CN105955028A - On-orbit guidance avoidance control integrated algorithm for spacecraft - Google Patents

On-orbit guidance avoidance control integrated algorithm for spacecraft Download PDF

Info

Publication number
CN105955028A
CN105955028A CN 201610388966 CN201610388966A CN105955028A CN 105955028 A CN105955028 A CN 105955028A CN 201610388966 CN201610388966 CN 201610388966 CN 201610388966 A CN201610388966 A CN 201610388966A CN 105955028 A CN105955028 A CN 105955028A
Authority
CN
Grant status
Application
Patent type
Prior art keywords
spacecraft
potential
control
orbit
guidance
Prior art date
Application number
CN 201610388966
Other languages
Chinese (zh)
Other versions
CN105955028B (en )
Inventor
罗建军
高登巍
袁建平
朱战霞
马卫华
王明明
Original Assignee
西北工业大学
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date

Links

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/10Simultaneous control of position or course in three dimensions
    • G05D1/101Simultaneous control of position or course in three dimensions specially adapted for aircraft

Abstract

The invention discloses an on-orbit guidance avoidance control integrated algorithm for a spacecraft. The on-orbit guidance avoidance control integrated algorithm includes the steps: establishing a relative movement model; designing a potential function and a sliding-mode control guidance control integrated algorithm; analyzing the robustness of the algorithm, and providing a safety orbit space; and finally verifying the effectiveness of the on-orbit guidance avoidance control integrated algorithm for a spacecraft through a simulation example. The on-orbit guidance avoidance control integrated algorithm for a spacecraft analyzes the safety section of the safety orbit under a disturbed condition, can quickly perform on-orbit calculation and control the spacecraft to perform real-time obstacle avoidance, can guarantee that the spacecraft can avoid the obstacle in the safety range, and is conductive to a spacecraft to more reliably perform an on-orbit flight task in the future.

Description

-种航天器在轨规避制导控制一体化算法【技术领域】 - to avoid the kind of spacecraft in orbit guidance and control integration algorithm FIELD

[0001] 本发明属于航天器控制技术领域,设及一种航天器在轨规避制导控制一体化算法。 [0001] The present invention belongs to the technical field of spacecraft control, and provided Spacecraft orbit avoidance guidance control integration algorithm. 【背景技术】 【Background technique】

[0002] 随着对空间研究、开发与应用能力的不断提高,各国相继研制并发射了大量面向各种任务要求的航天器,由初步进入空间和利用空间到空间操作和空间应用。 [0002] With the continuous improvement of space research, development and application capabilities, countries have developed and launched a large space is required for a variety of tasks, to space operations and space applications from the initial access to space and use of space. 而空间操作的自主性、安全性等也逐渐被人们所关注。 The autonomous operation of the space, security, and so has gradually been concerned.

[0003] 近年来,航天器安全轨迹制导中人工势函数法(Artif icial potential function,APF)越来越多的被使用。 [0003] In recent years, security spacecraft trajectories Guidance artificial potential function method (Artif icial potential function, APF) is used more and more. 其最初是由KhaUb在"Rea]_-Time Obstacle Avoidance for Manipulator and Mobile Robots"中提出,用来解决机械臂在操作空间的路径规划问题,其基本思想是构造目标引力场和障碍物斥力场,使它们共同作用捜索势函数势能下降方向来寻找无碰路径。 It was originally in the "Rea] _- Time Obstacle Avoidance for Manipulator and Mobile Robots" proposed by the KhaUb, to solve the path planning problem in the operation of the robotic arm of the space, the basic idea is to construct gravitational field goal and obstacle repulsion field, Dissatisfied cable so that they cooperate potential function in the lowering direction to find potential collision-free path. McInnes在"Autonomous Rendezvous Using Artificial Potential 化nction Guidance"中提出的将其应用在航天器领域到目前为止已经有20多年的时间,相关方面的文献有很多,发展相对成熟。 McInnes in the "Autonomous Rendezvous Using Artificial Potential of nction Guidance" proposed in its application in the field of spacecraft so far has been 20 years time, there are many relevant aspects of literature, is relatively mature. 比如Ender St.John在"Ankersen F.Safety- critical autonomous spacecraft proximity operations via potential function guidance"中提出将其应用到W自主转移飞行器ATV、HTV和ISS的交会对接中,结果令人满意。 For example, Ender St.John proposed to apply it to self-W Transfer Vehicle ATV, HTV rendezvous and docking of the ISS, with satisfactory results in "Ankersen F.Safety- critical autonomous spacecraft proximity operations via potential function guidance". 张大伟等人在('Safe Guidance for Autonomous Rendezvous and Dockin邑with a Non-Cooperative Target"中提出将人工势函数应用在非合作目标的交会对接任务中,并与模糊控制方法相结合,针对动态障碍物躲避和对接安全轨迹约束进行了研究和方针。文南犬('Swarm aggregations using artificial potentials and sliding mode control" 中提出将人工势函数和滑模控制相结合应用于卫星聚集和编队。文献"Autonomous Distributed Control Algorithm for Multiple Spacecraft in Close Proximity Operations"中提出将人工势函数法和LQR方法相结合应用于多目标的近程操作中。人工势函数法具有稳定性易判定、计算效率高等显著优点,是一种比较适合应用在自主式的交会对接任务中的人工智能方法。而滑模控制适用于线性与非线性系统、连续与离散系统、确定与不确定系统等,运种控制方法通过控制量的切换使系统状态沿着滑模面 Zhang Dawei, who proposed the application of artificial potential function in non-cooperative rendezvous and docking mission objective, and combined with fuzzy control methods ( 'Safe Guidance for Autonomous Rendezvous and Dockin town with a Non-Cooperative Target ", for a moving obstacle track and avoid docking security research and policy constraints. Wennan dog "proposed artificial potential function and the combination of sliding mode control used in satellite aggregation and formation in literature" ( 'Swarm aggregations using artificial potentials and sliding mode control Autonomous Distributed Control Algorithm for multiple Spacecraft in Close proximity operations "in the proposed method and the artificial potential function LQR method of combining operations to the multi-target proximity in artificial potential function easily determined stability, significant advantages of higher computational efficiency, is a Comparative species suitable for use in the methods of artificial intelligence autonomous rendezvous and docking task while sliding mode control applicable to linear and nonlinear systems, continuous and discrete systems, is determined with uncertainty systems, operation control method is switched by controlling the amount of status of the system along the sliding surface 滑动,使系统在受到参数摄动和外界干扰时具有不变性。经历多年发展,现已成为自动控制一种普遍的设计方法。但是存在一定的抖振问题。 Slide the system invariant when subjected to external disturbances and parameter perturbations. After many years of development, has now become the automatic control of a universal design approach, but there are some chattering problems.

[0004] 借助势函数法在障碍物的规避中的优势,W及滑模控制对于非线性控制的良好性能,本发明将两种方法进行结合,并通过鲁棒控制理论设计了一种能够在存在位置干扰和测量误差的情况下进行障碍物躲避的制导控制一体化算法,可W实现任意位置的轨迹规划和静态或者动态障碍物的躲避。 [0004] With the advantages of the potential function in the obstacle avoidance, W, and good performance of sliding mode control for nonlinear control, according to the present invention, two methods will be combined, and designed by the robust control theory capable of the obstacle avoidance of the interference position in the presence of measurement errors and integration of guidance and control algorithms, may be implemented anywhere W trajectory planning and obstacle avoidance static or dynamic. 【发明内容】 [SUMMARY]

[0005] 本发明的目的在于针对航天器在轨飞行时有效躲避障碍物、提高飞行安全的需求,提供一种航天器在轨规避制导控制一体化算法,该算法能够提高避障的实时性和安全性。 [0005] The present invention is effective for the spacecraft to avoid obstacles in the flight track, improve flight safety requirements, provide a spacecraft in orbit integration algorithm to avoid the guidance control, the algorithm can improve real-time obstacle avoidance and safety.

[0006] 为达到上述目的,本发明采用W下技术方案予W实现: [0006] To achieve the above object, the present invention adopts the technical scheme I W W implemented:

[0007] -种航天器在轨规避制导控制一体化算法,包括W下步骤: [0007] - to avoid the kind of spacecraft in orbit guidance and control integration algorithms, including W steps:

[000引1)建立航天器相对运动方程 [000 cited 1) the establishment of the spacecraft relative motion equation

Figure CN105955028AD00051

[00091 1、1 H 础说玄玄油古化天器相对运动动力学方程; [00091 1,1 H Xuan Xuan said base oil of the ancient days relative movement dynamics equation;

[0010: (1) [0010: (1)

[0011: [0011:

[0012; [0012;

[0013; [0013;

[0014] 其中,O为目标航天器的轨道角速度,U为追踪航天器的控制输出,d为未建模误差,包括引力梯度误差,各种摄动,目标未知控制力,或者其他不可测量和估计的未知干扰; [0014] where, O is the angular velocity of the target spacecraft orbit, U is the output of the tracking control spacecraft, d is unmodeled errors, including errors gravity gradient, various perturbation, control target is unknown, or unmeasured, and other estimates of unknown disturbances;

[0015] 其中的动力学方程可W更换为任何航天器相对运动动力学模型; [0015] wherein W can be replaced kinetic equation any relative motion of spacecraft dynamics model;

[0016] 2)设计势函数和滑模控制一体化制导控制算法 [0016] 2) the design and potential function integrated sliding mode control algorithm Guidance Control

[0017] 航天器的势函数定义在状态空间中,设状态变量为X,期望的状态为Xd;引力势函数促使追踪航天器到达预设的目标状态,因此引力势函数设计为: [0017] spacecraft potential function defined in the state space, the reset state variable X, Xd a desired state; gravitational potential function causes tracking the spacecraft reaches a predetermined target state, the gravitational potential function is designed to:

[001 引 [001 Cited

Figure CN105955028AD00052

(2) (2)

[0019] 引力势函数中同时包含了位置和速度信息,描述了期望跟踪的位置和其运动的趋势;其中Pp、Pv为正定矩阵; [0019] gravitational potential function contains both position and velocity information, describes the trend of the desired track position and its movement; wherein Pp, Pv is a positive definite matrix;

[0020] 斥力势选用高斯函数: [0020] repulsive potential selected Gaussian function:

[0021] [0021]

Figure CN105955028AD00053

(3) (3)

[0022] 其中,4表示斥力势的高,O表示斥力势的宽,矩阵N是与障碍物形状有关的外形矩阵;下标i表示多个不同的障碍物;总的势能表示航天器在存在障碍物的情况下势能是引力势和斥力势的和;势函数的梯度提供滑模控制的滑模面: [0022] where 4 indicates a high potential repulsion, O for repulsion potential width, N is the matrix associated with the matrix shape to the shape of the obstacle; the subscript i represents a plurality of different obstacles; represents the total potential energy of the spacecraft in the presence of the potential obstacle to be attractive and repulsive potential and; gradient of the potential function to provide sliding surface of the sliding mode control:

[0023] [0023]

Figure CN105955028AD00054

(4) (4)

[0024] 人工势函数所代表的能量场的梯度用来表示其能量下降的方向,而能量高的地方被障碍物所产生的虚拟斥力势所代替,低势场被规划的期望轨迹所代替,因此沿着梯度方向的路径即为满足任务规划的安全路径; [0024] The gradient of the energy field artificial potential function is used to indicate the direction represented by the energy drop, and high energy where the obstacle is replaced by the generated virtual repulsion potential, low potential field is replaced by a desired trajectory planning, Therefore, the direction of the gradient along the path is the path to meet the security mission planning;

[0025] 滑模控制的收敛必须满足: [0025] The sliding mode control convergence must be met:

[0026] [0026]

Figure CN105955028AD00055

(5) (5)

[0027] 采用化miIton-化cobi Inequality理论进行控制器设计;其鲁棒性采用L2增益的形式进行描述: [0027] The theory of miIton- of cobi Inequality controller design; robust form of its gain L2 will be described:

[0028] [0028]

Figure CN105955028AD00061

(6) (6)

[0029]其中假设Z为滑模面;定义Iyapunov函数为: [0029] wherein Z is assumed sliding surface; Iyapunov function is defined as:

[0030] [0030]

Figure CN105955028AD00062

口) mouth)

[0031] 因为控制稳定性需满足F<0,因此设计控制器为: [0031] Since the control stability must satisfy F <0, so the design of the controller:

[0032] [0032]

Figure CN105955028AD00063

(Si (Si

[0033] 通过验证Hami Iton函数得到: [0033] obtained by verifying Hami Iton functions:

[0034] [0034]

Figure CN105955028AD00064

Imperial

[0035] 因此证明控制系统在存在干扰的情况下依然稳定; [0035] In the control system thus demonstrating the presence of interference remained stable;

[0036] 3)鲁棒性分析 [0036] 3) Analysis of Robustness

[0037] 当考虑测量误差时控制力表示为: [0037] When considering a measurement error control is expressed as:

[00;3 引 [00; 3 lead

Figure CN105955028AD00065

(lOj (LOj

[0039] 定义^A)和如分别为矩阵A的最大和最小特征值;Ft为动力学方程线性化系数矩阵,Ht为测量矩阵;为简化起见,令=vT(/> I,并定义: [0039] A ^ is defined), and such characteristics are maximum and minimum values ​​of the matrix A; Ft matrix kinetic coefficient of linear equations, the measurement Ht of the matrix; for simplicity, so = vT (/> I, and define:

[0040] [0040]

Figure CN105955028AD00066

(K) (K)

[0041 ]对于传感器,测量数据采用率为P,在每一时刻有如下表达式: [0041] For the sensor, the measurement data rate using P, at each moment following expression:

[00 创(;口) [00 record (; mouth)

[0043] 假设追踪航天器的 [0043] hypothesis tracking the spacecraft

Figure CN105955028AD00067

轨迹有99.74%的概率处于安全轨迹范围内,即状态值处于[戈-巧壬+ 口]区间,其中口= 3.^/^;因此通过中值定理得到滑模面S的误差限: 99.74% probability with a track in the safety profile range, i.e., the state value is [Ge - + port clever nonyl] interval, where a = 3 ^ / ^; thus the margin of error sliding surface S obtained by the mean value theorem:

Figure CN105955028AD00068

[0044] (13) [0044] (13)

[0045] [0045]

[0046] 此时系统的稳定和传感器的测量精度有关,经过推导得到传感器的测量噪声需满足如下不等式时控制才能保证稳定并处于上述安全轨迹范围内: [0046] At this time, the system stability and accuracy of the sensor related to measurement noise was derived through the sensors need to meet the following inequality control to ensure stability, and when the security is within the above range trajectory:

[0047] (14) [0047] (14)

Figure CN105955028AD00071

[004引' [004 cited '

[0049] 与现有技术相比,本发明具有W下有益效果: [0049] Compared with the prior art, the present invention has beneficial effects W:

[0050] 本发明提出了一种航天器在轨避障的制导控制一体化算法,并分析了存在干扰情况下安全轨迹的安全区间。 [0050] The present invention provides a spacecraft orbit avoidance guidance control integration algorithm, and analyzes the trajectory safety security interval of interference. 该算法可W快速在轨计算并控制航天器进行实时避障,并且确保航天器在安全范围内躲避障碍物,有益于未来航天器更可靠地进行在轨飞行任务。 The algorithm can calculate W quickly track and control the spacecraft in real-time obstacle avoidance, avoid obstacles and make sure the spacecraft in a safe range, good for future spacecraft and more reliable on-orbit mission. 【附图说明】 BRIEF DESCRIPTION

[0051 ]图1为静态障碍物避障时的相对运动轨迹图; [0051] FIG. 1 is a view of the relative trajectory of the static obstacle avoidance;

[0052] 图2为蒙特卡洛打祀图; [0052] FIG. 2 is a Monte Carlo FIG Si played;

[0053] 图3为障碍物运动时的相对运动轨迹图。 [0053] FIG 3 relative trajectory view of an obstacle movement. 【具体实施方式】 【Detailed ways】

[0054] 下面结合附图对本发明做进一步详细描述: [0054] DRAWINGS The present invention will be described in detail:

[0055] 参见图1-图3,本发明航天器在轨规避制导控制一体化算法,包括W下步骤: [0055] Referring to FIGS. 1-3, the present invention is to circumvent orbit spacecraft guidance and control integration algorithm, W comprising the steps of:

[0056] 1)建立航天器相对运动方程 [0056] 1) the establishment of the spacecraft relative motion equation

[0057] W目标轨道坐标系为参考坐标系,建立航天器相对运动动力学方程: [0057] W target orbit coordinate system as the reference coordinate system, the establishment of the spacecraft relative motion kinetic equation:

Figure CN105955028AD00072

[005引(1) [Primer 005 (1)

[0化9] [0 of 9]

[0060] 12345678 2 共中,《刃曰称肌入帯的机迫用化设,U为追踪航天器的控制输出,d为未建模误差,包括引力梯度误差,各种摄动,目标未知控制力,或者其他不可测量和估计的未知干扰; 3 其中的动力学方程可W更换为任何航天器相对运动动力学模型; 4 2)设计势函数和滑模控制一体化制导控制算法5 航天器的势函数定义在状态空间中,设状态变量为X,期望的状态为Xd;引力势函数促使追踪航天器到达预设的目标状态,因此引力势函数设计为: 6 [0060] In co-123456782, "said blade into said muscle force with Bands of machine set, U is the output of the tracking control spacecraft, d is unmodeled errors, including errors gravity gradient, various perturbation, the target unknown control, or other unmeasured and unknown interference estimation; 3 wherein the kinetic equation can be replaced by any spacecraft W relative motion dynamics model; 42) and the design potential function sliding mode control integrated control algorithm 5 spacecraft Guidance the potential function is defined in the state space, the reset state variable X, Xd a desired state; gravitational potential function causes tracking the spacecraft reaches a predetermined target state, the gravitational potential function is designed to: 6

[0066] [0066]

Figure CN105955028AD00073

(2) 7 引刀势巧数甲问町包昔J位置和化巧信思,巧述了期望跟踪的位置和其运动的趋势;其中Pp、Pv为正定矩阵; 8 斥力势选用高斯函数: (2) A number of clever 7 primer Daoshi cho package Q and the position of Xi Qiao J Si channel, the coincidence of said desired tracking position and trend of movement thereof; wherein Pp, Pv is a positive definite matrix; 8 repulsive potential selected Gaussian function:

[0069] [0069]

Figure CN105955028AD00081

(3) (3)

[0070] 其中,4表示斥力势的高,O表示斥力势的宽,矩阵N是与障碍物形状有关的外形矩阵;下标i表示多个不同的障碍物;总的势能表示航天器在存在障碍物的情况下势能是引力 [0070] where 4 indicates a high potential repulsion, O for repulsion potential width, N is the matrix associated with the matrix shape to the shape of the obstacle; the subscript i represents a plurality of different obstacles; represents the total potential energy of the spacecraft in the presence of When an obstacle is the gravitational potential energy

Figure CN105955028AD00082

势和斥+1执於t壬n -执来fr於T梯曲女旦ZfK/岛女挂子六生||於T、、/岛女莫面. Potential performed at t + 1 and non-repellent n - to perform curved staircase fr to T F denier ZfK / F island linked to Subsix green || T ,, / M mo island surface.

[0071] (4) [0071] (4)

[0072] 人工势函数所代表的能量场的梯度用来表示其能量下降的方向,而能量高的地方被障碍物所产生的虚拟斥力势所代替,低势场被规划的期望轨迹所代替,因此沿着梯度方向的路径即为满足任务规划的安全路径; [0072] The gradient of the energy field artificial potential function is used to indicate the direction represented by the energy drop, and high energy where the obstacle is replaced by the generated virtual repulsion potential, low potential field is replaced by a desired trajectory planning, Therefore, the direction of the gradient along the path is the path to meet the security mission planning;

Figure CN105955028AD00083

[0073] 滑横控制的收敛必须满足: [0073] Convergence of the cross slide control must be met:

[0074] (5) [0074] (5)

[0075] -化CObi Inequality理论进行控制器设计;其鲁棒性采用L2增益的形式进 [0075] - of controller design theory CObi Inequality; L2 gain using its robustness form into

[0076] 倘 [0076] In the event

[0077] 其中假巧Z为滑模面;定义Iyapunov函数为: [0077] wherein Z is a false coincidence sliding surface; Iyapunov defined function:

[007引 [007 Cited

Figure CN105955028AD00084

. ) )

[0079] 因为控制稳定性需满足F^O,因此设计控制器为: [0079] Since the control stability to be fulfilled F ^ O, so the design of the controller:

[0080] [0080]

Figure CN105955028AD00085

(S) (S)

[0081 ] 通过验证化mi Iton函数得到: [0081] mi Iton obtained by verifying the function of:

[0082] [0082]

Figure CN105955028AD00086

(9) (9)

[0083] 因此证明控制系统在存在干扰的情况下依然稳定; [0083] In the control system thus demonstrating the presence of interference remained stable;

[0084] 3)鲁棒性分析 [0084] 3) Analysis of Robustness

[0085] 当考虑测量误差时控制力表示为: [0085] When considering a measurement error control is expressed as:

[0086] [0086]

Figure CN105955028AD00087

(10) (10)

[0087]定义^A)和分别为矩阵A的最大和最小特征值;Ft为动力学方程线性化系数矩阵,Ht为测量矩阵;为简化起见,令并定义: [0087] A ^ defined) and the minimum and maximum eigenvalues ​​of matrix A, respectively; Ft matrix kinetic coefficient of linear equations, the measurement Ht of the matrix; for simplicity, and is defined so that:

[008引 [008 Cited

Figure CN105955028AD00091

"I) Ct he / a -VI "I) Ct he / a -VI

[0089] 对于传感器,测量数据采用率为P,在每一时刻有如下表达式: [0089] For the sensor, the measurement data rate using P, at each moment following expression:

[0090] [0090]

Figure CN105955028AD00092

(12) (12)

[0091] 假设追踪航天器的轨迹有99.74%的概率处于安全轨迹范围内,即状态值处于长-口: i +糾区间,其中口= 3. ;因此通过中值定理得到滑模面S的误差限: [0091] Suppose the spacecraft trajectory tracking 99.74% probability that there is within the safe range of tracks, i.e., the state value in the long - port: i + correction section, wherein a = 3; thus the sliding surface S obtained by the Mean Value Theorem error limit:

Figure CN105955028AD00093

[0092] (巧) [0092] (Qiao)

[0093] [0093]

[0094] 此时系统的稳定和传感器的测量精度有关,经过推导得到传感器的测量噪声需满足如下不等式时控制才能保证稳定并处于上述安全轨迹范围内: [0094] At this time, the system stability and accuracy of the sensor related to measurement noise was derived through the sensors need to meet the following inequality control to ensure stability, and when the security is within the above range trajectory:

Figure CN105955028AD00094

[00 巧] (14) [00 Qiao] (14)

[0096] [0096]

[0097] 初跑相对距闻:L-1000 0 0」,目称相对距闻:L-10 0 0]T,未知扰动上限:2m/s2,采样频率:1〇监,位置误差:〇x=〇y=〇z = 0.3m,速度误差:二(7 ,测量角度误差:Oa = Op = 0.0 6°,测量距离误差:Op = O. 5m,推力上限:200N。 [0097] First running distance relative smell: L-1000 0 0 ", said head relative smell from: L-10 0 0] T, the upper limit of unknown disturbances: 2m / s2, the sampling frequency: 1〇 monitoring, position error: 〇x 〇y = = = 〇z 0.3M, speed error: bis (7, measuring angle error: Oa = Op = 0.0 6 °, the measurement distance error: Op = 5m O., thrust limit: 200N.

[0098] W在轨飞行交会任务避障为实例,说明本发明制导控制一体化算法和安全区间计算的有效性。 [0098] W in-orbit rendezvous flight obstacle avoidance task as an example to illustrate the effectiveness of the present invention is guidance and control algorithms and security integration interval calculations. 在追踪过程中,如果传感器不能给出正确的测量信号,后验估计方差会有所增加,从而使得安全边界放大,如果安全边界和障碍物有重合则必须更换传感器或者改变控制参数。 In the tracking process, if the sensor does not give the correct measurement signal posteriori estimation variance will increase, so that the security border enlarged, if the safety margin, and there is an overlap of the obstacle sensor must be replaced or change the control parameters. 如图1所示,真实的运动轨迹处于管状空间内。 As shown in FIG. 1, the true trajectory is within the tubular space. 为了进一步说明安全轨迹和鲁棒分析的可靠性,在不改变目标初始轨道参数的情况下进行了蒙特卡洛打祀实验,如图2所示, 所有的轨迹均处于计算的管状空间内,而与障碍物保持安全距离,从图中可W看出真实的轨迹距离障碍物最近的距离也超过20m。 To further illustrate the robustness and reliability of the safety track analysis, performed without changing the initial target orbit parameters play Si Monte Carlo experiment, as shown, in all the tracks 2 are calculated within the tubular space, and keep a safe distance from obstacles, W from the figure can be seen from the recent real obstacles from the track has more than 20m.

[0099] 并且证明了该算法在动态障碍物规避中的有效性,设计仿真如图3所示,航天器分别在70s,75s ,80s进行展示,追踪航天器可W成功避开动态障碍物,并最终到达目标位置。 [0099] and demonstrate the effectiveness of the algorithm avoid dynamic obstacles in the design simulation as shown, the spacecraft are on display in the 70s, 75s, 80s 3, W can track the spacecraft successfully avoid dynamic obstacles, and finally reach the target position.

[0100] W上内容仅为说明本发明的技术思想,不能W此限定本发明的保护范围,凡是按照本发明提出的技术思想,在技术方案基础上所做的任何改动,均落入本发明权利要求书的保护范围之内。 [0100] W content merely illustrate the technical idea of ​​the present invention, W is not to limit the scope of this invention, all made in accordance with the technical idea of ​​the present invention, any changes made on the basis of the aspect, the present invention fall within the the scope of protection of the claims.

Claims (1)

  1. 1. 一种航天器在轨规避制导控制一体化算法,其特征在于,包括以下步骤: 1) 建立航天器相对运动方程以目标轨道坐标系为参考坐标系,建立航天器相对运动动力学方程: X = Ax + Dx + u + d .(1). 矩阵A和D描述为: A spacecraft orbit avoidance guidance control integration algorithm, characterized by comprising the following steps: 1) establishing relative motion equation of the spacecraft to a target track as the reference coordinate system coordinate system established relative motion of spacecraft dynamics equation: X = Ax + Dx + u + d (1) is described as a matrix A and D..:
    Figure CN105955028AC00021
    其中,ω为目标航天器的轨道角速度,u为追踪航天器的控制输出,d为未建模误差,包括引力梯度误差,各种摄动,目标未知控制力,或者其他不可测量和估计的未知干扰; 其中的动力学方程可以更换为任何航天器相对运动动力学模型; 2) 设计势函数和滑模控制一体化制导控制算法航天器的势函数定义在状态空间中,设状态变量为X,期望的状态为xd;引力势函数促使追踪航天器到达预设的目标状态,因此引力势函数设计为: Where, [omega] is the angular velocity of the target spacecraft orbit, u is the output of the tracking control spacecraft, d is unmodeled errors, including errors gravity gradient, various perturbation, control target is unknown, or other estimates of unmeasured and unknown interference; wherein the kinetic equation can be replaced by any relative motion of spacecraft dynamics model; 2) design potential function and potential function guided sliding mode control integrated spacecraft control algorithm is defined in the state space, the reset state variable X, desired state xd; gravitational potential function to promote tracking the spacecraft reaches the preset target state, the gravitational potential function is designed to:
    Figure CN105955028AC00022
    引力势函数中同时包含了位置和速度信息,描述了期望跟踪的位置和其运动的趋势; 其中PP、PV为正定矩阵; 斥力势选用高斯函数: Gravitational potential function contains both position and velocity information, describes the trend of the desired track position and its movement; wherein PP, PV is a positive definite matrix; Potential repulsion selected Gaussian function:
    Figure CN105955028AC00023
    其中,Φ表示斥力势的高,σ表示斥力势的宽,矩阵N是与障碍物形状有关的外形矩阵;下标i表示多个不同的障碍物;总的势能表示航天器在存在障碍物的情况下势能是引力势和斥力势的和;势函数的梯度提供滑模控制的滑模面: s = νχφ + νχφ = νχφα + V χφ,. + V χφα + V χφν (4) 人工势函数所代表的能量场的梯度用来表示其能量下降的方向,而能量高的地方被障碍物所产生的虚拟斥力势所代替,低势场被规划的期望轨迹所代替,因此沿着梯度方向的路径即为满足任务规划的安全路径; 滑模控制的收敛必须满足: sri:<〇(5) 采用Hamilton-Jacobi Inequality理论进行控制器设计;其鲁棒性采用L2增益的形式进行描述: Wherein, [Phi] represents high potential repulsion, [sigma] represents the repulsive potential is wide, the matrix N is an external shape of the matrix associated with the obstacle; the subscript i indicates a plurality of different obstacles; represents the total potential energy of the spacecraft in the presence of an obstacle a case where the potential energy is gravitational potential and the potential and repulsion; gradient of the potential function to provide a sliding surface sliding mode control: s = νχφ + νχφ = νχφα + V χφ ,. + V χφα + V χφν (4) artificial potential function representing the gradient energy field used to indicate the direction of decline of energy, where the high energy generated is replaced by a virtual obstacle repulsion potential, low potential field is replaced by a desired trajectory planning, and therefore the path along the gradient direction is met when a secure path planning task; sliding mode control convergence must be met: sri: <square (5) using the Hamilton-Jacobi Inequality controller design theory; L2 which takes the form of robust gain will be described:
    Figure CN105955028AC00024
    其中假设z为滑模面;定义lyapunov函数为: Wherein z is assumed sliding surface; lyapunov function is defined as:
    Figure CN105955028AC00031
    因为控制稳定性需满足訪切,因此设计控制器为: Because the need to meet the access control stability cut, so the design of the controller:
    Figure CN105955028AC00032
    通过验证Hamilton函数得到: Hamilton verification function obtained by:
    Figure CN105955028AC00033
    因此证明控制系统在存在干扰的情况下依然稳定; 3)鲁棒性分析当考虑测量误差时控制力表示为: Thus demonstrating that the control system in the presence of interference remained stable; 3) is expressed as Robust analysis of control when considering measurement error:
    Figure CN105955028AC00034
    定义1(A)和分别为矩阵A的最大和最小特征值;Ft为动力学方程线性化系数矩阵, Ht为测量矩阵;为简化起见,令C ,并定义: Defined 1 (A), and wherein the maximum and minimum values ​​of the matrix A; Ft kinetically linear matrix equation coefficients, Ht of the measurement matrix; for simplicity, so that C, and define:
    Figure CN105955028AC00035
    d: =bc/a+l 对于传感器,测量数据采用率为P,在每一时刻有如下表达式: d: = bc / a + l to the sensor, using the measured data rate P, the following expression at each moment:
    Figure CN105955028AC00036
    假设追踪航天器的轨迹有99.74 %的概率处于安全轨迹范围内,即状态值处于[i-?/ 1 + ;?]区间,其中¥ = 3..^];因此通过中值定理得到滑模面8的误差限: Suppose trajectory tracking the spacecraft has a 99.74% probability that the track is in the safe range, i.e., the state value is [i - / 1 +;??] Interval, where ¥ = 3 .. ^]; Sliding thus obtained by the Mean Value Theorem error limit surface 8:
    Figure CN105955028AC00037
    此时系统的稳定和传感器的测量精度有关,经过推导得到传感器的测量噪声需满足如下不等式时控制才能保证稳定并处于上述安全轨迹范围内: At this time, the system stability and accuracy of the sensor related to measurement noise was derived through the sensors need to meet the following inequality control to ensure stability, and when the security is within the above range trajectory:
CN 201610388966 2016-06-02 2016-06-02 To avoid the kind of spacecraft in orbit guidance and control algorithms body CN105955028B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN 201610388966 CN105955028B (en) 2016-06-02 2016-06-02 To avoid the kind of spacecraft in orbit guidance and control algorithms body

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN 201610388966 CN105955028B (en) 2016-06-02 2016-06-02 To avoid the kind of spacecraft in orbit guidance and control algorithms body

Publications (2)

Publication Number Publication Date
CN105955028A true true CN105955028A (en) 2016-09-21
CN105955028B CN105955028B (en) 2018-09-07

Family

ID=56908630

Family Applications (1)

Application Number Title Priority Date Filing Date
CN 201610388966 CN105955028B (en) 2016-06-02 2016-06-02 To avoid the kind of spacecraft in orbit guidance and control algorithms body

Country Status (1)

Country Link
CN (1) CN105955028B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107168357A (en) * 2017-06-30 2017-09-15 北京航空航天大学 Spacecraft attitude maneuver control method giving consideration to attitude constraint and unwinding resistance

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090076728A1 (en) * 2004-11-15 2009-03-19 Airbus France Aircraft terrain avoidance and alarm method and device
CN102081752A (en) * 2011-01-27 2011-06-01 西北工业大学 Dynamic flight path planning method based on adaptive mutation genetic algorithm
CN102354218A (en) * 2011-06-24 2012-02-15 哈尔滨工业大学 Sampling control method for relative motion of spacecrafts
CN102419597A (en) * 2011-12-05 2012-04-18 哈尔滨工业大学 Method for consistently controlling gesture of large-scale formation spacecraft with limited relative gesture
CN103019239A (en) * 2012-11-27 2013-04-03 江苏大学 Trajectory tracking sliding mode control system and control method for spraying mobile robot
CN103399986A (en) * 2013-07-02 2013-11-20 哈尔滨工业大学 Space manipulator modeling method based on differential geometry
CN103869822A (en) * 2014-04-01 2014-06-18 西北工业大学 Multiple-rotor-wing unmanned aerial vehicle sensing and avoiding system and avoiding method thereof
CN104704542A (en) * 2012-08-01 2015-06-10 爱维奥斯尼克空间科技有限公司 Direct broadcast alert apparatus and method
CN104842355A (en) * 2015-01-20 2015-08-19 西北工业大学 Mixed-integer prediction control method for redundant space robot under obstacle avoidance restraint

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090076728A1 (en) * 2004-11-15 2009-03-19 Airbus France Aircraft terrain avoidance and alarm method and device
CN102081752A (en) * 2011-01-27 2011-06-01 西北工业大学 Dynamic flight path planning method based on adaptive mutation genetic algorithm
CN102354218A (en) * 2011-06-24 2012-02-15 哈尔滨工业大学 Sampling control method for relative motion of spacecrafts
CN102419597A (en) * 2011-12-05 2012-04-18 哈尔滨工业大学 Method for consistently controlling gesture of large-scale formation spacecraft with limited relative gesture
CN104704542A (en) * 2012-08-01 2015-06-10 爱维奥斯尼克空间科技有限公司 Direct broadcast alert apparatus and method
CN103019239A (en) * 2012-11-27 2013-04-03 江苏大学 Trajectory tracking sliding mode control system and control method for spraying mobile robot
CN103399986A (en) * 2013-07-02 2013-11-20 哈尔滨工业大学 Space manipulator modeling method based on differential geometry
CN103869822A (en) * 2014-04-01 2014-06-18 西北工业大学 Multiple-rotor-wing unmanned aerial vehicle sensing and avoiding system and avoiding method thereof
CN104842355A (en) * 2015-01-20 2015-08-19 西北工业大学 Mixed-integer prediction control method for redundant space robot under obstacle avoidance restraint

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
MINGMING WANG 等: "A non-linear model predictive controller with obstacle avoidance for a space robot", 《ADVANCES IN SPACE RESEARCH》 *
陈统 等: "椭圆轨道航天器自主接近的制导律研究", 《宇航学报》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107168357A (en) * 2017-06-30 2017-09-15 北京航空航天大学 Spacecraft attitude maneuver control method giving consideration to attitude constraint and unwinding resistance
CN107168357B (en) * 2017-06-30 2018-08-07 北京航空航天大学 Species considered anti-unwinding constraints pose spacecraft Maneuver Control

Also Published As

Publication number Publication date Type
CN105955028B (en) 2018-09-07 grant

Similar Documents

Publication Publication Date Title
Qu et al. A new analytical solution to mobile robot trajectory generation in the presence of moving obstacles
Ge et al. Dynamic motion planning for mobile robots using potential field method
Webb et al. Kinodynamic RRT*: Asymptotically optimal motion planning for robots with linear dynamics
Kuderer et al. Feature-Based Prediction of Trajectories for Socially Compliant Navigation.
Huang Velocity planning for a mobile robot to track a moving target—a potential field approach
Lindstrom et al. Detecting and tracking moving objects from a mobile platform using a laser range scanner
Cheah et al. Region-based shape control for a swarm of robots
Das et al. A vision-based formation control framework
Yang et al. A bioinspired neurodynamics-based approach to tracking control of mobile robots
Baras et al. Decentralized control of autonomous vehicles
Zhang et al. Learning deep control policies for autonomous aerial vehicles with mpc-guided policy search
Kretzschmar et al. Socially compliant mobile robot navigation via inverse reinforcement learning
Matveev et al. Real-time navigation of mobile robots in problems of border patrolling and avoiding collisions with moving and deforming obstacles
Manchester et al. Circular navigation missile guidance with incomplete information and uncertain autopilot model
JP2003241836A (en) Control method and apparatus for free-running mobile unit
Mellinger et al. Trajectory generation and control for precise aggressive maneuvers with quadrotors
Pathak et al. An integrated path-planning and control approach for nonholonomic unicycles using switched local potentials
Liang et al. Decentralized formation control and obstacle avoidance for multiple robots with nonholonomic constraints
Hennes et al. Multi-robot collision avoidance with localization uncertainty
Althoff et al. Safety assessment of robot trajectories for navigation in uncertain and dynamic environments
Ye Navigating a mobile robot by a traversability field histogram
Mueller et al. A model predictive controller for quadrocopter state interception
CN102323819B (en) Intelligent wheelchair outdoor navigation method based on coordinated control
Saska et al. Motion planning and control of formations of micro aerial vehicles
Monteiro et al. Attractor dynamics approach to formation control: theory and application

Legal Events

Date Code Title Description
C06 Publication
C10 Entry into substantive examination
GR01