多枚倾斜转弯导弹的滚转通道之分布式有限时间姿态协调控制

对多枚倾斜转弯(BTT)导弹设计滚转通道自动驾驶仪时,基于分布式协调控制理论,本文提出了一类分布式有限时间姿态协调控制器.由于BTT导弹的气动参数变化强烈、机动要求高,要求控制器响应速度高,抗干扰能力强.本文基于有限时间控制技术,并结合多智能体系统的协调控制理论,对多枚BTT导弹滚转通道提出了一种分布式有限时间姿态协调控制律.在该控制律作用下,所有的BTT导弹通过相互协调,其滚转角可以在有限时间内达到一致并为给定的参考指令信号.仿真结果表明了该方法的有效性.     

BTT导弹滚转通道模型参考变结构自动驾驶仪设计

BTT导弹的气动参数强烈变化特点、大机动需求和控制技术要求导弹滚转通道必须具有快的响应速度和强的抗干扰能力.针对这些特点,引入了模型参考变结构控制(MRVSC)设计导弹滚转通道自动驾驶仪,应用Simulink对PID和MRVSC两种自动驾驶仪进行仿真分析;在飞行高度为200m时,PID和MRVSC自动驾驶仪对理想弹道的跟踪效果几乎相同;在10km高度,PID方法的跟踪效果明显变差,而MRVSC具有同样的跟踪效果;仿真结果表明,MRVSC自动驾驶仪能够保证快的响应速度和抵抗参数大范围变化.     

高超声速飞行器鲁棒自动驾驶仪设计研究

针对高超声速飞行器姿态控制问题,设计了具有鲁棒特性的自动驾驶仪;针对带有耦合特性的面对称外形高超声速飞行器的动力学模型,在存在气动参数摄动的情形下,基于数值有界不确定性描述形式,利用鲁棒控制理论和线性矩阵不等式(LMl)求解方法,设计了三通道鲁棒的自动驾驶仪控制器;最后仿真结果表明,所设计的三通道自动驾驶仪使得高超声速飞行器获得理想的动态性能和稳态品质,并对气动参数和通道间的耦合不确定性具有较强的鲁棒性.     

BTT导弹变结构自适应控制仿真研究

一种变结构自适应控制律,可以不依赖于系统的精确数学模型,但对于BTT导弹气动参数不确定性具有良好的控制效果.采用Matlab,分别对BTT导弹滚转、偏航以及俯仰三个通道进行数值仿真,接着又对闭环系统进行了仿真验证,根据对仿真结果的分析,对该控制律进行了进一步的改进.所设计的改进控制律很好地解决了导弹数学模型不能精确获得以及参数大范围变化的问题,并且在很大程度上克服了导弹各通道间存在的耦合现象,与其它控制方法比较,具有算法相对简单,并且易于仿真验证的特点,对BTT导弹自动驾驶仪研究具有很好的指导意义.     

机动再入飞行器自适应自动驾驶仪设计

解决了机动再入飞行器在气动系数变化范围大和气动耦合严重等恶劣条件下的姿态和过载控制问题. 为了能充分利用飞行器可测量信息提高系统自适应能力, 提出了滚动通道状态方程参数辨识—级点配置—前馈补偿自适应控制和横向通道基于攻角反馈以过载为主控信号的变参数自适应控制的自动驾驶仪设计方法. 通过对某飞行器的制导控制系统仿真, 可以看出该自动驾驶仪使飞行器有很好的飞行性能.     

空空导弹增益调度鲁棒H_∞控制自动驾驶仪设计

为了满足空空导弹大空域、高机动飞行的技术指标要求,提出了BTT导弹的增益调度鲁棒H∞自动驾驶仪设计方法;建立了BTT导弹线性变参数(LPV)系统数学模型;提出了LPV系统增益调度鲁棒H∞控制设计方法和设计过程;通过把BTT导弹自动驾驶仪分为俯仰、偏航/滚转通道分别进行设计,并以俯仰通道为例进行了仿真验证;仿真结果表明该控制算法具有良好的控制性能,从而,验证了增益调度鲁棒H∞控制算法的正确性和有效性。     

基于模糊树逆方法的高超飞行器变质心控制

本文针对高超飞行器变质心姿态动力学模型所具有的高度非线性、多变量、强耦合特性,通过合理的简化,得到了一个耦合的非线性动力学系统;根据简化模型的特点,将该模型分为俯仰偏航通道模型和滚动通道模型,通道间耦合视为扰动.应用模糊树模型逼近俯仰偏航通道的逆模型,实现了俯仰偏航通道解耦线性化,对各线性子系统设计闭环控制器,实现了飞行器俯仰偏航通道姿态角的跟踪;应用预测变结构方法保证了滚动通道的快速稳定并且无抖振现象.最后,将该方法应用于高超飞行器姿态系统控制的仿真研究,表明了本文方法的有效性和可行性.     

基于FLSIM的自动驾驶仪建模及仿真

以仿真一体化软件--FLSIM为基础,实现对自动驾驶仪的建模和仿真.建模从基础的状态方程开始,给出FLSIM识别的状态方程;并在此基础上,按内环(俯仰角、滚转角、偏航角)和外环(高度、航向等)控制的分类实现自动驾驶仪模型建立.通过仿真结果的静态和动态指标进行寻优仿真试验以调整模型参数,最终达到优化模型参数的目的.最后以B747为例,从建模到试验运行以及优化参数,获得其自动驾驶仪的仿真实现.证明其是灵活和方便的,于实际情况一致.     

卫星制导炸弹模型参考变结构控制器设计

为减小卫星制导炸弹各通道间的耦合影响,提出了机弹分离后快速单通道滚转控制至滚转稳定再介入俯仰、偏航控制的控制策略,建立了各通道的飞行控制模型.针对炸弹大空域参数时变特点,给出了一种模型参考变结构控制的方法来适应参数大范围的变化,提高了控制精度.对某型号卫星制导炸弹,分别设计了滚转、俯仰、偏航通道的变结构控制律.然后进行了六自由度弹体仿真.仿真结果表明,控制方案能有效地解决卫星制导炸弹通道间的耦合现象,增强了控制系统的适应性与鲁棒性.     

空空导弹大攻角俯仰自动驾驶仪设计

研究导弹自动驾驶仪优化控制问题,针对空空导弹在大攻角飞行过程中,系统的空气动力学特性存在强非线性耦合和参数不确定性,引起系统稳定性差.为了提高系统性能,在导弹俯仰运动的非线性数学模型的基础上,以导弹攻角为被控信号,舵偏角指令为输入信号,提出采用反馈线性化方法对导弹模型进行线性化,然后运用变结构控制理论进行控制器设计.控制器结构简单,易于实现,能够抑制被控对象中存在的不确定性.并通过数学仿真与全状态反馈控制方法设计的控制器进行了比较.结果表明采用反馈线性化和滑模变结构方法设计的控制系统对气动参数摄动和外部扰动具有较强的鲁棒性.     

Disturbance Observer Based Control for Four Wheel Steering Vehicles With Model Reference

This paper presents a disturbance observer based control strategy for four wheel steering systems in order to improve vehicle handling stability. By combination of feedforward control and feedback control, the front and rear wheel steering angles are controlled simultaneously to follow both the desired sideslip angle and the yaw rate of the reference vehicle model. A nonlinear three degree-of-freedom four wheel steering vehicle model containing lateral, yaw and roll motions is built up, which also takes the dynamic effects of crosswind into consideration. The disturbance observer based control method is provided to cope with ignored nonlinear dynamics and to handle exogenous disturbances. Finally, a simulation experiment is carried out, which shows that the proposed four wheel steering vehicle can guarantee handling stability and present strong robustness against external disturbances.      

Multivariable autopilot design for sounding rockets using intelligent Eigenstructure Assignment technique

When a sounding rocket rolls about its longitudinal axis, the role of angle of attack and sideslip angle exchange regularly. This interchange causes the aerodynamic moments to alternate between pitching and yawing moments, which, coupled with the moment of inertia effects, further aggravates the inertial cross-coupling. In this paper, first we analyze the cross-coupling phenomena and derive a Linear, Time-Invariant (LTI), multi input — multi output model of a spinning sounding rocket and then we design an autopilot for this system. An application of multivariable control technique is presented to the design of the autopilot. The involved controller is advanced by combining Eigenstructure Assignment (EA) approach with the Particle Swarm Optimization (PSO) algorithm. Results of linear and nonlinear simulations are reported to demonstrate the performance and stability margin of the considered autopilot.     

Integrated stability control of AFS and DYC for electric vehicle based on non-smooth control

A controller which ensures the driving stability of a four-wheel-independent-drive electric vehicle (4WID-EV) is designed in this paper. The controller is structurally hierarchically designed. In order to keep the 4WID-EV running steadily, an upper-level controller integrating the active front-wheel steering control method (AFS) and direct yaw moment control method (DYC) is designed to keep the sideslip angle and yaw rate tracking the ideal values. A non-smooth control method is used to improve the closed-loop system's convergence and anti-disturbance performance. The additional yaw moment generated by the upper-level controller is distributed to four driving wheels by the lower-level controller. An optimal control algorithm is used in the lower-level controller to achieve the minimum sum of tire utilisation, and ensure the power performance and driving stability of the 4WID-EV. In order to verify the effectiveness of the designed controller, a simulation model of the stability control system is established based on Carsim-Matlab/Simulink. And the simulation is performed under double lane change road considering the disturbances. The results of the simulation show that the 4WID-EV with the designed controller achieves smaller sideslip angle than sliding-mode control and the actuator chatter is slight. Then the stability and safety of the 4WID-EV are greatly improved.     

基于自抗扰技术的高超声速飞行器控制系统设计

高超声速飞行器在飞行过程中超燃冲压发动机对攻角及侧滑角有较严格的要求,为实现对攻角及侧滑角的精确控制,文章采用自抗扰控制技术设计了高超声速飞行器的攻角自动驾驶仪;首先建立高超声速飞行器控制系统的数学模型,然后采用扩张状态观测器对受扰对象的状态和干扰进行观测,并对状态误差采用非线性反馈,对观测的干扰进行补偿,从而实现对干扰的快速抑制和对指令的精确跟踪,最后仿真表明所设计的自动驾驶仪满足性能要求,验证了该方法的正确性。     

防空导弹姿态控制系统终态滑模变结构设计

针对防空导弹垂直发射姿态调转时的快速性要求,研究了快速姿态调转的控制问题.首先基于一类多输入多输出高阶非线性系统的Teminal(终态)滑模变结构控制方法,对垂直发射防空导弹的滚动和俯仰、偏航通道所呈现的非线性、强耦合性进行了分析,并设计了一种新型滑模控制器.控制器设计方案消除了滑模控制的到达阶段,系统的初始状态始终保持在滑模面上,确保了系统的全局鲁棒性和稳定性,且能在有限且可控时间内使跟踪误差趋近于零.最后通过数字仿真验证了系统在不确定因素情况下具有强鲁棒性和适应性,可用于防空导弹短时间姿态调转控制.     

Yaw Moment Control Strategy for Four Wheel Side Driven EV

When four wheel side driven EV travals in steering or changes lanes in high speed, the vehicle is easy to side-slip or flick due to the difference of wheel hub motor and a direct effect of vehicle nonlinear factors on vehicle yaw motion, which would affect vehicle handling and stability seriously. To solve this problem, a joint control strategy, combined with the linear programming algorithm and improved sliding mode algorithm, which combines the exponential reaching law and saturation function was proposed. Firstly, the vehicle dynamics model and the reference model according with the structure and driving characteristics of four wheel side driven EV were set up. Then, introduced the basic method of the improved sliding mode variable structure control and complete the sliding mode variable structure controller design basic on vehicle sideslip angle and yaw velocity.The controller accomplish optimal allocation of vehicle braking force through a linear programming algorithm, according to yaw moment produced by the vehicle motion state. Single lane driving simulation results show that the proposed control strategy can not only control vehicle sideslip angle and yaw velocity well, but also accomplish good controlling of the vehicle yaw moment, so as to significantly improve the handling and stability of vehicle.     

Evaluation of a sliding mode observer for vehicle sideslip angle

This paper presents a sliding mode observer of vehicle sideslip angle, which is the principal variable relating to the transversal forces at the tire/road interface. The vehicle is first modelled, and the model is subsequently simplified. This study validates the observer using both a validated simulator and real experimental data acquired by the Heudiasyc laboratory car, and also shows the limitations of this method. The observer requires a yaw rate sensor and data about vehicle speed are required in order to estimate sideslip angle. Some properties of the nonlinear observability matrix condition number are discussed, and relations between this variable and observation error, vehicle speed and tire cornering stiffness are presented.     

Robust Tracking Control of a Quadrotor Helicopter

In this paper, a robust tracking control method for automatic take-off, trajectory tracking, and landing of a quadrotor helicopter is presented. The designed controller includes two parts: a position controller and an attitude controller. The position controller is designed by the static feedback control method to track the desired trajectory of the altitude and produce the desired angles for pitch and roll angles. By combining the proportional-derivative (PD) control method and the robust compensating technique, the attitude controller is designed to track the desired pitch and roll angles and stabilize the yaw angle. It is proven that the attitude tracking error of each channel can converge to the given neighborhood of the origin ultimately. Experimental results demonstrate the effectiveness of the designed control method.     

Integrated vehicle dynamics management for distributed‐drive electric vehicles with active front steering using adaptive neural approaches against unknown nonlinearity

This paper proposes a new integrated vehicle dynamics management for enhancing the yaw stability and wheel slip regulation of the distributed‐drive electric vehicle with active front steering. To cope with the unknown nonlinear tire dynamics with uncertain disturbances in integrated control problem of vehicle dynamics, a neuro‐adaptive predictive control is therefore proposed for multiobjective coordination of constrained systems with unknown nonlinearity. Unknown nonlinearity with unmodeled dynamics is modeled using a random projection neural network via adaptive machine learning, where a new adaptation law is designed in premise of Lyapunov stability. Given the computational efficiency, a neurodynamic method is extended to solve the constrained programming problem with unknown nonlinearity. To test the performance of the proposed control method, simulations were conducted using a validated vehicle model. Simulation results show that the proposed neuro‐adaptive predictive controller outperforms the classical model predictive controller in tracking nominal wheel slip ratio, desired vehicle yaw rate and sideslip angle, showing its significance in vehicle yaw stability enhancement and wheels slip regulation.     

MIMO conditional integrator control for unmanned airlaunch

A nonlinear MIMO controller based on the conditional integrator technique is designed for the robust stabilization of a new satellite launching strategy called (unmanned) airlaunch. This control technique concerns an integrator performing similar to a sliding mode controller when the system is outside a boundary layer defined by the controller, and performing as a linear controler that provides the integral term when the system enters into the boundary layer. Satellite airlaunch strategy consists in using a two‐stage launching system. The first stage is composed of an airplane (manned or unmanned) that carries a rocket launcher, which constitute the subsequent stages. The control objective is to stabilize the aircraft in the launch phase. It is developed separately for the two nonlinear (one MIMO and one SISO) motion modes of the model, the longitudinal mode and lateral mode, and is then applied to the full model of the aircraft. The considered system is highly nonlinear, mostly as a consequence of a possible large angle of attack, sideslip, and roll angle. Finally, the present work illustrates through simulations, the good performance of the proposed control algorithm. Copyright © 2013 John Wiley & Sons, Ltd.