变的。引入了自适应补偿项消除建模误差和干扰的影响。仿真结果验证了该方法的有效性。     

基于非线性干扰观测器的高超声速飞行器反演滑模控制

针对高超声速飞行器非线性动力学系统中存在的高度非线性、多变量耦合及参数不确定等特点,利用非线性干扰观测器对各种干扰的逼近特性,结合反演滑模控制,设计了一种飞行器反演滑模控制器。该方法首先利用干扰观测器观测出系统的干扰,未观测出的部分干扰使用反演滑模控制进行补偿,避免了累积误差,实现对制导指令的鲁棒输出跟踪,并证明了系统稳定性。仿真结果验证了该方法能较理想地观测干扰,保证系统良好的鲁棒性。     

含非线性输入的非线性系统自适应模糊控制

讨论一类含非线性输入的非线性系统的自适应模糊控制问题。首先运用隐函数存在定理证明系统的理想控制器的存在性,利用I型模糊逻辑系统对该理想控制器进行在线逼近,提出了一种具有监督器的自适应模糊滑模控制器设计的新方案。该方案通过直接自适应模糊控制器与监督控制器的适当切换,保证了闭环系统的稳定性,由此确定出建模的有界区域,而且通过引入最优逼近误差的自适应补偿项,保证跟踪误差收敛到零。仿真结果表明了该方法的有效性。