1、毕 业 设 计（论 文）外 文 参 考 资 料 及 译 文译文题目： 控制工程实践 学生姓名： 学 号： 专 业： 所在学院： 指导教师： 职 称： 20xx年 2月 27日Control Engineering Practice1.Abstract Due to the inherent instabilities and nonlinearities of rotorcraft dynamics, its changing properties during flight and the engineering difficulties to predict its aerodynamic
2、s with high levels of fidelity, helicopter flight control requires the application of special strategies. These strategies must allow to cope with the nonlinearities of the system and assure robustness in the presence of inaccuracies and changes in configuration.In this paper, a novel approach based
3、 on an Incremental Nonlinear Dynamic Inversion is applied to simplify the design of helicopter flight controllers. With this strategy, by employing the feedback of acceleration measurements to avoid the need for information relative to any aerodynamic change, the control system does not need any mod
4、el data that depends exclusively on its states, thus enhancing its robustness to model uncertainties.The overall control system is tested by simulating two tasks with distinct agility levels as described in the ADS-33 helicopter handling qualities standard. The analysis shows that the controller pro
5、vides an efficient tracking of the commanded references. Furthermore, with the robustness properties verified within the range of inaccuracies expected to be found in reality, this novel method seems to be eligible for a potential practical implementation to helicopter vehicles.Keywords:Helicopter F
6、light control Nonlinear control Incremental Nonlinear Dynamic Inversion Pseudo-Control Hedging2.Introduction Helicopters are generally reliable flying machines, capable of fulfilling missions impossible with fixed-wing aircraft, most notably rescue operations. These missions, however, often lead to
7、highand sometimes excessive pilot workload. The excessive pilot workload for helicopters indicates that, even modern helicopters, often have poor Handling Qualities (HQs) (Padfield, 1998). This ismainly due to the fact that helicopters are highly nonlinear and complex dynamic systems, inherently uns
8、table by nature, with strong coupled inter-axis behavior which makes piloting a very demanding job. Therefore, to assure safety and effectiveness in helicopter operation, these vehicles are enhanced with feedback control systems which can go from simple mechanical stabiliza-tion devices to Automatic
9、 Flight Control Systems (AFCSs) (Prouty & Curtiss, 2003; Stiles, Mayo, Freisner, Landis, & Kothmann, 2004).Precise control and carefree HQs in future helicopter designsmay only be achieved with control laws that balance theconflicting requirements of stability and maneuverability. This means that he
10、licopter flight control requires strategies that allow to cope with the nonlinearities of the system while providing robustness in the presence of inaccuracies due to changes in configuration and to the inability to characterize its aerodynamics with high levels of fidelity (Pavel, 2001). As the lat
11、ter uncertainties are generally substantial or unknown, an adaptive control architecture may be required. This is, in fact, the most common strategy of the past few years (Hovakimyan, Kim, Calise, Prasad, & Corban, 2001; Lee, Ha, & Kim, 2005; Leitner, Calise, & Prasad, 1998; Moelans, 2008): a Nonlin
12、ear Dynamic Inversion (NDI) (also referred to as Feedback Linearization technique) of an approximate model (linearized at a pre-specified trim condition) together with adaptive elements to compensate for the inversion error. In general, further developments consider the same type of architecture, bu
13、t introduce some improvements in the structure of the dynamic inversion (Johnson & Kannan, 2005) or in the adaptive aws (Zeng & Zhu, 2006).Adaptive control systems are however limited in terms of practical applicability, not only due to their complex high-order architectures, but also due to flight
14、certification issues because (1) it is difficult to prove that the controller will never “learn” incorrectly, causing harm to the vehicle, and (2) it is also hard to prove that it is able to recover from a failure in adaptation (Johnson & Calise, 2000). In order to overcome these shortcomings, this
15、paper derives the application of a novel technique known as Incremental Nonlinear Dynamic Inversion (INDI) to helicopter flight control. The INDI (also referred to as modified, simplified or sensor-based NDI) has been recently adopted for fixed-wing aircraft flight control (Bacon, Ostroff, & Joshi, 2001; Chen & Zhang, 2008; Sieberling, Chu, & Mulder, 2010). By computing incremental commands instead of the total control inputs and employing acceleration feedback to extract the information relative to aerodynamic cha
