Control system design and evaluation for robust autonomous rotorcraft guidance

This paper describes the design and performance analysis of a control system for rotorcraft with an emphasis on the requirements called for by autonomous guidance. To be able to track trajectories, such as those generated by a guidance system, a path following controller is used in combination with a velocity control augmentation. The path following system is motivated by nonlinear stability analysis. The velocity control augmentation follows a loop-shaping design for the inner-loop attitude control and a dynamic inversion velocity control design for the outer-loop. The identified model of the dynamics along with the uncertainties is used to determine the robustness and performance of the velocity control system. Finally, the paper presents a novel method to evaluate the overall performance of the control system in terms of the tracking error statistics. These results are then used to determine a tracking error model, which can be used to predict the tracking error for a given reference.     

Trim of rotorcraft multibody models using a neural-augmented model-predictive auto-pilot

The aeromechanical analysis of rotorcraft using comprehensive multibody vehicle models is crucially dependent on the ability to accurately compute the model trim settings. Among the various techniques proposed in the literature, the auto-pilot approach, being independent of the complexity of the model, has the potential to solve trim problems efficiently even for the highly detailed aero-servo-elastic vehicle models that are developed using modern finite-element-based multibody analysis codes. Published proportional auto-pilots show to work well in many practical instances. However, their robustness with respect to the flight condition is often poor, so that they must be accurately tuned. In this paper, an auto-pilot based on adaptive non-linear model-predictive control is proposed. The formulation uses a non-linear reference model of the rotorcraft, which is augmented with an adaptive neural element. The adaptive element identifies and corrects the mismatch between reduced and comprehensive models, thereby improving the predictive capabilities of the controller. The methodology is tested on the wind-tunnel trim of a rotor multibody model and compared to an existing implementation of a classical auto-pilot for comprehensive rotorcraft analysis applications. The proposed controller shows improved stability over the conventional approach without the need for calibration. Commemorative Contribution.     

旋翼空中机器人系统架构及设计

设计并验证了某型旋翼空中机器人的系统架构。整个空中机器人系统由直升机和地面站两部分组成。直升机是空中机器人的主体,可以自主飞行并完成指定任务。地面站用于监控无人直升机的飞行,并实现人机交互等多项功能。此外,地面站还可通过视觉导航系统引导直升机的自主着陆。直升机与地面站之间通过指令数字链路和视频模拟链路进行信息交互和实时通讯。经实际飞行验证,该空中机器人系统具有鲁棒和实时的特点,能实现直升机自主飞行和自主起降功能。     

船舶航迹控制鲁棒自适应模糊设计

研究了船舶直线航迹控制问题.基于Lyapunov稳定性理论,将Nussbaum增益技术融入Backstepping设计方法之中,利用模糊系统逼近系统中的未知非线性,提出一种鲁棒自适应模糊控制算法.该算法保证了闭环系统的信号是一致最终有界的,使得系统输出收敛到零的一个较小邻域,从而能够实现船舶的直线航迹控制;而且,该算法不需要高频增益符号的任何信息,还解决了可能存在的控制器奇异值问题.计算机仿真结果验证了控制器的有效性.     

Robust attitude controller design for miniature quadrotors

This paper addresses the robust attitude control problem of miniature quadrotors. A simplified linear dynamical model is obtained for each attitude angle, whereas nonlinear dynamics, interaxis coupling, parameter perturbations, and external disturbances are considered as uncertainties. For each channel, a linear time‐invariant and decoupled robust controller are proposed based on a linear reduced‐order observer and a robust compensator. The observer is applied to estimate the angular velocities, and the robust compensator is introduced for reducing the effects of uncertainties. It is proven that the estimation errors of angular velocities and angular tracking errors can converge to the given neighborhood of the origin in a finite time. Experimental results on the miniature quadrotor are presented to verify the effectiveness of the proposed control approach. Copyright © 2015 John Wiley & Sons, Ltd.     

网络化控制系统中鲁棒控制器的设计与优化

针对网络化控制系统,提出了新型的延迟状态变量模型,考虑到模型的不确定因素和外 部扰动,推出了鲁棒控制器存在的条件,并给出了该控制器设计和性能优化的方法。仿真结果表明, 该控制器对所有允许的网络延迟、模型不确定性和外部扰动,具有良好的性能。     

挠性系统的鲁棒控制设计

提出一种新的鲁棒设计思想：将挠性模态部分的Nyquist图线安排到右半平面。由于综合运用了频域分析、极点配置、正实性引理、线性矩阵不等式等概念和算法，使得这种鲁棒控制设计得以实现，且简单直观。通过两个算例说明了该设计方法的有效性。     

On the design of multi‐rate tracking controllers: Application to rotorcraft guidance and control

This paper presents a new methodology for the design and implementation of gain‐scheduled controllers for multi‐rate systems. The proposed methodology provides a natural way to address the integrated guidance and control problem for autonomous vehicles when the outputs are sampled at different instants of time. A controller structure is first proposed for the regulation of non‐square multi‐rate systems with more measured outputs than inputs. Based on this structure, an implementation for a gain‐scheduled controller is obtained that satisfies an important property known as the linearization property. The implementation resembles the velocity implementation for single‐rate systems. The method is then applied to the problem of steering an autonomous rotorcraft along a predefined trajectory defined in terms of space and time coordinates. By considering a convenient error vector to describe the vehicle's dynamics, the trajectory tracking problem is reduced to that of regulating the error variables to zero. Because of the periodic multi‐rate nature of the onboard sensor suite, the controller synthesis is dealt with under the scope of linear periodic systems theory. Simulation results obtained with a full non‐linear rotorcraft dynamic model are presented and discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

基于鲁棒自适应反步的可重复使用飞行器再入姿态控制

考虑惯性矩阵不确定和力矩扰动的影响, 设计再入可重复使用飞行器的鲁棒自适应反步姿态控制器. 首先, 设计虚拟控制时, 通过自适应实现对不确定项的未知边界的估计; 其次, 设计实际控制输入时, 为消除反步法的“计算爆炸”问题, 将虚拟控制导数作为不确定项, 引入鲁棒项消除不确定与力矩扰动的影响; 再次, 基于Lyapunov 理论证明了跟踪误差收敛到任意小邻域; 最后, 基于X-33 的六自由度模型仿真验证了所设计的控制策略的有效性.     

Robust LQR design for systems with probabilistic uncertainty

In this paper, we consider the design of robust quadratic regulators for linear systems with probabilistic uncertainty in system parameters. The synthesis algorithms are presented in a convex optimization framework, which optimize with respect to an integral cost. The optimization problem is formulated as a lower‐bound maximization problem and developed in the polynomial chaos framework. Two approaches are considered here. In the first approach, an exact optimization problem is formulated in the infinite‐dimensional space, which is solved approximately using polynomial‐chaos expansions. In the second approach, an approximate problem is formulated using a reduced‐order model and solved exactly. The robustness of the controllers from these two approaches are compared using a realistic flight control problem based on an F16 aircraft model. Linear and nonlinear simulations reveal that the first approach results in a more robust controller.     

Finite-time control of underactuated spacecraft hovering

Finite-time controllers are proposed in this paper for underactuated spacecraft hovering in the absence of the radial or in-track thrust. The indirect method, which is generally adopted to solve the singularity problem in the conventional terminal sliding mode, is modified to ensure the continuity of the high-order time derivative of the sliding surface at the switch points. Rigorous proofs via the Lyapunov-based approaches verify the finite-time stability of the closed-loop system. By comparisons with the asymptotic controllers, the advantages of the finite-time ones in faster convergence rate and enhanced control precision have also been substantiated.     

Robust feedforward design for a two-degrees of freedom controller

In this paper we address the problem of designing the feedforward block of a two degrees of freedom controller in the case of single input single output (SISO) discrete-time linear systems with model uncertainty. In this work the design of the feedforward filter is formulated as a robust model matching problem. First, a closed form solution of the optimal noncausal filter, which minimizes the worst-case model matching error for each ω[0,2π], is obtained. Then, suitable rational stable approximations of the optimal solution are derived either by means of causal filters or, when a preview of the reference signal is available, by means of noncausal FIR filters. The efficiency of the proposed method is tested on a simulated example.     

Robust pole clustering in a good ride quality region of aircraft for matrices with structured uncertainties

This paper presents a general analysis of robust pole clustering in a good ride quality region (GRQR) of aircraft for matrices with structured uncertainties. This region is an intersection of a ring and a horizontal strip, located in the left half-plane, which is a specific non-Ω-transformable region providing good ride quality of aircraft. The paper applies the Rayleigh principle along the norm theory to analyze robust pole clustering within this region since the generalized Lyapunov theory is not valid for non-Ω-transformable regions. Concerned uncertainties are structured/parametric uncertainties, including interval matrices. The results are useful for robust control analysis and design, especially, of robust good ride quality of aircraft, shuttles, vehicles and space station, as well as some industrial systems. An example of the F-16 dynamics for which GRQR is suitable is included to illustrate the results.     

Robust adaptive self-structuring fuzzy control design for nonaffine,nonlinear systems

In this article, a robust adaptive self-structuring fuzzy control (RASFC) scheme for the uncertain or ill-defined nonlinear, nonaffine systems is proposed. The RASFC scheme is composed of a robust adaptive controller and a self-structuring fuzzy controller. In the self-structuring fuzzy controller design, a novel self-structuring fuzzy system (SFS) is used to approximate the unknown plant nonlinearity, and the SFS can automatically grow and prune fuzzy rules to realise a compact fuzzy rule base. The robust adaptive controller is designed to achieve an L ₂ tracking performance to stabilise the closed-loop system. This L ₂ tracking performance can provide a clear expression of tracking error in terms of the sum of lumped uncertainty and external disturbance, which has not been shown in previous works. Finally, five examples are presented to show that the proposed RASFC scheme can achieve favourable tracking performance, yet heavy computational burden is relieved.     

Robust reliable control design for networked control system with sampling communication

In this article, the problem of robust exponential stability and reliable stabilisation for a class of continuous-time networked control systems (NCSs) with a sample-data controller and unknown time-varying sampling rate is considered. The analysis is based on average dwell-time, Lyapunov–Krasovskii functional and linear matrix inequality (LMI) technique. The delay-dependent criteria are developed for ensuring the robust exponential stability of the considered NCSs. The obtained conditions are formulated in terms of LMIs that can easily be solved by using standard software packages. Furthermore, the result is extended to study the robust stabilisation for NCS with parameter uncertainties. A state feedback controller is constructed in terms of the solution to a set of LMIs, which guarantee the robust exponential stabilisation of NCS and the controller. Finally, numerical examples are presented to illustrate the effectiveness of the obtained results.     

Robust passivity-based control design for active nonlinear suspension system

In this article, we propose a novel interconnection and damping assignment passivity-based control (IDA-PBC) design for a quarter car nonlinear active suspension system. As an energy shaping method, IDA-PBC is suitable for applying the main concept of skyhook (SH) control. In addition to the damping term, we utilize the characteristics of the energy shaping method to change the sprung and unsprung masses, thereby strengthening the vibration suppression effect. An IDA-PBC-based controller design for an active suspension system, which includes a nonlinear spring, a nonlinear damper, and mass uncertainty, is proposed. Different from most IDA-PBC applications, which tend to control the position or the velocity, our methods focus on transforming a nonlinear suspension system into a desired linear system with ideal aseismatic properties. Unlike a conventional controller using the SH control strategy, we design a virtual vehicle body and an unsprung mass in addition to the damper coefficients. By deriving the port-Hamiltonian form of the suspension system from its dynamics and rewriting it based on the relative coordinates, we obtain a feedback law that only uses the relative displacement and velocity of the suspension system. We derive the conditions for ensuring the global asymptotical stability of the suspension system and propose the guidelines for parameter selection that can guarantee robust stability against parameter uncertainties.     

Multi-input,multi-output flight control system design for the YF-16 using nonlinear QFT and pilot compensation

Nonlinear quantitative feedback theory (QFT) and pilot compensation techniques are used to design a 2 × 2 flight control system for the YF-16 aircraft over a large range of plant uncertainty. The design is based on numerical input-output time histories generated with a FORTRAN implemented nonlinear simulation of the YF-16. The first step of the design process is the generation of a set of equivalent linear time-invariant (LTI) plant models to represent the actual nonlinear plant. It has been proven that the solution to the equivalent plant problem is guaranteed to solve the original nonlinear problem. Standard QFT techniques are then used in the design synthesis based on the equivalent plant models. A detailed mathematical development of the method used to develop these equivalent LTI plant models is provided. After this inner-loop design, pilot compensation is developed to reduce the pilot's workload. This outer-loop design is also based on a set of equivalent LTI plant models. This is accomplished by modelling the pilot with parameters that result in good handling qualities ratings, and developing the necessary compensation to force the desired system responses.     

Robust design and task-priority control for rescue robot HURCULES

This paper proposes a novel design strategy and task-priority-based control methodology for a robot to successfully complete a rescue operation in an extremely unstructured environment. The mechanical structure is designed to obtain both versatile manipulability and all-terrain mobility. The regularized hierarchical quadratic program is used for whole-body motion and force control. The optimization strategy is reasoning about regularization and thus it ensures convergence of the solution in the face of singularities while taking into account equality and inequality constraints. We demonstrate the effectiveness of the online optimization-based control algorithms through extensive real-world numerical and experimental results. Finally, we highlight that the rescue robot can successfully execute missions to extract a casualty and dispose of a dangerous object both indoor and outdoor environments.