FUZZY DIRECT ADAPTIVE CONTROL FOR A CLASS OF DECENTRALIZED NONLINEAR SYSTEMS

In this paper, a stable fuzzy direct control scheme is presented for a class of interconnected nonlinear systems with unknown nonlinear subsystems and unknown nonlinear interconnections. In this control algorithm, fuzzy logic systems are employed to approximate the optimal controllers, which are designed on the assumption that all dynamics for each subsystem are known; then the fuzzy controllers and adaptation mechanisms for each subsystem depend only on local measurements to provide asymptotic tracking of a reference trajectory. In addition, a fuzzy sliding mode controller is developed to compensate for the fuzzy approximating errors and attenuate the interactions between subsystems. Global asymptotic stability is established in the Lyapunov sense, with the tracking errors converging to a neighborhood of zero. A simulation example is given to illustrate the performance of the proposed method.     

无人机非确定性等价自适应容错飞行控制

针对存在执行器复合故障的固定翼无人机跟踪控制问题,本文提出一种基于非确定性等价原理的自适应容错飞行控制策略.该策略能够有效地估计无人机纵向动态中执行器的失效及漂移故障,保证故障发生后闭环系统的最优性能指标.在自适应容错飞行控制设计中,通过引入辅助系统并动态调节因子,构造非确定性等价原理中偏微分方程的近似解,以简化自适应律设计复杂度.此外,借助Lyapunov稳定性分析方法,证明了在所设计的自适应容错控制器作用下闭环系统的稳定性.最后,仿真验证表明所设计的控制方法能够保证故障无人机的闭环系统性能.     

Decentralized adaptive fuzzy sliding mode control for reconfigurable modular manipulators

A stable decentralized adaptive fuzzy sliding mode control scheme is proposed for reconfigurable modular manipulators to satisfy the concept of modular software. For the development of the decentralized control, the dynamics of reconfigurable modular manipulators is represented as a set of interconnected subsystems. A first‐order Takagi–Sugeno fuzzy logic system is introduced to approximate the unknown dynamics of subsystem by using adaptive algorithm. The effect of interconnection term and fuzzy approximation error is removed by employing an adaptive sliding mode controller. All adaptive algorithms in the subsystem controller are derived from the sense of Lyapunov stability analysis, so that resulting closed‐loop system is stable and the trajectory tracking performance is guaranteed. The simulation results are presented to show the effectiveness of the proposed decentralized control scheme. Copyright © 2009 John Wiley & Sons, Ltd.     

Multivariable sliding mode backstepping controller design for quadrotor UAV based on disturbance observer

This paper deals with the tracking control problem of quadrotor unmanned aerial vehicles (QUAVs) with external disturbances. First, because the QUAV model contains two non-integrity constraints, the dynamic model of the QUAV is decomposed into two subsystems which are independently controlled, so as to reduce controller design complexity. Secondly, the nonlinear disturbance observer (DOB) technique is integrated into a backstepping control method to design the controller for the first subsystem, in which a DOB is applied to estimate the lumped uncertainty. Based on the double power reaching law and the DOB, a multivariable sliding mode control (MSMC) scheme is developed for the second subsystem. Thirdly, based on Lyapunov theory, the closed-loop system is proved to be asymptotically stable. Finally, our comparative simulation results demonstrate that the presented control scheme behaves better in terms of tracking performance than the adaptive backstepping control (ABC) approach.     

Zero dynamics stabilisation and adaptive trajectory tracking for WIP vehicles through feedback linearisation and LQR technique

This paper presents a composite control strategy integrating adaptive sliding-mode control and the linear quadratic regulator (LQR) technology for a wheeled inverted pendulum (WIP) vehicle system. The system can be partitioned into an actuated rotational subsystem and an underactuated longitudinal subsystem based on the different control input in the mathematical model. In particular, the instability analysis of zero dynamic for the underactuated longitudinal subsystem is investigated in detail using the feedback linearisation technology. Then, an adaptive sliding-mode control is designed for the trajectory tracking, where an adaptive algorithm is developed to handle with the parameter uncertainties. In addition, the LQR technique is employed to guarantee zero dynamics stability so as to achieve simultaneously the vehicle body stabilisation at the upright position. Simulation results show the good performance and strong robustness of the proposed control schemes.     

Trajectory Control of a Quadrotor Subject to 2D Wind Disturbances

The paper addresses the flight control of a quad-rotor subject to two dimensional unknown static/varying wind disturbances. A model separation is proposed to simplify the control of the six-degrees-of-freedom (6DOF) nonlinear dynamics of the flying robot. Such approach allows to deal with quad-rotor’s 3D-motion via two subsystems: dynamic (altitude and MAV-relative forward velocity) and kinematic (nonholonomic-like navigation) subsystems. In terms of control, a hierarchical control is used as the overall control structure to stabilize the kinematic underactuaded subsystem. A control strategy based on sliding-mode and adaptive control techniques is proposed to deal with slow and fast time-varying wind conditions, respectively. This choice not only provides well tracking control but also improves the estimation of unknown disturbance. The backstepping technique is used to stabilize the inner-loop heading dynamics, such recursive design takes into account a constrained heading rate. Promising simulations results show the validity of the proposed control strategy while tracking a time-parameterized straight-line and sinusoidal trajectory.     

固定翼无人机自动着陆的一体化制导控制

本文基于制导控制一体化方法的思想,将滑模变结构控制和自抗扰控制技术结合于动态面控制结构中,提出一种固定翼无人机自动着陆方法.在建立六自由度无人机模型、无人机和目标点间的相对视线角度模型的基础上,在动态面控制框架下加入滑模变结构控制来设计制导控制一体化方法.在此过程中加入自抗扰控制技术,提高了系统对未建模部分、参数的不确定性和外界干扰的鲁棒性,并抑制了滑模变结构控制的抖振.该方法使得无人机在平稳地飞向目标点的同时能够满足着陆视线角度的约束.文中详细论述设计思想和设计方法,最后通过仿真验证说明本文方法的有效性.     

Adaptive Reinforcement Learning Strategy with Sliding Mode Control for Unknown and Disturbed Wheeled Inverted Pendulum

This paper develops a novel adaptive integral sliding-mode control (SMC) technique to improve the tracking performance of a wheeled inverted pendulum (WIP) system, which belongs to a class of continuous time systems with input disturbance and/or unknown parameters. The proposed algorithm is established based on an integrating between the advantage of online adaptive reinforcement learning control and the high robustness of integral sliding-mode control (SMC) law. The main objective is to find a general structure of integral sliding mode control law that can guarantee the system state reaching a sliding surface in finite time. An adaptive/approximate optimal control based on the approximate/adaptive dynamic programming (ADP) is responsible for the asymptotic stability of the closed loop system. Furthermore, the convergence possibility of proposed output feedback optimal control was determined without the convergence of additional state observer. Finally, the theoretical analysis and simulation results validate the performance of the proposed control structure.

     

飞翼布局无人机分数阶积分滑模姿态控制

针对存在复合干扰的飞翼布局无人机(UAV)姿态控制问题,提出了一种基于分数阶积分滑模与双幂次趋近律的姿态跟踪控制方案.结合分数阶微积分及滑模变结构控制理论,设计了分数阶积分滑模面.为解决传统趋近律收敛时间长和抖振严重等不足,提出一种具有二阶滑模特性且有限时间收敛的双幂次趋近律.在名义控制律的基础上,设计super twisting滑模干扰观测器,实现对复合干扰的估计和补偿,增强内外环控制器应对复合干扰的鲁棒性.为充分利用冗余操纵面与解决非线性舵效问题,在飞行控制系统中引入了非线性控制分配环节.仿真结果验证了所提方案的有效性.     

不确定时滞切换系统的鲁棒滑模控制

该文研究了一类具有非匹配不确定性和非线性扰动的时滞切换系统的滑模控制问题.首先,针对每个子系统设计对应的时滞依赖滑模面,利用驻留时间方法,给出了由滑动模态方程组成的切换系统鲁棒渐近稳定的充分条件;然后设计了滑模控制器,使得闭环系统的状态能够到达滑模面上,产生滑动模态.最后,仿真实例说明所提出方法的有效性.     

Adaptive nonlinear model predictive path-following control for a fixed-wing unmanned aerial vehicle

This paper presents an adaptive Nonlinear Model Predictive Control (NMPC) for the path-following control of a fixed-wing unmanned aerial vehicle (UAV). The objective is to minimize the mean and maximum errors between the reference path and the UAV. Navigating in a cluttered environment requires accurate tracking. However, linear controllers cannot provide good tracking performance due to nonlinearities that arise in the system dynamics and physical limitations such as actuator saturation and state constraints. NMPC provides an alternative since it can combine multiple objectives and constraints, which minimize the objective function. However, it is difficult to decide appropriate control horizon since the path-following performance depends on the profile of the path. Therefore, a fixed-horizon NMPC cannot guarantee accurate tracking performance. An adaptive NMPC that varies the control horizon according to the path curvature profile for tight tracking is proposed in this paper. Simulation results show that the proposed adaptive NMPC controller can follow the path more accurately than a conventional, fixed-horizon NMPC.     

一类非线性系统的自适应滑模模糊控制

针对一类具有多个子系统的欠驱动非线性系统提出了一种自适应滑模模糊控制方法. 首先通过分析模糊控制与边界层滑模控制的相似性,提出了滑模模糊控制方法;然后根据滑模 面斜率和各子系统控制对于系统动态性能的影响,分别采用模糊推理根据系统状态自动地实时 调节滑模面斜率和各子系统在系统控制中的作用;最后通过简单的滑模模糊控制器实现对具有 多个子系统的欠驱动非线性系统的控制.将该方法应用于吊车的运输控制中,仿真结果证明了 其有效性和鲁棒性.     

Decentralized adaptive iterative learning control for interconnected systems with uncertainties

In many applications,the system dynamics allows the decomposition into lower dimensional subsystems with interconnections among them.This decomposition is motivated by the ease and flexibility of the controller design for each subsystem.In this paper,a decentralized model reference adaptive iterative learning control scheme is developed for interconnected systems with model uncertainties.The interconnections in the dynamic equations of each subsystem are considered with unknown boundaries.The proposed controller of each subsystem depends only on local state variables without any information exchange with other subsystems.The adaptive parameters are updated along iteration axis to compensate the interconnections among subsystems.It is shown that by using the proposed decentralized controller,the states of the subsystems can track the desired reference model states iteratively.Simulation results demonstrate that,utilizing the proposed adaptive controller,the tracking error for each subsystem converges along the iteration axis.     

H∞ tracking-based sliding mode control foruncertain nonlinear systems via an adaptive fuzzy-neural approach

A novel adaptive fuzzy-neural sliding-mode controller with H(infinity) tracking performance for uncertain nonlinear systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors. Because of the advantages of fuzzy-neural systems, which can uniformly approximate nonlinear continuous functions to arbitrary accuracy, adaptive fuzzy-neural control theory is then employed to derive the update laws for approximating the uncertain nonlinear functions of the dynamical system. Furthermore, the H(infinity) tracking design technique and the sliding-mode control method are incorporated into the adaptive fuzzy-neural control scheme so that the derived controller is robust with respect to unmodeled dynamics, disturbances and approximate errors. Compared with conventional methods, the proposed approach not only assures closed-loop stability, but also guarantees an H(infinity) tracking performance for the overall system based on a much relaxed assumption without prior knowledge on the upper bound of the lumped uncertainties. Simulation results have demonstrated that the effect of the lumped uncertainties on tracking error is efficiently attenuated, and chattering of the control input is significantly reduced by using the proposed approach.     

非匹配扰动干扰下的无人直升机轨迹跟踪控制

针对小型无人直升机在飞行过程中容易受到非匹配扰动影响的特点,本文设计了一种基于新型滑模控制方法的轨迹跟踪控制器.首先,建立了无人直升机系统的非线性数学模型,并对该模型进行近似反馈线性化处理,同时将模型分为位置和偏航两个子系统;然后,利用扩展扰动观测器对复合扰动以及非匹配扰动的各阶导数的估计值,设计新型时变滑模面,得到滑模控制律,并给出了控制系统的稳定性分析;最后,仿真结果验证了控制方法的有效性和优越性.该新型滑模控制方法的优越性主要体现在:对非匹配扰动具有较强的鲁棒性,以及能有效地抑制抖振现象.     

Adaptive composite suboptimal control for linear singularly perturbed systems with unknown slow dynamics

In this article, using singular perturbation theory and adaptive dynamic programming (ADP) approach, an adaptive composite suboptimal control method is proposed for linear singularly perturbed systems (SPSs) with unknown slow dynamics. First, the system is decomposed into fast‐ and slow‐subsystems and the original optimal control problem is reduced to two subproblems in different time‐scales. Afterward, the fast subproblem is solved based on the known model of the fast‐subsystem and a fast optimal control law is designed by solving the algebraic Riccati equation corresponding to the fast‐subsystem. Then, the slow subproblem is reformulated by introducing a system transformation for the slow‐subsystem. An online learning algorithm is proposed to design a slow optimal control law by using the information of the original system state in the framework of ADP. As a result, the obtained fast and slow optimal control laws constitute the adaptive composite suboptimal control law for the original SPSs. Furthermore, convergence of the learning algorithm, suboptimality of the adaptive composite suboptimal control law and stability of the whole closed‐loop system are analyzed by singular perturbation theory. Finally, a numerical example is given to show the feasibility and effectiveness of the proposed methods.     

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler–Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.     

Decoupled fuzzy sliding-mode control

A decoupled fuzzy sliding-mode controller design is proposed. The decoupled method provides a simple way to achieve asymptotic stability for a class of fourth-order nonlinear systems with only five fuzzy control rules. The ideas behind the controller are as follows. First, decouple the whole system into two second-order systems such that each subsystem has a separate control target expressed in terms of a sliding surface. Then, information from the secondary target conditions the main target, which, in turn, generates a control action to make both subsystems move toward their sliding surface, respectively. A closely related fuzzy controller to the sliding-mode controller is also presented to show the theoretical aspect of the fuzzy approach in which the characteristics of fuzzy sets are determined analytically to ensure the stability and robustness of the fuzzy controller. Finally, the decoupled sliding-mode control (SMC) is used to control three highly nonlinear systems and confirms the validity of the proposed approach     

Experimental Control of a Two-Dof Flexible Robot Manipulator by Optimal and Sliding Methods

This paper presents an experimental study of a robust control scheme for flexible-link robotic manipulators. The design is based on a simple strategy for trajectory tracking which exploits the two-time scale nature of the flexible part and the rigid part of the dynamic equations of this kind of robotic arms: A slow subsystem associated with the rigid motion dynamics and a fast subsystem associated with the flexible link dynamics. Two experimental approaches are considered. In a first test an LQR optimal design strategy is used, while a second design is based on a sliding-mode scheme. Experimental results on a laboratory two-dof flexible manipulator show that this composite approach achieves good closed-loop tracking properties for both design philosophies, which compare favorably with conventional rigid robot control schemes.     

基于CFD方法的固定翼无人机着陆控制建模

为了实现固定翼无人机低速平稳着陆的目的,以某型无人机为例,阐述以计算流体动力学(CFD)方法求解固定翼无人机气动力系数的过程,即构建飞机几何模型、设定计算域并划分网格、基于非耦合隐式求解器求解在K-E湍流模型下各飞行状态的气动系数.提出以较大迎角低速滑翔降落的着陆控制方法,基于求解的气动特性,计算飞机降落前的理想状态,并基于状态反馈的纵向控制律实现着陆控制.在Simulink环境中,基于AeroSim工具箱构建仿真程序,验证了方法的有效性.