直连式三体绳系卫星姿态鲁棒最优跟踪控制

 针对存在参数不确定性以及外部有界干扰的直连式三体旋转绳系卫星系统姿态跟踪控制问题,提出了一种分布式鲁棒最优控制方法。该方法首先针对单体绳系卫星姿态模型,在不考虑参数不确定性和干扰的条件下,应用Hamilton-Jacobi-Bellman方程设计了最优控制器;接着,考虑到实际系统存在参数不确定性和干扰,采用自适应与鲁棒误差积分方法在线学习参数不确定性和有界干扰,与最优控制器结合设计了鲁棒最优控制器,使闭环系统满足了性能指标达到最小的要求,并应用Lyapunov稳定性定理证明了其闭环系统的渐近稳定性。进一步考虑到绳系卫星系统的运动同步性,将单体绳系卫星姿态控制器设计扩展至直连式三体绳系卫星姿态系统,设计了分布式鲁棒最优控制器。最后在MATLAB/Simulink平台上进行了仿真,验证了方法的可行性与有效性,表明其具有潜在的应用前景。     

Adaptive variable structure tracking control for constrained robots

The problem of controller design for constrained robots with the consideration of computational efficiency is addressed. An efficient adaptive variable structure control algorithm based on a reduced dynamics formulation, is presented for trajectory tracking of an end-effector on a constrained surface with specified constraint forces. It is shown that the objective can be achieved without exact knowledge of robot dynamics and on-line calculation of nonlinear dynamic functions. The control algorithm is constructed with at most three control parameters to be adjusted adaptively, and that number is determined independently of the number of degrees of freedom of the robotic manipulators. A numerical example is presented to illustrate the developed method     

基于自适应不对称高斯基函数网络的可靠飞行跟踪控制

针对歼击机操纵面结构故障,提出了一种基于自适应不对称高斯基函数网络（AGBFN）的可靠跟踪控制方案。该方案的特点是在传统的线性控制器的基础上,引入基于自适应AGBFN的自适应控制器,用于在线补偿由于建模误差、外扰、以及操纵面卡死或损伤所造成的影响,并且采用控制隔离技术来处理执行机构的饱和问题。完全自适应AGBFN采用不对称高斯基函数,并且可以在线更新网络所有参数,克服了传统RBF网络对称性约束,提高了网络的适应性和学习能力,从而保证歼击机的操纵品质,且输出较好地跟踪参考模型输出。飞行仿真结果表明,文中采用的控制方法使飞机在正常状态和故障状态下均可获得满意的控制效果。     

Fixed-time adaptive model reference sliding mode control for an air-to-ground missile

This paper addresses the fixed-time adaptive model reference sliding mode control for an air-to-ground missile associated with large speed ranges, mismatched disturbances and un-modeled dynamics. Firstly, a sliding mode surface is developed by the tracking error of the state equation and the model reference state equation with respect to the air-to-ground missile. More specifically,a novel fixed-time adaptive reaching law is presented. Subsequently, the mismatched disturbances and the un-modeled dynamics are treated as the model errors of the state equation. These model errors are estimated by means of a fixed-time disturbance observer, and they are also utilized to compensate the proposed controller. Therefore, the fixed-time controller is obtained by an adaptive reaching law and a fixed-time disturbance observer. Closed-loop stability of the proposed controller is established. Finally, simulation results including Monte Carlo simulations, nonlinear six-DegreeOf-Freedom(6-DOF) simulations and different ranges are presented to demonstrate the efficacy of the proposed control scheme.     

基于浸入与不变理论的航天器姿态跟踪自适应控制

针对惯性参数不确定的航天器姿态跟踪控制问题，基于浸入与不变（I&I）方法设计出了一种新的姿态跟踪控制器。研究结果表明，传统的浸入与不变方法运用到姿态跟踪模型，存在参数回归矩阵不可积进而导致偏微分方程无解析解的问题。针对该问题，提出了一种对回归矩阵改造使其满足可积条件的方法，通过动态放缩技术消除了回归矩阵改造前后的差异对闭环系统稳定性的影响，设计出了一种新的航天器姿态跟踪自适应控制器。通过李雅普诺夫稳定性分析方法证明了所设计的控制器能够保证闭环系统的全局渐近稳定性。相对于已有的基于动态放缩法的浸入与不变控制器，设计了一种全新的缩放因子，使得控制器的执行不需要缩放因子的信息，并且也不需要惯量矩阵的先验信息。最后，仿真对比实验进一步验证了所设计控制器的有效性和优越性。     

基于CMAC的伺服系统控制研究

针对高精度伺服系统中存在的非线性和各种不确定性因素,提出了基于小脑模型神经网络的复合控制方法,控制器由前馈控制器、比例微分控制器(PD)和小脑模型神经网络控制器(CMAC)构成,该方法在传统的PD+前馈控制方法上加入了CMAC神经网络算法的快速学习,精确逼近的优点,既保证了快速实时跟踪,又进一步提高了跟踪精度。实验结果证明,用CMAC控制方法后系统的跟踪精度比PD＋前馈控制方法提高近一个数量级,同时该方法对摩擦引起的波形畸变有很好的抑制作用,仿真和实验研究表明了该方法的可行性和有效性,并能满足实时性要求,对提高伺服系统的高精度动态跟踪性能有很好的工程参考价值。     

无人直升机的自适应非线性控制

最近几年，许多仿真结果都揭示了基于神经网络的直接自适应控制在飞行控制系统设计中的发展潜力。其中最重要的一点就是显著降低了对系统动态模型的要求。本文把该方法应用于无人直升机，给出了自适应姿态控制系统和跟踪控制器的设计方法。通过，数字仿真表明该控制方法有良好的跟踪控制性能。     

Modified robust optimal adaptive control for flight environment simulation system with heat transfer uncertainty

To solve the rapid transient control problem of Flight Environment Simulation System (FESS) of Altitude Ground Test Facilities (AGTF) with large heat transfer uncertainty and disturbance, a new adaptive control structure of modified robust optimal adaptive control is presented. The mathematic modeling of FESS is given and the influence of heat transfer is analyzed through energy view. To consider the influence of heat transfer in controller design, we introduce a matched uncertainty that represents heat transfer influence in the linearized system of FESS. Based on this linear system, we deduce the design of modified robust optimal adaptive control law in a general way. Meanwhile, the robust stability of the modified robust optimal adaptive control law is proved through using Lyapunov stability theory. Then, a typical aero-engine test condition with Mach Dash and Zoom-Climb is used to verify the effectiveness of the devised adaptive controller. The simulation results show that the designed controller has servo tracking and disturbance rejection performance under heat transfer uncertainty and disturbance; the relative steady-state and dynamic errors of pressure and temperature are both smaller than 1% and 0.2% respectively. Furthermore, the influence of the modification parameter γ is analyzed through simulation. Finally, comparing with the standard ideal model reference adaptive controller, the modified robust optimal adaptive controller obviously provides better control performance than the ideal model reference adaptive controller does.     

一类非仿射输入和不确定性系统的输出跟踪控制

针对一类具有非仿射输入和不确定性的混沌系统,提出了鲁棒自适应RBFNN反演控制。RBF神经网络用来逼近设计过程中所有的未知非线性函数,并且对逼近的误差设计了鲁棒项,设计的自适应律是针对RBF所有权值的上界而不是权值本身,因而在线自适应参数数量减少了,节约了计算时间。该方法保证了混沌系统的输出能跟踪任意参考信号,并且跟踪误差是一致渐进收敛的。仿真结果表明该方法的可行性和有效性。     

惯性参数不确定的自由漂浮空间机器人自适应控制研究

针对自由漂浮空间机器人系统惯性参数不确定问题,提出一种笛卡儿空间内的自适应轨迹跟踪控制方法。采用扩展机械臂模型建立了自由漂浮空间机器人关节空间动力学方程,进而推导笛卡儿空间中的自由漂浮空间机器人动力学方程。在基于逆动力学法的自由漂浮空间机器人自适应控制器设计中,利用标称控制器离线固定控制参数与补偿控制器在线补偿方法,既可以保证惯量矩阵可逆,又可以使控制参数实时估计。采用Lyapunov方法的稳定性分析表明系统是稳定且渐进收敛的。最后,应用该控制方法对两杆平面自由漂浮空间机器人进行了仿真研究。仿真结果显示自由漂浮空间机器人末端执行器在笛卡儿空间具有良好的轨迹跟踪能力。     

Robust Hybrid Control for Ballistic Missile Longitudinal Autopilot

This paper investigates the boost phase’s longitudinal autopilot of a ballistic missile equipped with thrust vector control. The existing longitudinal autopilot employs time-invariant passive resistor-inductor-capacitor (RLC) network compensator as a control strategy, which does not take into account the time-varying missile dynamics. This may cause the closed-loop system instability in the presence of large disturbance and dynamics uncertainty. Therefore, the existing controller should be redesigned to achieve more stable vehicle response. In this paper, based on gain-scheduling adaptive control strategy, two different types of optimal controllers are proposed. The first controller is gain-scheduled optimal tuning-proportional-integral-derivative (PID) with actuator constraints, which supplies better response but requires a priori knowledge of the system dynamics. Moreover, the controller has oscillatory response in the presence of dynamic uncertainty. Taking this into account, gain-scheduled optimal linear quadratic (LQ) in conjunction with optimal tuning-compensator offers the greatest scope for controller improvement in the presence of dynamic uncertainty and large disturbance. The latter controller is tested through various scenarios for the validated nonlinear dynamic flight model of the real ballistic missile system with autopilot exposed to external disturbances.     

基于BOWA小脑模型的高精度稳定 电动加载系统

 随着电动加载系统的不断发展,对控制精度、动态特性和稳定性提出了更高的要求,常规的小脑模型(CMAC)和PD控制相结合的复合控制策略难以满足加载指标要求。针对无人机舵机电动加载系统的控制需求,提出了一种基于平衡学习、最优权值和自适应学习率的新型小脑模型(BOWA-CMAC)复合控制策略,它在保留小脑模型算法正常学习过程的同时,避免了算法的过学习现象,保证了系统的稳定,同时提高了跟踪精度和动态特性。仿真和实验结果表明,BOWA-CMAC复合控制策略具有很强的鲁棒性,抑制了加载系统的多余力矩,保证了系统的稳定性,有效提高了系统的跟踪精度和动态特性,非常适合于实时控制。     

非线性预测控制在巡航导弹地形跟踪中的应用

建立了巡航导弹的非线性动力学模型,针对该模型的非线性连续预测控制方法,提出了预测跟踪误差和跟踪误差线性组合的性能指标,通过使性能指标最小,产生了巡航导弹地形跟踪的最优非线性反馈控制器,通过对虚拟地形的跟踪验证了控制器的性能,结果表明,该控制器不仅具有精确的跟踪性能而且具有良好的鲁棒性。     

基于神经网络的MIMO非线性最小相位系统鲁棒自适应控制

 针对一类模型未知的具有不确定性和外部干扰的多输入多输出（MIMO）非线性最小相位系统提出了鲁棒自适应输出反馈跟踪控制方案。用高斯径向基函数（RBF）神经网络逼近对象未知非线性,用高增益观测器估计系统不可测量状态。所设计的鲁棒自适应控制器不仅能使闭环系统稳定,所有状态有界,而且跟踪误差一致最终有界,并保证最终边界足够小。仿真结果表明了所提出方法的有效性。     

Fuzzy adaptive robust control for space robot considering the effect of the gravity

Space robot is assembled and tested in gravity environment, and completes on-orbit service（OOS） in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control（FARC） strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative（PD） controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.     

压电陶瓷叠层作动器迟滞蠕变非线性自适应混合补偿控制方法

压电陶瓷叠层作动器的迟滞蠕变非线性特性严重影响了控制系统的稳定性及动态跟踪精度。针对其迟滞蠕变非线性补偿控制问题,提出了一种高精度动态补偿压电陶瓷叠层作动器非线性特性的自适应混合补偿控制方法,即迟滞蠕变前馈补偿与自适应滤波反馈补偿结合的前馈-反馈混合控制方法。采用改进的Prandtl-Ishlinskii（Modified Prandtl-Ishlinskii,MPI）模型对压电陶瓷叠层作动器迟滞蠕变非线性特性进行精细化建模,并得到其逆补偿模型进行前馈补偿。根据前馈补偿误差,采用自适应滤波反馈控制对输入信号进行实时调控,实现对压电陶瓷叠层作动器的迟滞非线性及lg（t）型蠕变特性的实时精确补偿控制。数值仿真与实验结果表明,相比于常规前馈迟滞蠕变补偿,所提出的自适应混合补偿控制方法可以有效降低压电陶瓷叠层作动器的迟滞补偿误差,极大提高了迟滞蠕变非线性动态跟踪精度以及自适应性。     

有输入未建模动态和不确定性导弹控制器设计

在考虑导弹控制系统同时存在输入未建模动态和参数不确定性的情况下,提出了一种基于RBF神经网络和反演技术的鲁棒自适应控制器的设计方法。首先用两个RBF神经网络对未建模动态进行了补偿,然后利用反演技术设计了鲁棒自适应控制器,对不确定性进行了处理,并用Lyapunov稳定性理论推导出RBF神经网络的权重矩阵调节率以及相关的自适应律,证明了系统的全局稳定性,最后通过仿真计算验证了设计的正确性。     

Attitude tracking control for variable structure near space vehicles based on switched nonlinear systems

An adaptive robust attitude tracking control law based on switched nonlinear systems is presented for a variable structure near space vehicle (VSNSV) in the presence of uncertainties and disturbances. The adaptive fuzzy systems are employed for approximating unknown functions in the flight dynamic model and their parameters are updated online. To improve the flight robust performance, robust controllers with adaptive gains are designed to compensate for the approximation errors and thus they have less design conservation. Moreover, a systematic procedure is developed for the synthesis of adaptive fuzzy dynamic surface control (DSC) approach. According to the common Lyapunov function theory, it is proved that all signals of the closed-loop system are uniformly ultimately bounded by the continuous controller. The simulation results demonstrate the effectiveness and robustness of the proposed control scheme.     

基于自适应模糊系统的空天飞行器非线性预测控制

 针对一类多输入多输出非线性不确定系统,提出了基于自适应模糊系统的非线性预测控制方法。控制器由基于模糊系统的非线性预测控制器和鲁棒自适应控制器两个部分组成。根据系统的跟踪误差在线调整模糊系统的权值,使得模糊系统一致逼近被控对象中的非线性函数,通过泰勒展开设计出基于模糊系统的非线性预测控制律,避免了预测控制在线优化带来的繁重的计算负担。鲁棒自适应控制器则用于减少不确定和模糊逼近误差对系统的影响。所设计的控制器保证了闭环系统的最终一致有界稳定。基于Lyapunov稳定原理,给出了理论证明和分析。最后利用提出的控制方案设计了空天飞行器高超声速飞行姿态的控制系统,仿真结果表明了控制方案的有效性。     

Adaptive control and stabilization of elastic spacecraft

This work treats the question of large angle rotational maneuver and stabilization of an elastic spacecraft (spacecraft-beam-tip body configuration). It is assumed that the parameters of the system are completely unknown. An adaptive control law is derived for the rotational maneuver of the spacecraft. Using the adaptive controller, asymptotically decoupled control of the pitch angle of the space vehicle is accomplished, however this maneuver causes elastic deformation of the beam connecting the orbiter and tip body. For the stabilization of the zero dynamics (flexible dynamics), a stabilizer is designed using elastic mode velocity feedback. In the closed-loop system including the adaptive controller and the stabilizer, reference pitch angle trajectory tracking and vibration suppression are accomplished. Simulation results are presented to show the maneuver capability of the control system