交会对接模拟系统姿态位置耦合有限时间控制

针对航天器交会对接模拟系统的姿态同步和位置跟踪控制问题,在存在外界扰动和系统不确定性的情况下,基于改进的快速非奇异终端滑模面和改进的自适应律,采用双闭环控制结构分别设计内环和外环有限时间姿态位置耦合控制器.所提出的自适应律不仅能有效地抑制扰动和不确定性且能保证控制器是连续的.李雅普诺夫理论推导和仿真结果表明,所提出的控制方法能保证系统内环和外环跟踪误差的有限时间稳定性和准确收敛性.     

Nonlinear adaptive control using the Fourier integral and itsapplication to CSTR systems

This paper presents a new nonlinear adaptive tracking controller for a class of general time-variant nonlinear systems. The control system consists of an inner loop and an outer loop. The inner loop is a fuzzy sliding mode control that is used as the feedback controller to overcome random instant disturbances. The stability of the inner loop is designed by the sliding mode control method. The other loop is a Fourier integral-based control that is used as the feedforward controller to overcome the deterministic type of uncertain disturbance. The asymptotic convergence condition of the nonlinear adaptive control system is guaranteed by the Lyapunov direct method. The effectiveness of the proposed controller is illustrated by its application to composition control in a continuously stirred tank reactor system.     

Robust Flight Control Using Nonsmooth Optimization for a Tandem Ducted Fan Vehicle

This work addresses the aerodynamic modeling and near‐hover‐flight control design for an unconventional aerial robot of the tandem ducted fan configuration, which is intended to be prototypical of a flight service vehicle. The main model elements of this novel unmanned vehicle, which exhibit highly nonlinear and unstable open‐loop modes, are presented. A frequency‐domain controllability analysis concerning the plant's behavior around the hovering flight condition is then adopted to determine the expected control performance, which is of important practical significance to controllability improvement through vehicle design changes. A robust controller that stabilizes the unmanned vehicle under wind disturbances is designed using a newly developed nonsmooth optimization algorithm, which rigorously and efficiently tunes the arbitrarily predefined structured controller against multiple control requirements. A successive two‐loop architecture is employed in the designed controller. In this architecture, the inner loop provides stability augmentation and decoupling, and the outer loop guarantees the desired velocity tracking performance. Simulation results under stochastic wind gusts are presented to verify the performance of the proposed controllers. Preliminary flight tests are also carried out to demonstrate the performance of the system.     

基于非线性L1自适应动态逆的飞行器姿态角控制

钊对常规动态逆控制器不能有效抵消系统中的不确定性这一缺点,提出了一种非线性L_1自适应动态逆控制方法.该方法能够克服常规动态逆的不足,在保证系统鲁棒性的前提下,提升飞行器姿态角控制效果.首先,采用时标分离原理,将姿态角控制系统分为内外两个回路:外回路采用常规动态逆控制器,用于姿态角的跟踪控制;内回路采用非线性L_1自适应控制器,用于角速率的控制.其中,L_1自适应控制器由静态反馈控制器和自适应控制器组成:静态反馈控制器通过状态反馈实现,用于保证内回路的稳定和具有期望的闭环特性;自适应控制器由状态观测器、自适应律和控制律组成,用于抵消系统中的不确定性.其次,对所提控制方法的稳定性进行了分析,结果证明了该控制方法能够保证内回路的稳定和外回路的误差有界.最后,在综合考虑多种不确定性的情况下,将本文提出的非线性L_1自适应动态逆控制方法用于某无人飞行器姿态角控制,仿真结果验证了该控制方法的有效性和鲁棒性.     

一种非线性多环递归自适应跟踪控制

针对控制输入有界的变参数广义高阶非线性系统跟踪控制问题,给出一种多环递归跟踪的鲁棒控制方法.通过分层引入虚拟跟踪器,将高阶系统分解为多个独立子系统;内环虚拟跟踪器使内环输出指数收敛于外环虚拟输入,最内环设计自适应控制器补偿参数摄动和外部干扰,并保证输出指数收敛于外环虚拟输入;多环递归跟踪实现系统输出精确跟踪期望输入,理论证明闭环系统的全局渐近收敛性.数值仿真验证了多环跟踪控制器的可行性和合理性.     

Guidance and nonlinear control system for autonomous flight of minirotorcraft unmanned aerial vehicles

Small unmanned aerial vehicles (UAVs) are becoming popular among researchers and vital platforms for several autonomous mission systems. In this paper, we present the design and development of a miniature autonomous rotorcraft weighing less than 700 g and capable of waypoint navigation, trajectory tracking, visual navigation, precise hovering, and automatic takeoff and landing. In an effort to make advanced autonomous behaviors available to mini‐ and microrotorcraft, an embedded and inexpensive autopilot was developed. To compensate for the weaknesses of the low‐cost equipment, we put our efforts into designing a reliable model‐based nonlinear controller that uses an inner‐loop outer‐loop control scheme. The developed flight controller considers the system's nonlinearities, guarantees the stability of the closed‐loop system, and results in a practical controller that is easy to implement and to tune. In addition to controller design and stability analysis, the paper provides information about the overall control architecture and the UAV system integration, including guidance laws, navigation algorithms, control system implementation, and autopilot hardware. The guidance, navigation, and control (GN&C) algorithms were implemented on a miniature quadrotor UAV that has undergone an extensive program of flight tests, resulting in various flight behaviors under autonomous control from takeoff to landing. Experimental results that demonstrate the operation of the GN&C algorithms and the capabilities of our autonomous micro air vehicle are presented. © 2009 Wiley Periodicals, Inc.     

Nonlinear robust sliding mode control of a quadrotor unmanned aerial vehicle based on immersion and invariance method

We present an asymptotic tracking controller for an underactuated quadrotor unmanned aerial vehicle using the sliding mode control method and immersion and invariance based adaptive control strategy in this paper. The control system is divided into two loops: the inner‐loop for the attitude control and the outer‐loop for the position. The sliding mode control technology is applied in the inner‐loop to compensate the unmatched nonlinear disturbances, and the immersion and invariance approach is chosen for the outer‐loop to address the parametric uncertainties. The asymptotic tracking of the position and the yaw motion is proven with the Lyapunov based stability analysis and LaSalle's invariance theorem. Real‐time experiment results performed on a hardware‐in‐the‐loop‐simulation testbed are presented to validate the good control performance of the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

An adaptive neural network approach to the tracking control of micro aerial vehicles in constrained space

This paper presents an adaptive neural network approach to the trajectory tracking control of micro aerial vehicles especially when they are flying in a limited indoor area. Differing from conventional controllers, the proposed controller employs the outer position loop to directly generate angular velocity commands in the presence of unknown aerodynamics and disturbances and then the fast inner loop to handle the angular rate control. Adaptive neural networks are deployed to estimate all the uncertain factors with the adaptation law derived from the Lyapunov function. To achieve a real-time performance, a norm estimation approach of ideal weights is designed to achieve a high bandwidth and lighten the burden of computation burden. Meanwhile, a barrier Lyapunov function is introduced to guarantee the constraint of vehicle positions as well as the validity of the neural network estimation. Simulations and practical flight tests are conducted to verify the feasibility and effectiveness of the proposed control strategy.     

Design and Implementation of a Flight Control System for an Unmanned Rotorcraft using RPT Control Approach

In this paper, we apply a so‐called robust and perfect tracking (RPT) control technique to the design and implementation of the flight control system of a miniature unmanned rotorcraft, named HeLion. To make the presented work self‐contained, we will first outline some background knowledge, including mainly the nonlinear flight dynamics model and the inner‐loop flight control system design. Next, the highlight of this paper, that is, the outer‐loop flight control system design procedure using RPT control technique, will be detailed. Generally speaking, RPT control technique aims to design a controller such that (i) the resulting closed‐loop system is asymptotically stable, and (ii) the controlled output almost perfectly tracks a given reference signal in the presence of any initial conditions and external disturbances. Since it makes use of all possible information including the system measurement output and the command reference signal together with all its derivatives (if available) for control, RPT control technique is particularly useful for the outer‐loop layer of an unmanned aircraft. Both simulation and flight‐test results will be presented and analyzed at the end of this paper, and the efficiency of the RPT control approach will be evaluated comprehensively.     

Robust dynamic surface trajectory tracking control for a quadrotor UAV via extended state observer

In this paper, we present an extended state observer–based robust dynamic surface trajectory tracking controller for a quadrotor unmanned aerial vehicle subject to parametric uncertainties and external disturbances. First, the original cascaded dynamics of a quadrotor unmanned aerial vehicle is formulated in a strict form with lumped disturbances to facilitate the backstepping design. Second, based on the separate outer‐ and inner‐loop control methodologies, the extended state observers are constructed to online estimate the unmeasurable velocity states and lumped disturbances existed in translational and rotational dynamics, respectively. Third, to overcome the problem of “explosion of complexity” inherent in backstepping control, the technique of dynamic surface control is utilized for trajectory tracking and attitude stabilization, and with the velocity and disturbance estimates incorporated into the dynamic surface control, a robust dynamic surface flight controller that guarantees asymptotic tracking in the presence of lumped disturbances is synthesized. In addition, the stability analysis is given, showing that the present robust controller can ensure the ultimate boundedness of all signals in the closed‐loop system and make the tracking errors arbitrarily small. Finally, comparisons and extensive simulations under different flight scenarios are performed to validate the effectiveness and superiority of the proposed scheme in accurate tracking performance and enhanced antidisturbance capability.     

基于MPU6050和互补滤波的四旋翼飞控系统设计

针对四轴飞行器飞行性能不稳定和惯性测量单元（IMU）易受干扰、存在漂移等问题,利用惯性传感器MPU6050采集实时数据,以经典互补滤波为基础,提出一种可以自适应补偿系数的互补滤波算法,该算法在低通滤波环节加入PI控制器,依据陀螺仪测得的角速度实时调节PI控制器补偿系数。飞行器姿态控制系统采用双闭环PID控制方法,姿态解算的欧拉角作为系统外环,陀螺仪角速度作为系统内环。最后,搭建以NI myRIO为核心控制器的四轴飞行器,通过LabVIEW实现算法和仿真,实验结果表明,自适应互补滤波算法可以准确解算姿态信息,双闭环PID控制超调量小、反应灵敏,控制系统基本满足飞行要求。     

Adaptive speed tracking control for autonomous land vehicles in all‐terrain navigation: An experimental study

This paper develops a nonparametric controller with an internal model control (IMC) structure for the longitudinal speed tracking control of autonomous land vehicles by designing a proportional and internal model control (IMC) cascade (P‐IMC) controller. An IMC architecture is employed in the inner control loop by establishing a nonparametric longitudinal dynamical model, whereas a P controller is designed for the outer control loop. An approach for estimating the terrain effects and compensating for the model errors is also introduced. The differences from other nonparametric controllers are discussed, and the stability of the P‐IMC controller is analyzed and validated experimentally. The P‐IMC controller is compared with the SpAM+PI to illustrate its advantages. The experimental results of autonomous all‐terrain driving show the effectiveness of the P‐IMC controller.     

基于PID和LQR的四旋翼无人机控制系统研究

为提高四旋翼无人机的飞行稳定性、无人飞行器控制系统的鲁棒性和控制精度,以建立的四旋翼无人机飞行控制系统模型为基础,采用现代控制理论与传统控制论相结合的方法,针对姿态角速率、姿态角分别设计内环LQR(线性二次型调节器)控制器,及外环PID控制的双回路闲环控制器.充分利用PID控制器易于掌握且对模型要求精度低、LQR控制器能改善内回路的动态特性和稳态性能的特点,完成四旋翼无人机的飞行控制.通过实验遴选该双闭环控制器相关参数并进行优化,实验结果表明所设计的双回路控制器控制性能指标良好.     

A Robust Controller for A 3‐DOF Flexible Robot with a Time Variant Payload

This article describes a new control scheme designed for a three degree of freedom (3‐DOF) flexible robot. The control scheme consists of two multi variable control loops. The inner loop is the motor's position control system, while the outer loop controls the robot tip's position, thus canceling vibrations which are originated by the structural flexibility of the manipulator during movement. As it will be shown, the outer control loop is robust to payload variations. The outer loop performance is based on a perfect cancelation of the inner loop dynamics. The effects of not achieving such perfect cancelation are also studied, and rules for designing a robust controller in this case are developed. Simulations assuming different payloads have been carried out with successful results for trajectory tracking. Trajectory tracking with a variable payload is also achieved.     

Adaptive‐gain multivariable super‐twisting sliding mode control for reentry RLV with torque perturbation

Reusable launch vehicle (RLV) should be under control in the presence of model uncertainty and external disturbance, which is considered as torque perturbation in this paper during the reentry phase. Such a challenge imposes tight requirements to the enhanced robustness and accuracy of the vehicle autopilot. The key of this paper is to propose an adaptive‐gain multivariable super‐twisting sliding mode controller when considering that the bounds of uncertainty and perturbation are not known. The important features of the controller are that the adaptation algorithm can achieve non‐overestimating values of the control gains and the multivariable super‐twisting sliding mode approach can obtain a more elegant solution in finite time. According to the multiple‐time scale features, the dynamics of RLV attitude motion are divided into outer‐loop subsystem and inner‐loop subsystem. On this basis, the controllers are designed respectively to ensure the finite‐time reentry attitude tracking. In addition, a proof of the finite‐time convergence for the overall system is derived using the Lyapunov function technique and multiple‐time scale characteristic. Finally, simulation results of six degree‐of‐freedom RLV are provided to verify the effectiveness and robustness of the proposed controller in tracking the guidance commands as well as achieving a safe and stable reentry flight. Copyright © 2016 John Wiley & Sons, Ltd.     

A multivariable control scheme for robot manipulators

The article puts forward a simple scheme for multivariable control of robot manipulators to achieve trajectory tracking. The scheme is composed of an inner loop stabilizing controller and an outer loop tracking controller. The inner loop utilizes a multivariable PD controller to stabilize the robot by placing the poles of the linearized robot model at some desired locations. The outer loop employs a multivariable PID controller to achieve input-output decoupling and trajectory tracking. The gains of the PD and PID controllers are related directly to the linearized robot model by simple closed-form expressions. The controller gains are updated on-line to cope with variations in the robot model during gross motion and for payload change. Alternatively, the use of high gain controllers for gross motion and payload change is discussed. Computer simulation results are given for illustration.     

Path‐Tracking Control of a Riderless Bicycle Via Road Preview and Speed Adaptation

In this study, a genetic‐fuzzy control system is used to control a riderless bicycle where control parameters can adapt to the speed change of the bicycle. The equations of motion are developed for a bicycle with constraints of rolling‐without‐slipping contact condition between the wheels and ground. This controller consists of two loops: the inner is a roll‐angle‐tracking controller which generates steering torque to control the roll angle while guaranteeing the stability, and the outer is a path‐tracking controller which generates the reference roll angle for the inner loop. The inner loop is a sliding‐mode controller (SMC) designed on the basis of a linear model obtained from a system identification process. By defining a stable sliding surface of error dynamics and an appropriate Lyapunov function, the bicycle can reach the roll‐angle reference in a finite time and follow that reference without chattering. The outer loop determines the proper reference roll‐angle by using a fuzzy‐logic controller (FLC) in which previewing and tracking errors are taken into consideration. The robustness of the proposed controller against speed change and external disturbances is verified by simulations.     

Adaptive hybrid force/position control of robot manipulators using an adaptive force estimator in the presence of parametric uncertainty

This study is devoted to sensorless adaptive force/position control of robot manipulators using a position-based adaptive force estimator (AFE) and a force-based adaptive environment compliance estimator. Unlike the other sensorless method in force control that uses disturbance observer and needs an accurate model of the manipulator, in this method, the unknown parameters of the robot can be estimated along with the force control. Even more, the environment compliance can be estimated simultaneously to achieve tracking force control. In fact, this study deals with three challenging problems: No force sensor is used, environment stiffness is unknown, and some parametric uncertainties exist in the robot model. A theorem offers control laws and updating laws for two control loops. In the inner loop, AFE estimates the exerted force, and then, the force control law in the outer loop modifies the desired trajectory of the manipulator for the adaptive tracking loop. Besides, an updating law updates the estimated compliance to provide an accurate tracking force control. Some experimental results of a PHANToM Premium robot are provided to validate the proposed scheme. In addition, some simulations are presented that verify the performance of the controller for different situations in interaction.     

基于时标分离的飞行器姿态双环控制器设计方法

基于时标分离思想,将飞行器姿态控制系统分为慢变化的姿态角回路和快变化的角速度回路分别设计。外环采用精确线性化方法设计控制器。考虑到飞行器转动惯量的大范围时变或摄动,内环采用模型参考自适应控制方法设计控制器。仿真验证了方法的有效性。     

四旋翼无人机抗干扰轨迹跟踪控制

针对四旋翼无人机轨迹跟踪过程中存在的参数不确定与外界干扰问题,设计一种双闭环自适应控制策略.为了降低控制器设计复杂度,根据四旋翼无人机系统的欠驱动特性将系统分成姿态内环和位置外环.在扰动观测器的基础上,利用积分型反步控制算法完成无人机位置信息在外界干扰下的稳定跟踪控制.在扰动观测器的基础上,利用自适应滑模控制算法完成无人机姿态信息在参数不确定和外界干扰作用下的稳定跟踪控制.与传统PID控制和滑模控制进行仿真对比,验证所提出控制策略的优越性.