飞机俯仰运动自抗扰控制器设计

提出了利用自抗扰控制器在大包线范围内设计飞机俯仰运动控制器的新方法．利用二阶自抗扰控制器补偿系统模型扰动和外扰，实现了纵向运动俯仰角变量的跟踪控制．自抗扰控制器直接依据飞机的非线性模型，符合飞机动力学模型摄动大的特点，在很大的包线范围内不需要改变控制器的结构和参数，简化了飞行控制律的设计过程．大包线范围内的仿真结果表明，系统具有良好的动态和稳态性能，控制器具有很强的鲁棒性，为解决大包线范围内的飞行控制问题提供了一种有效的新途径．     

控制面故障下的飞机运动建模与重构控制能力分析及设计

对控制面故障影响飞机运动的机理进行了推导,系统地阐述了控制面故障下的飞机运动建模方法。在建模的基础上,对故障系统的可重构性进行研究。分别从线性系统运动和物理运动两个方面,给出了可重构能力的评定方案。推导了误差反向传播的前向神经网络用于控制系统设计时满足Lyapunov稳定性的学习算法,提出了一种新型的采用反向传播神经网络补偿常规控制器的重构飞行控制设计方案。采用非线性飞机运动模型对控制器进行了仿真,验证了重构飞行控制器的性能。     

超机动飞机的动态建模与控制律设计及仿真

建立了带推力矢量的超机动飞机非线性动态模型,重点分析了气动力、气动力矩以及发动机的建模过程.采用基于神经网络的自适应逆方法,设计了超机动飞机大迎角机动下的控制律.首先应用动态逆方法,分别设计了快慢回路的飞行控制律;然后利用BP神经网络,在线补偿飞机模型不确定性以及外界干扰.眼镜蛇机动的仿真结果表明,所设计的控制律在大迎角机动条件下具有良好的控制性能,能够保证闭环系统的稳定性.     

电传飞机飞行品质低阶等效系统算法研究

研究了从飞行试验数据辨识电传飞机动力学模型的低阶等效系统参数的方法。采用频域相干性分析和高精度有限傅立叶变换对试验数据进行了精确的频谱分析。频域方程误差法、输出误差法和单纯形法相结合,为计算电传飞机的低阶等效系统提供了一个实用有效的算法,并使用某型电传飞机试验数据进行了可靠性和有效性验证。结果表明：使用本文的方法辨识的低阶等效系统模型能够准确地描述真实电传飞机的动力学特性。本文的研究内容为电传飞机飞行品质试验方法提供了技术支持。     

Structural load alleviation using distributed delay shaper: Application to flexible aircraft

Lightweight flexible aircraft suffers from unwanted oscillatory vibrations during aircraft manoeuvres. A recently developed distributed-delay signal (DZV) shaper is therefore proposed to be applied as a feedforward controller to alleviate the manoeuvre loads, as an alternative to traditional structural filters used routinely in this context. Structural filters are essentially linear low-pass filters with bandwidth below the significant flexible modes, applied to control signals generated either by the pilot’s direct input or by the flight control system. It has been showed that if instead a properly tuned signal shaper is used, better performance can be achieved: first, the target modes are significantly attenuated while the responsiveness of the aircraft is less compromised and secondly, the oscillatory nature of the vibrations are reduced. The high fidelity simulation results on a full scaled dynamic model of a highly flexible blended wing–body (BWB) aircraft show that in comparison to traditional structural filters, signal shapers significantly reduce the wing root loading (forces and moments) which provides potential structural benefits.     

Direct adaptive neural flight control system for an unstable unmanned aircraft

A direct adaptive controller design using neural network is proposed for an unstable unmanned research aircraft similar in configuration to combat aircraft. The control law to track the pitch rate command is developed based on system theory. Neural network with linear filters and back propagation through time learning algorithm is used to approximate the control law. The bounded signal requirement to develop the neural controller is circumvented using an off-line finite time training scheme, which provides the necessary stability and tracking performances. On-line learning scheme is implemented to compensate for uncertainties due to variation in aerodynamic coefficients, control surface failures and also variations in center of gravity position. The performance of the proposed control scheme is validated at different flight conditions. The disturbance rejection capability of the neural controller is analyzed in the presence of the realistic gust and sensor noises. Hardware-in-loop simulation is also carried out to study the behavior of control surface deflections in real-time.     

Conflict resolution for air traffic management: a study inmultiagent hybrid systems

Air traffic management (ATM) of the future allows for the possibility of free flight, in which aircraft choose their own optimal routes, altitudes, and velocities. The safe resolution of trajectory conflicts between aircraft is necessary to the success of such a distributed control system. In this paper, we present a method to synthesize provably safe conflict resolution manoeuvres. The method models the aircraft and the manoeuvre as a hybrid control system and calculates the maximal set of safe initial conditions for each aircraft so that separation is assured in the presence of uncertainties in the actions of the other aircraft. Examples of manoeuvres using both speed and heading changes are worked out in detail     

Robust flight control system design using H∞ loop-shaping and recessive trait crossover genetic algorithm

A proposed approach to robust controller design is introduced. This approach combines the recessive trait crossover genetic algorithm with the loop-shaping design procedure using H_∞ synthesis. The requirements, design and simulation of a flight control system for precision tracking task are considered. The proposed method is applied to design a control system for the F-16 fighter aircraft model. The flight simulations reveal that the desired performance objectives are achieved and that the controller provides acceptable performance in spite of modeling errors and plant parameter variations.     

基于功能模型的飞控系统安全性设计技术研究

为了确保飞控系统的安全可靠,提出一种基于功能模型的飞控系统安全性设计方法.首先,以需求为牵引,结合飞机的使用场景和性能,实现飞控系统的功能设计;然后,基于安全性设计理念,从系统功能的失效出发实现系统架构的余度设计,同时针对传统方法仅关注系统本身的故障组合分析,存在局限性、滞后性等问题,提出了基于网络化方法开展飞控系统故障推演的功能模型方法;最后,通过应用结果表明了本文所提方法的有效性和可行性.     

自抗扰控制器在超机动飞行快回路控制中的应用

提出了一种利用自抗扰控制器算法设计超机动飞行快回路控制律的新方法．根据自抗扰控制器能够动态补偿系统模型扰动和外扰的特性,在超机动飞行的快回路中引入自抗扰控制器。实现了快变量的动态解耦控制．控制律设计直接依据超机动飞行的强耦合、强非线性模型。在较大的包线范围内不需要改变控制器参数．简化了设计过程．仿真结果表明,系统具有良好的动态和稳态性能,控制器具有很强的鲁棒性．     

Flight envelope protection of aircraft using adaptive neural network and online linearisation

Flight envelope protection algorithm is proposed to improve the safety of an aircraft. Flight envelope protection systems find the control inputs to prevent an aircraft from exceeding structure/aerodynamic limits and maximum control surface deflections. The future values of state variables are predicted using the current states and control inputs based on linearised aircraft model. To apply the envelope protection algorithm for the wide envelope of the aircraft, online linearisation is adopted. Finally, the flight envelope protection system is designed using adaptive neural network and least-squares method. Numerical simulations are conducted to verify the performance of the proposed scheme.     

Mining the fuzzy control rules of aeration in a Submerged Biofilm Wastewater Treatment Process

This paper presents a special rule base extraction analysis for optimal design of an integrated neural-fuzzy process controller using an “impact assessment approach.” It sheds light on how to avoid some unreasonable fuzzy control rules by screening inappropriate fuzzy operators and reducing over fitting issues simultaneously when tuning parameter values for these prescribed fuzzy control rules. To mitigate the design efforts, the self-learning ability embedded in the neural networks model was emphasized for improving the rule extraction performance. An aeration unit in an Aerated Submerged Biofilm Wastewater Treatment Process (ASBWTP) was picked up to support the derivation of a solid fuzzy control rule base. Four different fuzzy operators were compared against one other in terms of their actual performance of automated knowledge acquisition in the system based on a partial or full rule base prescribed. Research findings suggest that using bounded difference fuzzy operator (O_b) in connection with back propagation neural networks (BPN) algorithm would be the best choice to build up this feedforward fuzzy controller design.     

Design of robust redundancy relations for a semi-scale YF-22 aircraft model

This paper presents an “ad hoc” methodology for the design of diagnostic software for the detection and isolation of faults on sensors and actuators of a remotely controlled semi scale YF-22 research aircraft. Starting from the structural analysis of the nonlinear dynamic equations of the aircraft, an algorithm, based on the “variables elimination method”, is proposed to compute a set of residual equations having all the possible fault signatures. The quality of each residual equation has been ranked according to a cost function chosen to represent implementation issues such as the sensitivity to measurement noise in the numerical computation of high order derivatives. An algorithm is then proposed for selecting a subset of residual equations with maximum “failure isolability” and minimum cost, according to the selected performance criteria. The issue of robustification of the residual equations to modeling errors and measurement noise has been addressed through nonlinear uncertainty mapping using Neural Networks in conjunction to FIR filters. The fault detection and isolation method has been applied by injecting simulated faults to flight data collected by a semi-scale YF-22 research aircraft model.     

Self-guiding of a high velocity pilotless aircraft on the terminal flight leg in atmosphere

An algorithm for self-guiding of a high velocity aircraft with high aerodynamic quality on the terminal flight leg in the atmosphere is proposed. This algorithm provides guiding to a given spatial domain with required high accuracy and the conditions of approaching this domain in the case of uncertain aerodynamic characteristics of the aircraft and the action of a wide spectrum of uncontrollable factors of different physical nature. The algorithm consists in the formation of an updated incident trajectory using the data of a multispectral observation system. The results of simulation of the process of terminal guiding of a high velocity aircraft using the proposed algorithm in different conditions are presented; these results prove the possibility of achieving high terminal accuracy and weak sensitivity of the algorithm to the action of uncontrollable factors.     

结冰飞机的包线保护与控制裕度研究

飞机结冰具有不确定性和随机性,会破坏飞机的动力学特性,威胁飞行安全.针对这一问题,对结冰飞机的安全边界保护和控制裕度计算展开探究.首先,应用可达集方法,将结冰的作用看作不确定性对抗输入,分析结冰对飞机安全包线边界的影响;然后,基于已知的结冰飞机飞行安全包线,提出两种包线边界保护方法,第1种是改进的最优控制边界保护方法,通过引入新型的最优控制保护动作的切换策略消除传统最优控制保护方法的控制量抖振现象,第2种是保留驾驶员操作权限的安全边界保护方法,通过计算安全边界上的可用控制指引驾驶员完成正确的操作,使得飞机飞行状态不超出安全包线;最后,通过实时计算飞机当前状态点的控制裕度对飞机超出包线进行提前预防,指引驾驶员完成安全程度较高的操作,并提出一种新型的控制裕度迭代计算策略,能够有效降低控制裕度计算的保守性.     

Design of nonlinear automatic flight control systems

A method for the synthesis of nonlinear automatic flight control systems is developed, and the performance of a control system synthesized by use of this method is compared to the performance of control system designed by use of linear quadratic optimal control theory. Comparisons are made on the basis of aircraft dynamic response at high angles of attack. It is found that the nonlinear controller reduces the altitude loss during stall and increases the magnitude of the angle of attack for which the aircraft can recover from stall.     

基于直接自适应控制的重构飞控系统研究

通常，飞控系统重构设计需知系统的故障信息，而使用直接自适应控制技术可在不知道系统故障信息的情况下，对飞控系统操纵面损伤进行重构，并且可使故障飞机很好地跟踪参考模型的输出．采用优化算法设计反馈补偿器以保证故障系统的严格正实性，并利用Lyapunov函数证明重构系统的渐近稳定性．将该方法用于某型飞机侧向控制系统的设计，仿真结果表明，在操纵面严重受损的情况下，飞机仍能保持良好的性能．     

Aerodynamic Effects Compensation on Multi-Rotor UAVs Based on a Neural Network Control Allocation Approach

This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural networks. Thus, the system performance can be improved by replacing the classic allocation matrix, without using the aerodynamic inflow equations directly. The network training is performed offline, which requires low computational power. The target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation algorithm. Such a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work, because of its small size. We compared the mechanical torques commanded by the flight controller, i.e., the control input, to those actually generated by the actuators and established at the aircraft. It was observed that the proposed neural network was able to closely match them, while the classic allocation matrix could not achieve that. The allocation error was also determined in both cases. Furthermore, the closed-loop performance also improved with the use of the proposed neural network control allocation, as well as the quality of the thrust and torque signals, in which we perceived a much less noisy behavior.      

一种飞机的航迹模拟仿真算法

飞行仿真中,飞机航迹模拟没有考虑飞机是匀速还是变速,一般由简单的直线和圆组合来表示,这种表示算法较为理想化或简单化。为了建立逼真空情,实现复杂多样的飞行动作模拟,本文对飞机运动的数学模型进行研究,归纳总结飞机直线飞行算法,针对飞机转弯航迹过于理想和简单化提出一种新的模拟算法来模拟飞机转弯航迹。将飞机匀速和变速转弯用一种算法实现,增加新的转弯方式并提高飞机航迹多样性。最后将新算法替代老算法在航管模拟训练系统中进行应用与仿真,与真实飞机航迹数据对比,证实新的算法可以模拟出变速转弯航迹,并使整体航迹更加接近真实。     

Supervisory adaptive dynamic RBF-based neural-fuzzy control system design for unknown nonlinear systems

Many published papers show that a TSK-type fuzzy system provides more powerful representation than a Mamdani-type fuzzy system. Radial basis function (RBF) network has a similar feature to the fuzzy system. As this result, this article proposes a dynamic TSK-type RBF-based neural-fuzzy (DTRN) system, in which the learning algorithm not only online generates and prunes the fuzzy rules but also online adjusts the parameters. Then, a supervisory adaptive dynamic RBF-based neural-fuzzy control (SADRNC) system which is composed of a DTRN controller and a supervisory compensator is proposed. The DTRN controller is designed to online estimate an ideal controller based on the gradient descent method, and the supervisory compensator is designed to eliminate the effect of the approximation error introduced by the DTRN controller upon the system stability in the Lyapunov sense. Finally, the proposed SADRNC system is applied to control a chaotic system and an inverted pendulum to illustrate its effectiveness. The stability of the proposed SADRNC scheme is proved analytically and its effectiveness has been shown through some simulations.