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.     

On a nonlinear multivariable servomechanism problem

Multivariable nonlinear plants with both measured and unmeasured vector disturbance signals are considered. Output-feedback, dynamic control laws are designed for the problem of tracking a constant or slowly-varying reference input while rejecting constant or slowly-varying disturbances.     

Uncertainty modeling and robust minimax LQR control of multivariable nonlinear systems with application to hypersonic flight

For a class of multi‐input and multi‐output nonlinear uncertainty systems, a novel approach to design a nonlinear controller using minimax linear quadratic regulator (LQR) control is proposed. The proposed method combines a feedback linearization method with the robust minimax LQR approach in the presence of time‐varying uncertain parameters. The uncertainties, which are assumed to satisfy a certain integral quadratic constraint condition, do not necessarily satisfy a generalized matching condition. The procedure consists of feedback linearization of the nominal model and linearization of the remaining nonlinear uncertain terms with respect to each individual uncertainty at a local operating point. This two‐stage linearization process, followed by a robust minimax LQR control design, provides a robustly stable closed loop system. To demonstrate the effectiveness of the proposed approach, an application study is provided for a flight control problem of an air‐breathing hypersonic flight vehicle (AHFV), where the outputs to be controlled are the longitudinal velocity and altitude, and the control variables are the throttle setting and elevator deflection. The proposed method is used to derive a linearized uncertainty model for the longitudinal motion dynamics of the AHFV first, and then a robust minimax LQR controller is designed, which is based on this uncertainty model. The controller is synthesized considering seven uncertain aerodynamic and inertial parameters. The stability and performance of the synthesized controller is evaluated numerically via single scenario simulations for particular cruise conditions as well as a Monte‐Carlo type simulation based on numerous cases. It is observed that the control scheme proposed in this paper performs better, especially from the aspect of robustness to large ranges of uncertainties, than some controller design schemes previously published in the literature. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Equilibrium response of flight control systems

The steady-state response of a controlled system is of particular importance in non-zero set point regulation, and nowhere is this of more concern than in the piloting of aircraft. Possible equilibrium states are, to a large extent, independent of the aircraft's stability and transient behavior; hence, stability and command objectives can be specified separately. Singular as well as nonsingular steady-state response may be desirable from the pilot's viewpoint, i.e. a constant command vector can imply varying state and control vectors. The flight control structure can be designed to account for this characteristic, while allowing full state or state-estimate feedback if desired. Dissimilar command vectors lead to markedly different responses in systems whose eigenvalues and eigenvectors are identical. A methodology for designing to achieve proper command response is presented, and numerical and graphical illustrations are provided for a generic lightweight fighter aircraft example.     

低速行驶车辆的非线性系统建模及控制

针对低速行驶工况下的车辆Stop and Go(起-停)巡航控制系统,本文推导其纵向行驶的非线性动力学方程.在此基础上采用精确线性化变换将非线性系统转化为线性可控正则型,并对此正则型设计一种跟踪控制器,实现了车辆低速甚至起-停工况的加速度精确跟踪.     

一种新的多输入非线性控制系统线性化的计算方法

通常, 即使对于一个可逼近反馈线性化的非线性系统, 求得一个所需的坐标变换和反馈仍然是困难的, 原因在于需要求解一组偏微分方程. 在本文中, 为了求得逼近反馈线性化所需的非线性反馈及坐标变换, 首先引入了一个扩展的坐标空间, 针对一类线性可控的多输入非线性系统, 推导了系统新的矩阵表达式. 然后, 提出了一种新的有效的构造化算法, 它降低了计算所需的运算量. 最后通过一个例子介绍了本方法的应用.     

一种新的多输入非线性控制系统高阶逼近线性化的计算方法

通常,即使对于一个可逼近反馈线性化的非线性系统,求得一 个所需的坐标变换和反馈仍然是困难的,原因在于需要求解一组偏微分 方程. 在本文中, 为了求得逼近反馈线性化所需的非线性反馈及坐标变 换, 我们首先引入了一个扩展的坐标空间, 针对一类线性可控的多输入非 线性系统,推导了系统新的矩阵表达式。基于这些准备,我们提出了一种 新的有效的构造化算法,它降低了计算所需的运算量。最后通过一个例 子我们介绍了本方法的应用.     

基于逆系统方法的广义非线性系统控制及电力系统应用

对一般广义非线性系统的反馈线性化问题,通过将代数变量视为虚拟输入,给出了构造性递归求逆算法,实现了系统的精确反馈线性化.作为该算法的应用,讨论了带有非线性负荷的三节点电力系统的励磁控制问题,设计了非线性励磁控制器.仿真结果表明了方法的有效性.     

Stationary policies for lower bounds on the minimum average cost of discrete‐time nonlinear control systems

The paper deals with the control problem of discrete‐time nonlinear systems. The main contribution of this note is to present conditions that assure the existence of stationary policies that generate lower bounds for the minimal long‐run average cost. These lower bounds coincide with the optimal solution when a mild convergence assumption holds. To illustrate the results, the paper presents an application for the simultaneous state‐feedback control problem, and the derived strategy is used to design a real‐time simultaneous control for two direct current motor devices. The dynamics of these two devices are written in terms of a nonlinear algebraic matrix recurrence, which in turn represents a particular case for our general nonlinear approach. The optimal gain for the corresponding simultaneous state‐feedback problem is obtained, and such a gain was implemented in a laboratory testbed to control simultaneously the two direct current motors. Copyright © 2013 John Wiley & Sons, Ltd.     

一类不确定非线性系统的鲁棒自适应轨迹线性化控制

针对一类不确定非线性系统,研究了一种新的鲁棒自适应轨迹线性化控制方案.利用径向基神经网络的在线逼近能力以及被控对象分析模型的有用信息设计一种径向基神经网络干扰观测器来估计系统中存在的不确定性.观测器输出用于设计补偿控制律抵消不确定性对系统性能的影响,鲁棒自适应控制律用于克服逼近误差.采用Lyapunov方法严格证明了在自适应调节律作用下闭环系统所有误差信号最终有界.最后利用倒立摆系统验证了新方法的有效性.     

Suboptimal control of nonlinear systems

The Modified LJ search method used by Nair[1] to find suboptimal controllers for linear systems is extended to the case of nonlinear systems. To illustrate the method, three numerical examples are discussed.     

A two-tier control architecture for nonlinear process systems with continuous/asynchronous feedback

In this work, we introduce a two-tier control architecture for nonlinear process systems with both continuous and asynchronous sensing and actuation. This class of systems arises naturally in the context of process control systems based on hybrid communication networks (i.e. point-to-point wired links integrated with networked wired or wireless communication) and utilising multiple heterogeneous measurements (e.g. temperature and concentration). Assuming that there exists a lower-tier control system which relies on point-to-point communication and continuous measurements to stabilise the closed-loop system, we propose to use Lyapunov-based model predictive control to design an upper-tier networked control system to profit from both the continuous and the asynchronous measurements as well as from additional networked control actuators. The proposed two-tier control system architecture preserves the stability properties of the lower-tier controller while improving the closed-loop performance. The theoretical results are demonstrated using two different chemical process examples.     

磁浮列车的非线性控制问题研究

建立了磁浮列车悬浮系统模型, 针对模型的非线性问题, 利用反馈线性化技术, 将系统的输入-状态线性化, 设计出一个P控制器和一个非线性补偿器, 得到了良好的仿真结果. 在此基础上, 进行了数字控制实验, 比较了仿真和实验结果. 实验表明反馈线性化技术可以解决磁浮列车非线性模型的控制问题.     

一类非线性离散系统自适应准滑模控制

针对一般非线性离散时间系统的不确定性和扰动抑制问题, 提出一种新的自适应准滑模控制算法. 算法包括两部分, 其一是基于紧格式动态线性化模型的自适应准滑模控制器设计, 其中动态线性化方法中“伪偏导数”的估计算法仅依赖于系统I/O 实时量测值. 其二是采用径向基神经网络估计器来估计系统的综合不确定性. 理论分析证明了系统的BIBO稳定性. 仿真结果验证了所提算法的有效性.     

The early days of geometric nonlinear control

Around 1970 the study of nonlinear control systems took a sharp turn. In part, this was driven by the hope for a more inclusive theory which would be applicable to various newly emerging aerospace problems lying outside the scope of linear theory, and also by the gradual realization that tools from differential geometry, and Lie theory in particular, could be seen as providing a remarkably nice fit with what seemed to be needed for the wholesale extension of linear control theory into a nonlinear setting. This paper discusses an initial phase of the development of geometric nonlinear control, including material on the broader context from which it emerged. We limit our account to developments occurring up to the early 1980s, not because the field stopped developing at that point but rather to limit the scope of the project to something manageable. Even so, because of the volume and diversity of the literature we have had to be selective, even within the given time frame.     

Asymptotic output tracking through singular points for nonlinear systems: Stability,disturbance rejection and robustness

The problem of output tracking in the presence of singularities started by Hirschorn and Davis (1987)² is reexamined. A transformation which allows us to make a study of the closed-loop stability of the nonlinear system is proposed. An error feedback control law relaxes the initial conditions imposed on the system and the function to be followed, obtaining asymptotic output tracking. A study of the singular tracking problem, when there exist disturbances or uncertainties in the dynamics, is also made. Again a stability analysis is carried out. Finally, the results obtained for the SISO case, to the MIMO case are extended.     

Extension of efficient predictive control to the nonlinear case

The combined use of the closed‐loop paradigm, an augmented autonomous state space formulation, partial invariance, local affine difference inclusion, and polytopic invariance are deployed in this paper to propose an NMPC algorithm which, unlike earlier algorithms that have to tackle online a nonlinear non‐convex optimization problem, requires the solution of a simple QP. The proposed algorithm is shown to outperform earlier algorithms in respect of size of region of attraction and online computational load. Conversely, for comparable computational loads, the proposed algorithm outperforms earlier algorithms in terms of optimality of dynamic performance. Copyright © 2005 John Wiley & Sons, Ltd.     

三相电压型逆变器的一种非线性复合控制策略研究

为了减少在三相电压型逆变器系统中应用精确线性化时选择反馈增益矩阵参数的随机性,提出将精确线性化方法和反步法结合起来应用于此系统中.首先根据非线性微分几何理论,验证了该系统仿射非线性模型满足2输入2输出系统精确线性化的条件.经过非线性坐标变换得到系统的参数严格反馈形式模型,再根据反步法的设计步骤,逐步设计虚拟控制相量和中间控制相量,使系统的状态分量具有渐近稳定性,从而得到原非线性系统的控制模型.最后通过实验验证了该复合控制策略的可行性.     

Adaptive fuzzy dynamic surface control for uncertain nonlinear systems

In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of ＂explosion of complexity＂ in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globally uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller （SMC）. Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.     

Distributed nonlinear model predictive control based on contraction theory

A novel distributed model predictive control algorithm for continuous‐time nonlinear systems is proposed in this paper. Contraction theory is used to estimate the prediction error in the algorithm, leading to new feasibility and stability conditions. Compared to existing analysis based on Lipschitz continuity, the proposed approach gives a distributed model predictive control algorithm under less conservative conditions, allowing stronger couplings between subsystems and a larger sampling interval when the subsystems satisfy the specified contraction conditions. A numerical example is given to illustrate the effectiveness and advantage of the proposed approach.