Adaptive control based on a parametric affine model for tail-controlled missiles

An adaptive control against uncertainties in tail-controlled STT (skid-to-turn) missiles is presented. First, we derive an analytic uncertainty model from a parametric affine missile model developed by the authors. Based on this analytic model, an adaptive feedback linearizing control law accompanied by a sliding mode control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme are demonstrated by simulation.     

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。     

基于自适应反演的导弹滑模控制

阐述了在导弹系统存在不确定性情况下,基于自适应反演控制技术和模糊神经网络理论,提出了一种导弹滑模控制系统设计方法。设计过程中将不确定性对系统的影响合成为一项,然后应用模糊神经逼近器来逼近系统的不确定项;考虑了已知信息,利用自适应模糊神经控制理论和滑模控制设计了控制器,应用Lypunov稳定性理论保证了闭环系统的稳定性,并推导出模糊神经逼近器各参数的自适应调节律。     

基于自适应滑模与模糊控制的导弹直接力/气动力复合控制系统优化设计

 针对导弹直接力/气动力复合控制问题,提出了一种基于自适应滑模控制(ASMC)与模糊逻辑的自动驾驶仪设计方法。该方法将整个导弹控制系统分为气动力控制子系统(ACS)和直接力控制子系统(RCS)两部分。前者采用自适应滑模控制理论进行设计,利用其所具有的强鲁棒性优点,克服了包括参数摄动与外界扰动在内的各类不确定性因素的影响。后者通过基于规则的模糊推理来确定不同条件下直接力作用的大小,以辅助提高气动力子系统的性能。在控制系统结构确定的条件下,利用遗传算法(GA)对各参数进行优化,实现了两个子系统之间的协调工作。仿真结果表明,所提出的控制方案对机动指令具有较好的跟踪效果,适用于直接力/气动力复合控制导弹的控制系统设计。     

基于鲁棒变结构控制方法的非线性导弹自动驾驶仪设计

对一类非线性不确定导弹控制系统,采用自适应方法进行了基于滑模理论的变结构控制器设计。该方案使得采用反演手段产生的微分爆炸问题得到较好的回避,同时构造自适应律,消除了不确定性对系统的影响,最后通过构造Lyapunov函数方法,确保了系统的鲁棒稳定性。文末仿真结果表明了该方案的有效性。     

带有广义不确定性的导弹非线性控制系统设计

 在导弹系统存在广义不确定性情况下,提出了一种基于反演设计技术和RBF神经网络的导弹非线性自适应控制系统设计方法。设计过程中将不确定性对系统的影响合成为一项,然后应用RBF神经网络消除了其对系统的影响,有效地解决了控制系数矩阵未知时控制器设计问题,同时放松了现有文献中对控制系数矩阵不确定性的要求。应用Lypunov稳定性定理推导出神经网络权重矩阵的自适应调节律,并证明了闭环系统的所有信号均有界且指数收敛至系统原点的一个邻域。最后给出的BTT导弹非线性六自由度数字仿真结果验证了该算法的有效性。     

基于RBF神经网络的机器人鲁棒自适应控制器设计

在考虑机器人系统中存在的模型不确定性的情况下,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,通过状态变换将机器人的模型转换为适用于反演技术的形式;然后,利用反演技术设计了鲁棒自适应控制器,用两个RBF神经网络分别对模型的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律以及相关的鲁棒项,证明了系统的全局稳定性;最后,进行了相应的仿真研究,验证了设计的正确性和有效性。     

战术导弹气动伺服弹性滑模控制技术

为抑制弹体弹性振动引起的控制系统品质恶化,建立了高精度弹性动态模型,采用模态自适应结构滤波技术,在极点配置优化控制参数的基础上,设计了滑模变结构策略,对局部增益进行自适应切换,实现了弹性导弹全包线鲁棒稳定。通过开发弹性弹体非线性集成仿真系统,为导弹气动伺服弹性振荡及失稳现象提供了数字仿真预测与复现手段,以全面验证飞行控制系统的综合性能。高空弹道试验与数字仿真结果表明,开发的非线性仿真系统可信度较高,滑模变结构策略设计合理,控制系统鲁棒性较强,能够抑制包括弹性振动在内的多种不确定性影响。     

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.     

Nonlinear Adaptive Robust Force Control of Hydraulic Load Simulator

This paper deals with the high performance force control of hydraulic load simulator. Many previous works for hydraulic force control are based on their linearization equations, but hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative control not yield to high-performance requirements. In this paper, a nonlinear system model is derived and linear parameterization is made for adaptive control. Then a discontinuous projection-based nonlinear adaptive robust force controller is developed for hydraulic load simulator. The proposed controller constructs an asymptotically stable adaptive controller and adaptation laws, which can compensate for the system nonlinearities and uncertain parameters. Meanwhile a well-designed robust controller is also developed to cope with the hydraulic system uncertain nonlinearities. The controller achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities; in the absence of uncertain nonlinearities, the scheme also achieves asymptotic tracking performance. Simulation and experiment comparative results are obtained to verify the high-performance nature of the proposed control strategy and the tracking accuracy is greatly improved.     

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。     

Decentralized attitude synchronization tracking control for multiple spacecraft under directed communication topology

This paper studies the attitude synchronization tracking control of spacecraft formation flying with a directed communication topology and presents three different controllers. By introducing a novel error variable associated with rotation matrix, a decentralized attitude synchronization controller, which could obtain almost global asymptotical stability of the closed-loop system, is developed. Then, considering model uncertainties and unknown external disturbances, we propose a robust adaptive attitude synchronization controller by designing adaptive laws to estimate the unknown parameters. After that, the third controller is proposed by extending this method to the case of time-varying communication delays via Lyapunov–Krasovskii analysis. The distinctive feature of this work is to address attitude coordinated control with model uncertainties, unknown disturbances and time-varying delays in a decentralized framework, with a strongly connected directed information flow. It is shown that tracking and synchronization of an arbitrary desired attitude can be achieved when the stability condition is satisfied. Simulation results are provided to demonstrate the effectiveness of the proposed control schemes.     

导弹纵向机动飞行的非线性鲁棒控制研究

将非线性无源方法用于导弹纵向机动飞行控制，并通过变结构控制器补偿系统的不确定性，这样设计的控制器能保证系统的鲁棒稳定性。将此方法用于导弹地形跟踪控制，仿真结果表明：此方法在导弹纵向机动飞行中控制效果较好。     

广义预测自适应控制器在导弹控制系统设计中应用

将一种新的广义预测自适应控制算法应用于快速时变的导弹控制系统设计中。讨论了设计参数对控制系统性能的影响;针对自适应控制信号过大,提出了改进方案,增强了系统的鲁棒性和抗干扰能力。大量的数字仿真结果表明:运用该方案设计的导弹控制系统具有很好的跟踪性能和强的抗干扰能力;对系统阶次、参数、时延和采样周期的变化具有很强的鲁棒性;自适应算法中,对验前知识要求少,实现起来也比较简单。     

Robust guidance for electro-optical missiles

A robust guidance law is presented which renders zero miss distance (ZMD) against deterministically or randomly maneuvering targets for all missile parametric uncertainties. Since the resulting guidance controller is a phase-lead network, it is mainly suitable for systems characterized by moderate glint levels such as electro-optical missiles. The structured uncertainties in missile dynamics are modeled by interval transfer functions. It is first shown that for the nominal case, when the total missile transfer function is positive real, ZMD can be obtained. When uncertainties are considered, the problem becomes design of a guidance controller which renders a family of transfer functions positive real. A new algorithm for the design of such controllers is proposed. An example illustrating a typical design procedure for a nonlinear real-life missile model is given, showing the simplicity and effectiveness of the proposed robust guidance. The main conclusion of this work is that the newly developed guidance law performs well against highly maneuvering targets and may be a suitable alternative to optimal guidance laws in low-glint systems.     

应用动态逆和时间尺度分离的BTT导弹控制

基于简化的ＢＴＴ导弹控制设计模型,应用非线性动态和时间尺度分离方法设计了一种非线性ＢＴＴ导弹自动驾驶仪,根据导弹实际的飞行高度和飞行速度,可以计算出导弹动力学系数的标称值,非线性动态逆法正是基于这些动力学系数的标移值,适适合于控制导弹作大空域飞行,六自由度仿真结果一步验证了方法是正确的与有效的。     

Backstepping design of missile guidance and control based on adaptive fuzzy sliding mode control

This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of the system, and for the uncertainties, we utilize an online-adaptive control law to estimate the unknown parameters. The stability analysis of the closed-loop system is also conducted. Simulation results show that, with the application of the adaptive fuzzy sliding mode control, small miss distances and smooth missile trajectories are achieved, and the system is robust against system uncertainties and external disturbances.     

Roll-pitch-yaw autopilot design for nonlinear time-varying missile using partial state observer based global fast terminal sliding mode control

The acceleration autopilot design for skid-to-turn (STT) missile faces a great challenge owing to coupling effect among planes, variation of missile velocity and its parameters, inexistence of a complete state vector, and nonlinear aerodynamics. Moreover, the autopilot should be designed for the entire flight envelope where fast variations exist. In this paper, a design of inte-grated roll-pitch-yaw autopilot based on global fast terminal sliding mode control (GFTSMC) with a partial state nonlinear observer (PSNLO) for STT nonlinear time-varying missile model, is employed to address these issues. GFTSMC with a novel sliding surface is proposed to nullify the integral error and the singularity problem without application of the sign function. The pro-posed autopilot consisting of two-loop structure, controls STT maneuver and stabilizes the rolling with a PSNLO in order to estimate the immeasurable states as an output while its inputs are missile measurable states and control signals. The missile model considers the velocity variation, gravity effect and parameters’ variation. Furthermore, the environmental conditions’ dynamics are mod-eled. PSNLO stability and the closed loop system stability are studied. Finally, numerical simula-tion is established to evaluate the proposed autopilot performance and to compare it with existing approaches in the literature.     

Missile autopilot design via functional inversion and time-scaled transformation

This paper presents a new approach to acceleration control of STT (Skid-To-Turn) missiles. In the design and stability analysis of our autopilot, we assume perfect roll-stabilization but consider fully all other nonlinearities of the missile dynamics including the coupling effect due to bank angle. Our autopilot controller consists of a partial-linearizing controller and a dynamic compensator. The partial-linearizing controller along with a time scaled transformation can convert the nonlinear missile dynamics to the so-called normalized system which is completely independent of Mach number and almost independent of air density. The dynamic compensator is designed based on this normalized system. This normalized system greatly simplifies the design process of an autopilot controller regardless of flight conditions. Our autopilot controller can provide fast and exact set-point tracking performance but without the slow-varying conditions on angle of attack and side-slip angle required often in the prior works.     

基于RBF神经网络的一类非线性系统反演鲁棒自适应控制

提出一种基于RBF神经网络的一类非线性系统反演鲁棒自适应控制器设计方法。使用RBF神经网络逼近系统不确定性,并和控制器与虚拟控制器中的鲁棒项一起消除不确定性的影响,由Lyapunov稳定性理论推出的RBF神经网络权值矩阵的自适应律能保证闭环系统的所有信号有界,且误差能够全局指数收敛于原点的邻域。该方法不需要系统不确定性的上界以及其任意阶导数,最后的仿真结果验证了方法的有效性。