采用D-K-D迭代算法设计导弹增益调度自动驾驶仪

导弹增益调度自动驾驶仪除具有对时变参数的自适应调节能力外,还应具有对不可测量不确定性的抑制能力.为此,将导弹自动驾驶仪设计问题描述为一类含有不可测量不确定性的线性参数时变(LPV)系统的鲁棒增益调度问题,构造了模型匹配自动驾驶仪设计结构,并通过D-K-D迭代算法综合运用LPV控制方法和μ综合方法设计了导弹鲁棒增益调度自动驾驶仪.设计的自动驾驶仪不仅能够随导弹飞行马赫数和高度的变化自动进行参数调节,还能够有效抑制量测噪声、量测误差及建模误差等不可测量不确定性.仿真结果验证了设计方法的有效性和可行性.     

采用D–K–D迭代算法设计导弹增益调度自动驾驶仪

导弹增益调度自动驾驶仪除具有对时变参数的自适应调节能力外, 还应具有对不可测量不确定性的抑制能力. 为此, 将导弹自动驾驶仪设计问题描述为一类含有不可测量不确定性的线性参数时变(LPV)系统的鲁棒增益调度问题, 构造了模型匹配自动驾驶仪设计结构, 并通过D–K–D迭代算法综合运用LPV控制方法和μ综合方法设计了导弹鲁棒增益调度自动驾驶仪. 设计的自动驾驶仪不仅能够随导弹飞行马赫数和高度的变化自动进行参数调节, 还能够有效抑制量测噪声、量测误差及建模误差等不可测量不确定性. 仿真结果验证了设计方法的有效性和可行性.     

大攻角导弹法向过载控制的变结构设计

通过分析大攻角导弹在飞行过程中出现的问题和滑模变结构理论所具有的优势,本文针对法向过载控制进行优化设计,目的是使其对内在参数变化等因素有较强的适应能力和鲁棒性。基于"过载+角速度+角度"三回路自动驾驶仪,将气动参数的变化等效为动力参数的摄动,设计变结构控制器,重构法向过载微分信号,易于工程实现。通过仿真验证了变结构控制器的性能,结果表明在大攻角飞行条件下,导弹法向过载变结构自动驾驶仪抗模型参数摄动的鲁棒性方面优于传统设计方法。     

战术导弹自动驾驶仪变结构控制设计与仿真

为了使战术导弹自动驾驶仪对导弹的内在参数变化等因素有较强的适应能力和鲁棒性片保证系统能够达到期望的性能指标要求,根据变结构理论对其进行了重新设计.先把战术导弹的典型自动驾驶仪回路简化为二阶线性变参数模型,并根据一条弹道上的导弹自动驾驶仪参数计算出其参数的变化范围.经严格推导了系统存在滑动模态的充分条件下设计了滑模变结构控制器对其进行控制.结论是,变结构控制方法对导弹内在参数大范围剧烈变化和外在环境扰动等因素具有较强的适应能力和鲁棒性.通过数字仿真验证了所设计的滑模变结构控制方法的正确性和有效性.     

基于准线性化模型设计导弹H∞增益调度自动驾驶仪

实现针对系统快变量攻角的自适应参数调节是导弹鲁棒增益调度自动驾驶仪设计的一个难点. 为解决此问题, 提出采用由状态替换方法建立的导弹准线性化模型作为设计模型, 基于线性参数时变(LPV)/μ控制技术构造自动驾驶仪设计结构, 并通过D-K-D迭代算法设计导弹H_∞增益调度自动驾驶仪. 所设计的自动驾驶仪不仅能够实现对马赫数和高度两个系统慢变量的自适应参数调节, 还能实现对系统快变量攻角的自适应参数调节. 非线性仿真结果验证了所提出方法的有效性.     

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.     

考虑自动驾驶仪动态特性的三维双环制导律

针对导弹自动驾驶仪动态特性条件下的机动目标拦截问题,基于非线性干扰观测器和命令滤波器设计一种新的三维双环制导律.将制导系统解耦为外环系统和内环系统.其中:外环控制器产生虚拟制导指令,以零化球坐标系下的弹目法向相对速率;内环控制器产生真实制导指令,以实现导弹自动驾驶仪对外环虚拟指令的快速跟踪.由于外环命令滤波器同时计算出虚拟制导指令的一阶导数和二阶导数,三阶系统的制导律设计问题仅用两步即可完成.拦截高速高机动目标的仿真结果表明,所设计的制导律能够有效补偿导弹自动驾驶仪动态特性影响,抗目标机动鲁棒性强,制导精度优良.     

基于模糊-PID的智能飞控技术研究

由于无人机在飞行过程中机体参数变化剧烈,针对某型无人机,通过对无人机运动学模型进行分析,以无人机纵向运动模型为验证平台,论证了模糊PID技术应用于无人机自动驾驶仪设计的可行性。将传统的PID控制与模糊控制相结合,通过PID控制实现控制的准确性,利用模糊控制提高控制的快速性。针对无人机飞行控制中的实际问题,着重提出了PID控制器和基于误差分区的模糊控制器的设计方法。实验证明该方法不仅增强了控制器的调节能力,还在一定程度上简化了控制器的设计。     

飞航导弹自动驾驶仪系统控制方案研究

为了克服飞航导弹运动过程中的非线性、时变性和不确定性对自动驾驶仪系统性能的不良影响,进一步提高导弹的飞行质量,对自动驾驶仪系统及其采用的控制方案进行了研究;首先对系统的整体结构进行了分析,然后在介绍经典PID方案的基础上,分别采用模糊自调整PID方案和神经网络自适应PID方案设计了导弹姿态运动控制器,最后进行了仿真实验;仿真结果的对比展示了所设计控制器良好的品质,验证了将模糊控制和神经网络应用于飞航导弹自动控制中的可行性和有效性,为其它非线性控制理论与导弹传统控制相结合以进一步提高导弹控制系统的性能奠定了基础。     

BTT导弹H∞鲁棒自动驾驶仪的6DOF数学仿真

该文Ｈ∞对控制方法设计的ＢＴＴ导弹自动驾驶仪进行六自由度（６ＤＯＦ）数学仿真，与传统的逐段切换自动驾驶仪增益以控制导弹沿全弹道飞行方法相比，本仿真仅用对标准弹道上上某特征设计的一个Ｈ∞鲁棒自动驾驶仪控制导弹的全弹道飞行，仿真结果表明，设计的Ｈ∞鲁棒自动驾驶仪控制导弹在大域内稳定，准确地飞行，在满足一定的性能指标要求的前提下系统有很强的鲁棒稳定性。     

磁悬浮储能飞轮线性变参数鲁棒增益调度控制

针对强陀螺效应的磁悬浮储能飞轮转速快变引起的模型变化而带来的控制问题,设计了线性变参数增益调度鲁棒控制器.根据飞轮的线性变参数模型,设计的鲁棒增益调度控制器,能够保证其全转速范围内的鲁棒稳定性和性能.为降低控制器设计的保守性,在设计控制器时,可缩小转速区间,使控制性能得到提高.与按照非时变模型设计的鲁棒控制器相比,线性变参数鲁棒增益调度控制器可以实现以转速为参数的自适应调节,在全转速范围内,其鲁棒稳定性和性能均具有显著优势.仿真结果验证了此控制器的有效性和先进性.     

Controller reduction for linear parameter-varying systems with a priori bounds

In this paper we develop a controller reduction procedure for linear parameter-varying (LPV) systems. The method uses synthesis Riccati inequalities for the normalized robust stabilization problem as a basis for the approximation. The technique provides a priori error bounds which are used to obtain closed-loop stability conditions and performance degradation level. We also generalize the relative model reduction method to LPV systems and give an energy interpretation to the controller reduction procedure. To illustrate the method, a reduced order controller is synthesized and tested on a nonlinear missile model.     

Systematic Gain‐Scheduling Control Design: A Missile Autopilot Example

The missile autopilot was designed using linear parameter‐varying (LPV) control techniques. The controller provides exponential stability guarantee and performance bound in terms of induced L₂ norm for the missile plant. The systematic gain‐scheduling approach is motivated by the recent development in LPV control theory and provides a well founded and systematic procedure for high performance missile autopilot design problem.     

多项式理论在导弹稳定性能评估中的应用

针对线性参数不确定性系统的鲁棒稳定性问题,提出一种新的分析方法,并对其在导弹自动驾驶仪鲁棒稳定性评估中的可行性进行了研究。首先给出线性参数不确定性系统在其特征多项式系数不相关情况下的鲁棒稳定性的充要条件,并通过自适应网格划分算法将此条件与鲁棒D-稳定性理论结合,得到基于多项式理论的评估算法。将算法用于导弹自动驾驶仪鲁棒稳定性评估,得到了不同攻角下导弹在全包线范围内的稳定区域。和只能在离散点进行评估的传统评估方法比较,结果表明提出的算法可以在全包线范围内连续进行评估,从而发现一些隐蔽的不稳定区域。     

Missile autopilot design via a multi‐channel LFT/LPV control method

In this paper, the missile pitch‐axis autopilot design is revisited using a new and recently available linear parameter‐varying (LPV) control technique. The missile plant model is characterized by a linear fractional transformation (LFT) representation. The synthesis task is conducted by exploiting new capabilities of the LPV method: firstly, a set of H₂/H_∞ criteria defined channel‐wise is considered; secondly, different Lyapunov and scaling variables are used for each channel/specification which is known to reduce conserva tism; and finally, the controller gain‐scheduling function is constructed as affine matrix‐valued function in the polytopic co‐ordinates of the scheduled parameter. All these features are examined and evaluated in turn for the missile control problem. The method is shown to provide additional flexibility to tradeoff conflicting and demanding performance and robustness specifications for the missile while preserving the practical advantage of previous single‐objective LPV methods. Finally, the method is shown to perform very satisfactorily for the missile autopilot design over a wide range of operating conditions. Copyright © 2001 John Wiley & Sons, Ltd.     

Anti-windup controller design using linear parameter-varying control methods

In this paper, we seek to provide a systematic anti-windup control synthesis approach for systems with actuator saturation within a linear parameter-varying (LPV) design framework. The closed-loop induced L2 gain control problem is considered. Different from conventional two-step anti-windup design approaches, the proposed scheme directly utilizes saturation indicator parameters to schedule accordingly the parameter-varying controller. Hence, the synthesis conditions are formulated in terms of linear matrix inequalities (LMIs) that can be solved very efficiently. The resulting gain-scheduled controller is non-linear in general and would lead to graceful performance degradation in the presence of actuator saturation non-linearities and linear performance recovery. An aircraft longitudinal dynamics control problem with two input saturation non-linearities is used to demonstrate the effectiveness of the proposed LPV anti-windup scheme.     

A design of gain-scheduled control for a linear parameter varying system: an application to flight control

For multi-input–multi-output, multi-parameter, nonlinearly parameter-dependent linear parameter-varying systems, a gain-scheduled control design method using both minimum sensitivity eigenvalue assignment and quadratic stability check is proposed. The designed controller guarantees the stability of the closed-loop system and assigns the eigenvalues of the frozen parameter closed-loop LPV system in the prespecified disjointed regions. Fewer controllers than that of any other method are needed to cover the whole parameter space. The proposed design method is applied to the design of a flight vehicle's back-to-turn (BTT) controller and nonlinear six-degree-of-freedom (6-DOF) simulations are performed to show its usefulness as a gain-scheduled controller design method.     

Fuzzy multi-objective design for a lateral missile autopilot

Gain scheduled control is one very useful control technique for linear parameter-varying (LPV) and nonlinear systems. A disadvantage of gain-scheduled control is that it is not easy to design a controller that guarantees the global stability of the closed-loop system over the entire operating range from the theoretical point of view. Another disadvantage is that the interpolation increases in complexity as number of scheduling parameters increases. As an improvement, this paper presents a gain-scheduling control technique, in which fuzzy logic is used to construct a model representing a quasi-LPV or a nonlinear missile and to perform a control law. The fuzzy inference system is generated using a multi-objective evolutionary algorithm to optimize the performance characteristics of the plant.     

Probabilistic Robust Linear Parameter-varying Control of a Small Helicopter Using Iterative Scenario Approach

In this paper, we present an iterative scenario approach (ISA) to design robust controllers for complex linear parameter-varying (LPV) systems with uncertainties. The robust controller synthesis problem is transformed to a scenario design problem, with the scenarios generated by identically extracting random samples on both uncertainty parameters and scheduling parameters. An iterative scheme based on the maximum volume ellipsoid cutting-plane method is used to solve the problem. Heuristic logic based on relevance ratio ranking is used to prune the redundant constraints, and thus, to improve the numerical stability of the algorithm. And further, a batching technique is presented to remarkably enhance the computational efficiency. The proposed method is applied to design an output-feedback controller for a small helicopter. Multiple uncertain physical parameters are considered, and simulation studies show that the closed-loop performance is quite good in both aspects of model tracking and dynamic decoupling. For robust LPV control problems, the proposed method is more computationally efficient than the popular stochastic ellipsoid methods.