快速模型预测控制用于微型直升机航迹跟踪

为实现微型共轴无人直升机(MCUH)的航迹跟踪,考虑系统的状态和输入约束,利用非线性模型预测控制(NMPC)技术设计一种快速在线的控制器。首先,简化MCUH的非线性模型,利用系统的微分平坦特性生成满足直升机动力学的可行航迹,沿着该航迹对系统进行线性化,得到近似直升机非线性动力学的线性时变(LTV)模型。然后,将传统输出航迹跟踪NMPC问题转化为LTV-MPC优化问题,降低问题的复杂度,为确保航迹跟踪误差系统的指数渐近稳定,分别设计终端域和终端罚值。最后,通过数值仿真,验证快速在线NMPC策略的可行性。结果表明:设计的预测控制器误差控制精度高、求解速度快,可实现对有约束的时变航迹的跟踪。     

High-fidelity trajectory optimization for aeroassisted vehicles using variable order pseudospectral method

In this study, the problem of time-optimal reconnaissance trajectory design for the aeroassisted vehicle is considered. Different from most works reported previously, we explore the feasibility of applying a high-order aeroassisted vehicle dynamic model to plan the optimal flight trajectory such that the gap between the simulated model and the real system can be narrowed. A highly-constrained optimal control model containing six-degree-of-freedom vehicle dynamics is established. To solve the formulated high-order trajectory planning model, a pipelined optimization strategy is illustrated. This approach is based on the variable order Radau pseudospectral method, indicating that the mesh grid used for discretizing the continuous system experiences several adaption iterations. Utilization of such a strategy can potentially smooth the flight trajectory and improve the algorithm convergence ability. Numerical simulations are reported to demonstrate some key features of the optimized flight trajectory. A number of comparative studies are also provided to verify the effectiveness of the applied method as well as the high-order trajectory planning model.     

基于高斯伪谱法的吸气式高超声速飞行器爬升弹道优化研究

吸气式高超声速飞行器爬升弹道设计是其总体设计的一个重要问题。这里提出一种基于高斯伪谱法的弹道优化方法,用于解决该问题。以末端弹道倾角为性能指标,飞行攻角为设计变量,建立了飞行器纵平面弹道优化模型。通过高斯伪谱法对状态变量和控制变量进行离散,将最优控制问题转化为非线性规划问题,再利用序列二次规划算法对其进一步求解。仿真结果表明,该方法收敛域大,对初值不敏感,设计精度高,是吸气式高超声速飞行器方案弹道优化的重要方法。     

Direct dynamic-simulation approach to trajectory optimization

This paper proposes a new direct method for an efficient trajectory optimization using the point that the dynamics of a deterministic system are uniquely determined by initial states and controls imposed over the time horizon of interest. To effectively implement this concept, the Hermite spline is adopted to interpolate the continuous controls and the system dynamics are integrated with corresponding control parameters in prior. As a result, the optimal control problem can be transcribed into a nonlinear programming problem which has no dynamic equality constraints and no intermediate states in its design variables. In addition, the paper proposes an efficient recursive Jacobian estimation technique and introduces a Jacobian transformation matrix to straightforwardly handle the general state constraints. Important properties of the present method are thoroughly investigated through its applications to the trajectory optimization for a soft lunar landing from a parking orbit, including the detailed analyses for the de-orbiting phase. The computed results are compared with those using the pseudo-spectral method to demonstrate an extreme outperformance of the proposed method in the aerospace applications over the traditional direct method.     

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。     

Trajectory optimization of multiple quad-rotor UAVs in collaborative assembling task

A hierarchic optimization strategy based on the offline path planning process and online trajectory planning process is presented to solve the trajectory optimization problem of multiple quad-rotor unmanned aerial vehicles in the collaborative assembling task. Firstly, the path planning process is solved by a novel parallel intelligent optimization algorithm, the central force optimization-genetic algorithm (CFO-GA), which combines the central force optimization (CFO) algorithm with the genetic algorithm (GA). Because of the immaturity of the CFO, the convergence analysis of the CFO is completed by the stability theory of the linear time-variant discrete-time sys-tems. The results show that the parallel CFO-GA algorithm converges faster than the parallel CFO and the central force optimization-sequential quadratic programming (CFO-SQP) algorithm. Then, the trajectory planning problem is established based on the path planning results. In order to limit the range of the attitude angle and guarantee the flight stability, the optimized object is changed from the ordinary six-degree-of-freedom rigid-body dynamic model to the dynamic model with an inner-loop attitude controller. The results show that the trajectory planning process can be solved by the mature SQP algorithm easily. Finally, the discussion and analysis of the real-time per-formance of the hierarchic optimization strategy are presented around the group number of the waypoints and the equal interval time.     

全测速测元弹道计算的数据融合算法与应用

针对“全测速”测元条件下弹道计算的数据融合问题,就数据融合中初值的确定、最优节点的搜索、样条基函数的选取、数据融合模型的数值解法等方面进行了分析与讨论,并给出一种适用于“全测速”测元条件下弹道计算的数据融合算法,经试用表明：该算法不仅具有良好的收敛性、稳定性,而且有着很好的数据融合效果,弹道计算的精度与“测距-测速”混合条件下数据融合弹道的精度相当。     

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.     

基于混合粒子群算法的上升段交会弹道快速优化设计

基于梯度搜索的高效性和粒子群搜索的随机性,提出了一种混合粒子群算法,并应用该算法研究了运载火箭上升段交会弹道快速优化设计问题.以运载火箭与目标飞行器在交会时刻的距离最小为目标函数,设计了运载火箭飞行程序,建立了运载火箭上升段交会弹道优化模型,同时分别采用混合粒子群算法、遗传算法和粒子群算法进行求解.仿真结果表明:基于本文算法对运载火箭上升段交会弹道进行优化设计,平均交会位置误差为4.137m,较遗传算法减少了17.940m,平均优化耗时488.922s,较粒子群算法缩短了2342.125s.混合粒子群算法搜索速度较快,收敛精度较高,可用于运载火箭上升段交会弹道的快速优化设计.      

基于任务安全性的亚轨道飞行器返回轨迹优化

基于高斯伪谱法,结合亚轨道飞行器返回段特点,从任务安全性的角度出发进行了返回轨迹优化研究。出于实际控制能力及安全性的考虑,采用伪控制量作为最优控制变量,摒弃了再入分段、末端区域能量管理段、航向校正圆锥等概念,引入"末端进场走廊"来描述性能指标及终端约束。仿真结果表明,在满足各种约束条件下,能够快速准确地生成亚轨道飞行器返回轨迹,同时验证了结果的可行性与最优性。     

航天器轨迹优化的通用数值方法

给出了航天器轨迹优化的一种通用数值仿真方法，该方法是由静态参数优化和动态参数优化构成，其中，静态参数优化采用可变误差多面体算法，动态参数优化采用基于最优控制理论的共轭梯度方法。     

基于BSP-ANN的四旋翼无人机轨迹跟踪方法

为了降低无人机轨迹跟踪误差,提高系统抗干扰能力,对反步（Backstepping）法进行改进提出一种基于反步神经网络（BSP-ANN）的无人机轨迹跟踪方法。首先,建立了四旋翼无人机运动学模型;然后,结合Backstepping方法在无人机的姿态控制、轨迹跟踪控制系统中引入Sigma-Pi神经网络,同时设计Sigma-Pi神经网络控制率,并证明该控制率满足Lyapunov意义下的系统稳定;最后,分别给出了相应的仿真实验。仿真结果表明：该算法可以有效降低跟踪误差,缩短无人机跟踪时间,同时可以提高系统的抗干扰能力。     

New reference trajectory optimization algorithm for a flight management system inspired in beam search

With the objective of reducing the flight cost and the amount of polluting emissions released in the atmosphere, a new optimization algorithm considering the climb, cruise and descent phases is presented for the reference vertical flight trajectory. The selection of the reference vertical navigation speeds and altitudes was solved as a discrete combinatory problem by means of a graphtree passing through nodes using the beam search optimization technique. To achieve a compromise between the execution time and the algorithm's ability to find the global optimal solution, a heuristic methodology introducing a parameter called ‘‘optimism coefficient was used in order to estimate the trajectory's flight cost at every node. The optimal trajectory cost obtained with the developed algorithm was compared with the cost of the optimal trajectory provided by a commercial flight management system(FMS). The global optimal solution was validated against an exhaustive search algorithm(ESA), other than the proposed algorithm. The developed algorithm takes into account weather effects, step climbs during cruise and air traffic management constraints such as constant altitude segments, constant cruise Mach, and a pre-defined reference lateral navigation route. The aircraft fuel burn was computed using a numerical performance model which was created and validated using flight test experimental data.     

Robust optimization of aircraft weapon delivery trajectory using probability collectives and meta-modeling

 Conventional trajectory optimization techniques have been challenged by their inability to handle threats with irregular shapes and the tendency to be sensitive to control variations of aircraft. Aiming to overcome these difficulties, this paper presents an alternative approach for trajectory optimization, where the problem is formulated into a parametric optimization of the maneuver variables under a tactics template framework. To reduce the size of the problem, global sensitivity analysis (GSA) is performed to identify the less-influential maneuver variables. The probability collectives (PC) algorithm, which is well-suited to discrete and discontinuous optimization, is applied to solve the trajectory optimization problem. The robustness of the trajectory is assessed through multiple sampling around the chosen values of the maneuver variables. Meta-models based on radius basis function (RBF) are created for evaluations of the means and deviations of the problem objectives and constraints. To guarantee the approximation accuracy, the meta-models are adaptively updated during optimization. The proposed approach is demonstrated on a typical airground attack mission scenario. Results reveal that the proposed approach is capable of generating robust and optimal trajectories with both accuracy and efficiency.     

Indirect Radau pseudospectral method for the receding horizon control problem

To solve the receding horizon control (RHC) problem in an online manner, a novel numerical method called the indirect Radau pseudospectral method (IRPM) is proposed in this paper. Based on calculus of variations and the first-order necessary optimality condition, the RHC problem for linear time-varying (LTV) system is transformed into the two-point boundary value problem (TPBVP). The Radau pseudospectral approximation is employed to discretize the TPBVP into well-posed linear algebraic equations. The resulting linear algebraic equations are solved via a matrix partitioning approach afterwards to obtain the optimal feedback control law. For the nonlinear system, the linearization method or the quasi linearization method is employed to approximate the RHC problem with successive linear approximations. Subsequently, each linear problem is solved via the similar method which is used to solve the RHC problem for LTV system. Simulation results of three examples show that the IRPM is of high accuracy and of high compu-tation efficiency to solve the RHC problem and the stability of closed-loop systems is guaranteed.     

无人飞行器参数依赖鲁棒控制研究

研究了具有参数不确定性的无人飞行器参数依赖鲁棒控制器设计问题。采用误差四元数建立姿态运动方程,避免了欧拉角描述姿态运动存在奇异性的问题。通过引入附加的松弛矩阵使Lyapunov矩阵和系统矩阵分离,并利用平方和工具箱求解非线性矩阵不等式得到了系统的鲁棒控制器。仿真结果表明了所提出的控制器设计方法的可行性和有效性。     

Real-time trajectory planning for UCAV air-to-surface attack using inverse dynamics optimization method and receding horizon control

This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle (UCAV) performing autonomous air-to-surface (A/S) attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem (RHC-OCP). In particular, an approximate elliptic launch acceptable region (LAR) model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom (2-DOF) receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.     

多无人机绳索悬挂协同搬运固定时间控制

针对多无人机绳索悬挂协同搬运跟踪控制问题,设计了一种新的固定时间协同跟踪控制算法。首先,通过旋量分析,计算系统不同状态下的有效旋量空间,并根据静力学平衡计算系统在有效旋量空间约束下的拉力容许裕度。其次,在保证绳索张紧以及最大拉力约束的条件下,基于微分平坦性以及绳索拉力优化分配算法,规划编队的期望跟踪轨迹。然后,基于Udwadia-Kalaba方程建立系统动力学模型,设计了连续的基于类超扭滑模和积分滑模的鲁棒控制项,以补偿系绳拉力给无人机造成的扰动,并设计了基于双极限齐次性原理的固定时间无人机协同外环位置控制器。针对无人机内环姿态稳定控制,设计了固定时间姿态稳定控制器。仿真结果表明,绳索拉力满足张紧和最大拉力约束,且设计的固定时间协同跟踪控制算法保证了系统在固定时间内稳定跟踪期望轨迹。     

巡航导弹航向规避弹道的优化设计

航向规避弹道的设计可视为一个多约束的优化问题。对此，通过选择导弹到达每个航路点的时间，用两点约束问题代替多点约束问题，得出了控制能量最优解，并分析了弹道特性。计算结果表明，弹道曲线在不超出导弹可用过载的前提下，通过所有航路点，并满足落点要求。该方法可用于航迹规划研究。     

Adaptive block dynamic surface control for integrated missile guidance and autopilot

A novel integrated guidance and autopilot design method is proposed for homing missiles based on the adaptive block dynamic surface control approach. The fully integrated guidance and autopilot model is established by combining the nonlinear missile dynamics with the nonlinear dynamics describing the pursuit situation of a missile and a target in the three-dimensional space. The integrated guidance and autopilot design problem is further converted to a state regulation problem of a time-varying nonlinear system with matched and unmatched uncertainties. A new and simple adaptive block dynamic surface control algorithm is proposed to address such a state regulation problem. The stability of the closed-loop system is proven based on the Lyapunov theory. The six degrees of freedom (6DOF) nonlinear numerical simulation results show that the proposed integrated guidance and autopilot algorithm can ensure the accuracy of target interception and the robust stability of the closed-loop system with respect to the uncertainties in the missile dynamics.