Neural control of hypersonic flight vehicle model via time-scale decomposition with throttle setting constraint

Considering the use of digital computers and samplers in the control circuitry, this paper describes the controller design in discrete time for the longitudinal dynamics of a generic hypersonic flight vehicle (HFV) with Neural Network (NN). Motivated by time-scale decomposition, the states are decomposed into slow dynamics of velocity, altitude and fast dynamics of attitude angles. By command transformation, the reference command for γ?θ _p ?q subsystem is derived from h?γ subsystem. Furthermore, to simplify the backstepping design, we propose the controller for γ?θ _p ?q subsystem from prediction function without virtual controller. For the velocity subsystem, the throttle setting constraint is considered and new NN adaption law is designed by auxiliary error dynamics. The uniformly ultimately boundedness (UUB) of the system is proved by Lyapunov stability method. Simulation results show the effectiveness of the proposed algorithm.     

Terminal sliding mode control for aeroelastic systems

An aeroelastic system is a nonlinear system with two freedoms, i.e., the plunge displacement and the pitch angle, in a dynamic system model. A chaos effect or a limit cycle oscillation is presumably attributed to the nonlinear effect of the pitch angle mentioned above or the interaction between the aerodynamic behaviors. It is that a single trailing edge input in an aeroelastic system is employed as a way to suppress the limit cycle oscillation with an exclusive choice between the plunge displacement and the pitch angle for a control law design. Consequently, the remaining inevitably turns into an internal dynamics, whose stability is adversely affected by the flight speed and structure parameters, a problem improved by no means using a singe control input design. Toward this end, this work presents a controller design criterion with multiple input channels for both the leading and training edges to remove the uncertainty effect of internal dynamics, and render more room for the response design of the plunge displacement as well as the pitch angle. Mostly due to external disturbance and unknown uncertainty, there is a deviation between the intended and implemented system performances for a robust control design, a mainstream research issue in the modern control. As a consequence of a sliding mode control utilized here, the limit cycle oscillation suffered in an aeroelastic system is removed effectively by the use of a terminal sliding mode control, and the chattering phenomenon seen in the control signal is hence eliminated by his method. It is seen from simulations that the control system is stably assured to reach the target within a limited time frame with an addition of a saturation function to the control law.     

Robust adaptive dynamic surface control design for a flexible air-breathing hypersonic vehicle with input constraints and uncertainty

The flight control problem of a flexible air-breathing hypersonic vehicle is presented in the presence of input constraint and aerodynamic uncertainty. A control-oriented model, where aerodynamic uncertainty and the strong couplings between the engine and flight dynamics are included, is derived to reduce the complexity of controller design. The flexible dynamics are viewed as perturbations of the model. They are not taken into consideration at the level of control design, the influence of which is evaluated through simulation. The control-oriented model is decomposed into velocity subsystem and altitude subsystem, which are controlled separately. Then robust adaptive controller is developed for the velocity subsystem, while the controller which combines dynamic surface control and radial basis function neural network is designed for the altitude subsystem. The unknown nonlinear function is approximated by the radial basis function neural network. Minimal-learning parameter technique is utilized to estimate the maximum norm of ideal weight vectors instead of their elements to reduce the computational burden. To handle input constraints, additional systems are constructed to analyze their impact, and the states of the additional systems are employed at the level of control design and stability analysis. Besides, “explosion of terms” problem in the traditional backstepping control is circumvented using a first-order filter at each step. By means of Lyapunov stability theory, it is proved theoretically that the designed control law can assure that tracking error converges to an arbitrarily small neighborhood around zero. Simulations are performed to demonstrate the effectiveness of the presented control scheme in coping with input constraint and aerodynamic uncertainty.     

漂浮基柔性空间机器人的鲁棒控制及振动抑制

讨论了漂浮基柔性空间机器人系统的动力学建模、运动控制算法设计以及关节、臂双重柔性振动的分级主动抑制问题. 利用系统动量、动量矩守恒关系和拉格朗日-假设模态法对系统进行动力学分析,建立系统动力学方程. 基于奇异摄动法,将系统分解为表示系统刚性运动部分的慢变子系统, 表示由柔性臂引起的系统柔性运动部分的快变子系统1和表示由柔性关节引起的系统柔性运动部分的快变子系统2. 针对慢变子系统提出一种鲁棒控制方法来补偿系统参数的不确定性和柔性关节引起的转动误差,实现系统期望运动轨迹的渐近跟踪;针对快变子系统1采用线性二次型最优控制器来抑制由柔性臂引起的系统柔性振动;针对快变子系统2设计了基于机械臂和电机转子的转角速度差值的反馈控制器来抑制由柔性关节引起的系统柔性振动. 因此,系统的总控制律为以上3个子系统控制律的综合. 最后通过仿真实验证明了所提出的混合控制方法的有效性.      

Velocity-sensorless proportional–derivative trajectory tracking control with active damping for quadcopters

The proposed observer-based control mechanism solves the trajectory tracking problem in the presence of external disturbances with the reduction in sensor numbers. This systematically considers the quadcopter nonlinear dynamics and parameter and load variations by adopting the standard controller design approach based on a disturbance observer (DOB). The first feature is designing first-order observers for estimating the velocity and angular velocity error, with their parameter independence obtained from the DOB design technique. As the second feature, the resultant velocity observer-based control action including active damping and DOBs secures first-order tracking behavior for the position and attitude (angle) loops through pole zero cancellation, thereby forming a proportional–derivative control structure. Closed-loop analysis results reveal the performance recovery and steady-state error removal properties in the absence of tracking error integrators. The numerical verification confirms the effectiveness of the proposed mechanism using MATLAB/Simulink.

     

Distributed time-varying formation tracking of multi-quadrotor systems with partial aperiodic sampled data

In this article, a distributed formation tracking controller is proposed for Multi-agent systems (MAS) consisting of quadrotors. It is considered that each quadrotor in the MAS only shares its translation position information with its neighbors. Moreover, position information is transmitted at nonuniform and asynchronous time instants. The control system is divided into an outer-loop for the position control and an inner-loop for the attitude control. A continuous-discrete time observer is used in the outer-loop to estimate both position and velocity of the quadrotor and its neighbors using discrete position information it receives. Then, these estimated states are used to design the position controller in order to enable quadrotors to generate the required geometric shape. A finite-time attitude controller is designed to track the desired attitude as dictated by the position controller. Finally, a closed-loop stability analysis of the overall system including nonlinear coupling is performed.

     

Decentralized adaptive neural control of nonlinear systems with unknown time delays

In this paper, a novel decentralized adaptive neural control scheme is proposed for a class of uncertain multi-input and multi-output (MIMO) nonlinear time-delay systems. RBF neural networks (NNs) are used to tackle unknown nonlinear functions, then the decentralized adaptive NN tracking controller is constructed by combining Lyapunov–Krasovskii functions and the dynamic surface control (DSC) technique along with the minimal-learning-parameters (MLP) algorithm. The proposed controller guarantees semi-global uniform ultimate boundedness (SGUUB) of all the signals in the closed-loop large-scale system, while the tracking errors converge to a small neighborhood of the origin. An advantage of the proposed control scheme lies in that the number of adaptive parameters for each subsystem is reduced to one, and three problems of “computational explosion,” “dimension curse” and “controller singularity” are solved, respectively. Finally, a numerical simulation is presented to demonstrate the effectiveness and performance of the proposed scheme.     

A controllability perspective of dynamic soaring

Dynamic soaring is an exquisite flying technique to acquire energy from the atmospheric wind shear. In this study, a geometric nonlinear controllability analysis of an unmanned aerial vehicle (UAV) under dynamic soaring conditions is performed. To achieve such an objective, the state-of-the-art mathematical tools of nonlinear controllability are summarized and presented to an aeronautical engineering audience. The dynamic soaring optimal control problem is then formulated and solved numerically. The controllability of the UAV along the optimal soaring trajectory is analyzed. More importantly, the geometric nonlinear controllability characteristics of generic flight dynamics are analyzed in the presence and absence of wind shear to provide a controllability explanation for the role of wind shear in the physics of dynamic soaring flight. It is found that the wind shear is instrumental in ensuring controllability as it allows the UAV attitude controls (pitch and roll) to play the role of thrust in controlling the flight path angle. The presented analysis represents a controllability-based mathematical proof for the energetics of flight physics.     

采用动量轮及推进器的微小卫星的姿态机动控制(英文)

提出了一种利用偏置动量轮及推进器实现大角度姿态机动控制的方法。首先建立轨道系下的卫星模型及动量轮推进器的模型,并基于该模型采用动量轮及推进器结合的反馈线性化控制方法,最后设计了大角度机动的参考轨迹。仿真和分析结果表明,文中的控制方法可以在45 s内使卫星机动40°,并在100 s内达到180°大角度,控制精度达到0.4°。可以无需对动量轮进行加减速操作而进行实时的姿态机动。不仅能满足实时性需要,同时可以避免动量轮饱和,降低能源消耗,为微小卫星姿态控制系统的工程实现提供了非常有价值的参考。     

全柔性空间机器人运动振动一体化输入受限重复学习控制

探究基座、臂、关节全柔性影响下空间机器人动力学模拟、运动控制及基座、臂、关节三重柔性振动主动抑制的问题, 设计了不基于系统模型信息的运动振动一体化输入受限重复学习控制算法. 将柔性基座与关节等效为线性弹簧与扭转弹簧, 柔性臂视为欧拉-伯努利梁模型, 利用拉格朗日方程与假设模态法建立动力学模型, 然后, 用奇异摄动理论将模型分解为包含刚性变量与臂柔性振动的慢变子系统, 包含基座、关节柔性振动的快变子系统, 并分别设计相应的子控制器, 构成了带关节柔性补偿的一体化控制算法. 针对慢变子系统, 提出输入受限重复学习控制算法, 由双曲正切函数, 饱和函数与重复学习项构成, 双曲正切函数与饱和函数实现输入力矩受限要求, 重复学习项补偿周期性系统误差, 以完成对基座姿态、关节铰周期轨迹的渐进稳定追踪. 然而, 为了同时抑制慢变子系统臂的柔性振动, 运用虚拟力的概念, 构造同时反映臂柔性振动与系统刚性运动的混合轨迹, 提出了基于虚拟力概念的输入受限重复学习控制器, 保证基座、关节轨迹精确追踪的同时, 对臂的柔性振动主动抑制. 针对快变子系统, 采用线性二次最优控制算法抑制基座与关节的柔性振动. 仿真结果表明: 控制器适用于一般柔性非线性系统, 满足输入力矩受限要求, 实现对周期信号的高精度追踪, 有效抑制基座、臂、关节的柔性振动, 证实算法的可行性.      

Combined control of fast attitude maneuver and stabilization for large complex spacecraft

In remote sensing or laser communication space missions, spacecraft need fast maneuver and fast stabilization in order to accomplish agile imaging and attitude tracking tasks. However, fast attitude maneuvers can easily cause elastic deformations and vibrations in flexible appendages of the spacecraft. This paper focuses on this problem and deals with the combined control of fast attitude maneuver and sta- bilization for large complex spacecraft. The mathematical model of complex spacecraft with flexible appendages and momentum bias actuators on board is presented. Based on the plant model and combined with the feedback controller, modal parameters of the closed-loop system are calculated, and a multiple mode input shaper utilizing the modal information is designed to suppress vibrations. Aiming at reducing vibrations excited by attitude maneuver, a quintic polynomial form rotation path planning is proposed with constraints on the actuators and the angular velocity taken into account. Attitude maneuver simulation results of the control systems with input shaper or path planning in loop are sepa- rately analyzed, and based on the analysis, a combined control strategy is presented with both path planning and input shaper in loop. Simulation results show that the combined control strategy satisfies the complex spacecraft＇s require- ment of fast maneuver and stabilization with the actuators＇ torque limitation satisfied at the same time.     

Dynamic control for permanent magnet synchronous generator system using novel modified recurrent wavelet neural network

Because permanent magnet synchronous generator (PMSG) system driven by permanent magnet synchronous motor (PMSM) based on wind turbine emulator (WTE) is a nonlinear and time-varying system with high complication, an accurate dynamic model of the PMSG system directly driven by WTE is difficult to establish for the linear controller design. In order to conquer this difficulty and improve the robustness of dynamic system, the PMSG system controlled by the online-tuned parameters of the novel modified recurrent wavelet neural network (NN)-controlled system is proposed to control output voltages and powers of controllable rectifier and inverter in this study. First, a closed-loop PMSM-driven system based on WTE is designed for driving the PMSG system to generate output power. Second, the rotor speeds of the PMSG, the voltages, and currents of the two power converters are detected simultaneously to yield maximum power output. In addition, two sets of the online-tuned parameters of the modified recurrent wavelet NN controllers in the controllable rectifier and inverter are developed for the voltage-regulating controllers in order to improve output performance. Finally, some experimental results are verified to show the effectiveness of the proposed novel modified recurrent wavelet NN controller for the power output of the PMSG system driven by WTE.     

Coupling-observer-based nonlinear control for flexible air-breathing hypersonic vehicles

This paper investigates the nonlinear control problem for flexible air-breathing hypersonic vehicles (FAHVs). The coupling dynamics between flexible and rigid-body parts of FAHVs may cause degradation of control performance or high-frequency oscillations of control input and flexible state. In this paper, the flexible effects produced by the coupling are modeled as a kind of unknown disturbance and included in the new control-design model, for which a coupling observer is constructed to estimate these effects. Thus, a novel nonlinear composite control strategy, which combines a coupling-observer-based feedforward compensator and a dynamic-inversion-based feedback controller, is proposed to reject the flexible effects on pitch rate and track desired trajectories of velocity and flight-path angle. The stability of composite closed-loop system is analyzed by using the Lyapunov theory. Simulation results on a full nonlinear model of FAHVs demonstrate that the presented controller is more effective by comparison with the previous scheme.     

可重复使用运载器大姿态机动自抗扰控制

针对可重复使用运载器大俯仰角或偏航角转弯机动而产生的姿态角奇异的控制问题,提出了基于四元数的自抗扰控制方法。通过两级跟踪微分器从期望四元数中逐步得到三通道解耦的角加速度信号,然后利用扩张状态观测器观测模型中的不确定项,最终采用动态逆得到解耦的三通道发动机等效摆角或RCS(Reaction Control System)等控制信号,并设计了数字滤波器对弹性振动与液体晃动信号进行滤波处理。考虑到系统模型具有非线性、不确定性、11阶弹性振动、一阶液体晃动、风干扰和气动偏差等多种外部扰动条件,对可重复使用运载器从主动段到再入飞行段进行了非线性六自由度仿真分析。仿真结果表明,基于四元数的自抗扰姿态控制器具有快速、平稳、超调量小、抗干扰能力强、无系统抖振且控制参数较少的特点。     

Comparative dynamic control for continuously variable transmission with nonlinear uncertainty using blend amend recurrent Gegenbauer-functional-expansions neural network

Because the nonlinear uncertainty of the continuously variable transmission system operated by the synchronous reluctance motor is unknown, control performance obtained for classical linear controller is poor, with comparison to more complex, nonlinear control methods. Due to good learning skill online, a blend amended recurrent Gegenbauer-functional-expansions neural network (NN) control system was developed to return to the nonlinear uncertainties behavior. The blend amended recurrent Gegenbauer-functional-expansions NN control system can fulfill overseer control, amended recurrent Gegenbauer-functional-expansions NN control with an adaptive dharma and recompensed control with a reckoned dharma. In addition, according to the Lyapunov stability theorem, the adaptive dharma in the amended recurrent Gegenbauer-functional-expansions NN and the reckoned dharma of the recompensed controller are established. Furthermore, an altered artificial bee colony optimization yields two varied learning rates for two parameters to find two optimal values, which helped improving convergence. Finally, various comparisons of the experimental results are demonstrated to confirm that the proposed control system can result better control performance.     

Robust attitude control for rapid multi-target tracking in spacecraft formation flying

A robust attitude tracking control scheme for spacecraft formation flying is presented. The leader spacecraft with a rapid mobile antenna and a camera is modeled. While the camera is tracking the ground target, the antenna is tracking the follower spacecraft. By an angular velocity constraint and an angular constraint, two methods are proposed to compute the reference attitude profiles of the camera and antenna, respectively. To simplify the control design problem, this paper first derives the desired inverse system （DIS）, which can convert the attitude tracking problem of 3D space into the regulator problem. Based on DIS and sliding mode control （SMC）, a robust attitude tracking controller is developed in the presence of mass parameter uncertainties and external disturbance. By Lyapunov stability theory, the closed loop system stability can be achieved. The numerical simulations show that the proposed robust control scheme exhibits significant advantages for the multi-target attitude tracking of a two-spacecraft formation.     

漂浮基柔性两杆空间机械臂的关节运动鲁棒控制与柔性振动最优控制Robust joint motion control and vibration optimal control for a free-floating two-flexible-link space manipulator

讨论了载体位置、姿态均不受控情况下,具有有界干扰及有界未知参数的漂浮基柔性两杆空间机械臂的具有鲁棒性的关节运动控制与柔性振动最优控制算法设计问题。首先选择合理的联体坐标系,利用拉格朗日方程并结合动量守恒原理得到漂浮基柔性两杆空间机械臂系统的动力学方程。通过合理选择联体坐标系与利用奇异摄动理论,实现了两个柔性杆柔性振动之间、关节运动与两柔性杆柔性振动的解耦,得到了柔性两杆空间机械臂的慢变子系统与柔性臂快变子系统。针对两个子系统设计相应的控制规律,即增广鲁棒慢变子系统控制律与柔性臂快变子系统最优控制律,这两个相应的子系统控制规律综合到一起构成飘浮基柔性两杆空间机械臂总的关节运动与臂柔性振动控制的组合控制律。系统的数值仿真证实了方法的有效性。该控制方案不需要直接测量漂浮基的位置、移动速度和移动加速度。     

Adaptive sliding mode control of dynamic system using RBF neural network

This paper presents a robust adaptive sliding mode control strategy using radial basis function (RBF) neural network (NN) for a class of time varying system in the presence of model uncertainties and external disturbance. Adaptive RBF neural network controller that can learn the unknown upper bound of model uncertainties and external disturbances is incorporated into the adaptive sliding mode control system in the same Lyapunov framework. The proposed adaptive sliding mode controller can on line update the estimates of system dynamics. The asymptotical stability of the closed-loop system, the convergence of the neural network weight-updating process, and the boundedness of the neural network weight estimation errors can be strictly guaranteed. Numerical simulation for a MEMS triaxial angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive RBF sliding mode control scheme.     

低成本车载GPS/INS组合导航姿态角更新算法

低成本INS系统的元件误差严重影响INS导航精度.针对车载系统,提出一种低成本车载GPS/INS组合导航姿态角更新算法.首先在GPS/INS组合导航Kalman滤波方程基础上,给出两种姿态角更新的观测方程.然后给出利用GPS测速确定航向角的原理,并且对低成本车载INS系统的俯仰角和翻滚角进行了分析,指出由INS随机误差造成的俯仰角和翻滚角误差比其本身量值要大,建议令俯仰角和翻滚角数值保持不变.利用实测算例确定了不同速度下的航向角精度,并且验证了该算法的有效性,以及相对于基于位置、速度组合的Kalman滤波,导航精度有明显提高.     

Detumbling strategy and coordination control of kinematically redundant space robot after capturing a tumbling target

This paper focuses on the motion planning to detumble and control of a space robot to capture a non-cooperative target satellite. The objective is to construct a detumbling strategy for the target and a coordination control scheme for the space robotic system in post-capture phase. First, the dynamics of the kinematically redundant space robot after grasping the target is presented, which lays the foundation for the coordination controller design. Subsequently, optimal detumbling strategy for the post-capture phase is proposed based on the quartic B\(\acute{\text{ e }}\)zier curves and adaptive particle swarm optimization algorithm subject to the specific constraints. Both detumbling time and control torques were taken into account for the generation of the optimal detumbling strategy. Furthermore, a coordination control scheme is designed to track the designed reference path while regulating the attitude of the chaser to a desired value. The space robot successfully dumps the initial velocity of the tumbling satellite and controls the base attitude synchronously. Simulation results are presented for detumbling a target with rotational motion using a seven degree-of-freedom redundant space manipulator, which demonstrates the feasibility and effectiveness of the proposed method.