挖掘机轨迹跟踪的滑模变结构控制

对液压挖掘机工作装置的轨迹跟踪进行了研究。在分析了液压挖掘机工作装置的动力学方程的基础上,针对其复杂的非线性,提出了一种新的液压挖掘机工作装置轨迹跟踪方法,即应用机器人学理论,建立了三自由度液压挖掘机工作装置的拉格朗日动力学模型,设计了带低通滤波器的滑模控制器,利用低通滤波器的滤除高频信号的功能,消除控制信号的抖动,给出沿规划轨迹工作所需的控制量,并给出了控制系统的设计方法。对三自由度工作装置进行了仿真研究,其结果表明,所设计的控制器对设定轨迹的跟踪具有良好的动态特性,对系统的不确定性具有较强的鲁棒性,在存在模型误差和外部扰动的情况下,该方案既能达到高精度快速跟踪的目的,又能消除滑模控制的抖动问题。     

A Robust Control Approach for Hydraulic Excavators Using <Emphasis Type="Italic">μ</Emphasis>-synthesis

In this work, a robust control is applied to the automation of a hydraulic excavator. Hydraulic excavators exhibit complex nonlinear behavior due to the inherent nonlinearity of the hydraulic servo system. Furthermore, the hydraulic excavator is subject to large disturbance forces during interaction with the environment. As a result, conventional feedback control techniques, such as a proportional-integral-derivative (PID) control, fail to provide consistent performance over the whole operation region of the excavator. Especially, when phase-offset errors vary between joints, undesirable motions are generated in the workspace, which evidently degrades the overall performance of the controller. With this in mind, we apply a robust control approach to the autonomous hydraulic excavators. By handling the nonlinearities and disturbances as uncertainties within the joint dynamics, a robust controller is designed by means of μ-synthesis that guarantees robust stability and performance within the given uncertainty bounds. Furthermore, by adopting a common model reference for each joint, we seek to increase the overall performance of tracking the digging trajectory in the workspace. Experimental results of the robust controller conducted on an industrial 21-ton class hydraulic excavator are presented.     

Operator-based robust nonlinear optimal vibration control for an L-shaped arm driven by linear pulse motor

An L-shaped arm driven by a linear pulse motor is considered in this paper, an operator-based robust nonlinear control approach is proposed to reduce the vibration of the arm. First, by separating the arm into two parts, its vibration dynamics is modelled based on Euler-Bernoulli beam theory. Second, by using operator-based robust right coprime factorization approach, two control schemes are designed, one for controlling the linear pulse motor move to the desired destination and reducing the vibration of the arm with optimal trajectory, another one is to control vibration of the arm by using a piezoelectric actuator, where a tracking compensator is designed to compensate the hysteresis of the piezoelectric actuator and make the arm vibration track to the reference values. Finally, simulation results are demonstrated to verify the effectiveness of the proposed control scheme.     

Trajectory control of a two DOF rigid–flexible space robot by a virtual space vehicle

Model based control schemes use inverse dynamics of the robot arm to produce the main torque component necessary for trajectory tracking. For a model-based controller one is required to know the model parameters accurately. This is a very difficult job especially if the manipulator is flexible. This paper presents a control scheme for trajectory control of the tip of a two arm rigid–flexible space robot, with the help of a virtual space vehicle. The flexible link is modeled as an Euler–Bernoulli beam. The developed controller uses the inertial parameters of the base of the space robot only. Bond graph modeling is used to model the dynamics of the system and to devise the control strategy. The efficacy of the controller is shown through simulated and animation results.     

Robust tracking control of a unicycle-type wheeled mobile manipulator using a hybrid sliding mode fuzzy neural network

This article presents a robust tracking controller for an uncertain mobile manipulator system. A rigid robotic arm is mounted on a wheeled mobile platform whose motion is subject to nonholonomic constraints. The sliding mode control (SMC) method is associated with the fuzzy neural network (FNN) to constitute a robust control scheme to cope with three types of system uncertainties; namely, external disturbances, modelling errors, and strong couplings in between the mobile platform and the onboard arm subsystems. All parameter adjustment rules for the proposed controller are derived from the Lyapunov theory such that the tracking error dynamics and the FNN weighting updates are ensured to be stable with uniform ultimate boundedness (UUB).     

Direct adaptive control of robotic systems

This paper presents a new approach to adaptive motion control of an important class of robotic systems. The control schemes developed using this approach are very simple and computationally efficient since they do not require knowledge of either the mathematical model or the parameter values of the robotic system dynamics. It is shown that the control strategies are globally stable in the presence of bounded disturbances, and that the size of the tracking errors can be made arbitrarily small. The proposed controllers are very general and are implementable with a wide variety of robotic systems, including both open- and closed-kinematic-chain manipulators. Computer simulation results are given for a seven degree-of-freedom (DOF) Robotics Research Corporation Model K-1607 arm. These results demonstrate that accurate and robust trajectory tracking can be achieved by using the proposed schemes.     

Projection operator-based robust adaptive control of an aerial robot with a manipulator

This paper describes a quadcopter manipulator system, an aerial robot with an extended workspace, its controller design, and experimental validation. The aerial robot is based on a quadcopter with a three degree of freedom robotic arm connected to the base of the vehicle. The work aims to create a stable airborne robot with a robotic arm that can work above and below the airframe, regardless of where the arm is attached. Integrating a robotic arm into an underactuated, unstable system like a quadcopter can enhance the vehicle's functionality while increasing instability. To execute a mission with accuracy and reliability during a real-time task, the system must overcome the inter-coupling effects and external disturbances. This work presents a novel design for a robust adaptive feedback linearization controller with a model reference adaptive controller and hardware implementation of the quadcopter manipulator system with plant uncertainties. The closed-loop stability of the aerial robot and the tracking error convergence with the robust controller is analyzed using Lyapunov stability analysis. The quadcopter manipulator system is custom developed in the lab with an off-the-shelf quadcopter and a 3D-printed robotic arm. The robotic system architecture is implemented using a Jetson Nano companion computer for autonomous onboard flight. Experiments were conducted on quadcopter manipulator system to evaluate the autonomous aerial robot's stability and trajectory tracking with the proposed controller.     

Adaptive control of free-floating space robots in Cartesian coordinates

An adaptive control scheme is proposed for the end-effector trajectory tracking control of free-floating space robots. In order to cope with the nonlinear parameterization problem of the dynamic model of the free-floating space robot system, the system is modeled as an extended robot which is composed of a pseudo-arm representing the base motions and a real robot arm. An on-line estimation of the unknown parameters along with a computed-torque controller is used to track the desired trajectory. The proposed control scheme does not require measurement of the accelerations of the base and the real robot arm. A two-link planar space robot system is simulated to illustrate the validity and effectiveness of the proposed control scheme.     

Robust adaptive trajectory tracking control of underactuated autonomous underwater vehicles with prescribed performance

In this paper, a novel robust adaptive trajectory tracking control scheme with prescribed performance is developed for underactuated autonomous underwater vehicles (AUVs) subject to unknown dynamic parameters and disturbances. A simple error mapping function is proposed in order to guarantee that the trajectory tracking error satisfies the prescribed performance. A novel additional control based on Nussbaum function is proposed to handle the underactuation of AUVs. The compounded uncertain item caused by the unknown dynamic parameters and disturbances is transformed into a linear parametric form with only single unknown parameter called virtual parameter. On the basis of the above, a novel robust adaptive trajectory tracking control law is developed using dynamic surface control technique, where the adaptive law online provides the estimation of the virtual parameter. Strict stability analysis indicates that the designed control law ensures uniform ultimate boundedness of the AUV trajectory tracking closed‐loop control system with prescribed tracking performance. Simulation results on an AUV in two different disturbance cases with dynamic parameter perturbation verify the effectiveness of our adaptive trajectory tracking control scheme.     

Experimental testing of a discrete‐time sliding mode controller for trajectory tracking of a wheeled mobile robot in the presence of skidding effects

This article addresses the trajectory tracking problem for a wheeled mobile base, considering the presence of disturbances that violate the nonholonomic constraint, and using an approximated discrete‐time model for the vehicle. The proposed solution is based on discrete‐time sliding mode control, in order to ensure that the controller is both robust and implementable. The asymptotic boundedness of the discrete‐time tracking errors is theoretically proved, and experimental results are reported, showing the effectiveness of the proposed control law. © 2002 Wiley Periodicals, Inc.     

Precision Synchronization Motion Trajectory Tracking Control of Multiple Pneumatic Cylinders

This paper deals with the synchronized motion trajectory tracking control problem of multiple pneumatic cylinders. An adaptive robust synchronization controller is developed by incorporating the cross‐coupling technology into the integrated direct/indirect adaptive robust control (DIARC) architecture. The position synchronization error and the trajectory tracking error of each cylinder are combined to construct the so‐called coupled position error. The proposed adaptive robust synchronization controller is designed with the feedback of this coupled position error and is composed of two parts: an on‐line parameter estimation algorithm and a robust control law. The former is employed to obtain accurate estimates of model parameters for reducing the extent of parametric uncertainties, while the latter is utilized to attenuate the effects of parameter estimation errors, unmodelled dynamics, and external disturbances. Theoretically, both the position synchronization and trajectory tracking errors will achieve asymptotic convergence simultaneously. Moreover, the effectiveness of the proposed controller is verified by the extensive experimental results performed on a two‐cylinder pneumatic system.     

Adaptive PID-like fault-tolerant control for robot manipulators with given performance specifications

ABSTRACT

This paper investigates the trajectory tracking problem of rigid robot manipulators with unknown dynamics and actuator failures. The goal is to achieve desirable tracking performance with a simple and low-cost control strategy. By introducing a new form of parameter estimation error, together with an error transformation, a robust adaptive and fault-tolerant control scheme is developed without the need for fault information nor precise robotic mathematical model. It is shown that, with the proposed control, the tracking error is ensured to converge to an adjustable residual set within prescribed finite time at a user pre-assignable decay rate. The appealing feature of the developed control also lies in its simplicity in structure (i.e. PID form) and effectiveness in dealing with modelling uncertainties as well as actuation faults.     

T-S 模糊模型变结构的机器臂轨迹跟踪控制

针对不确定性的机械臂轨迹跟踪问题,结合滑模变结构和T-S模糊模型的优点,给出一种基于T-S模糊模型的变结构轨迹跟踪的方法。首先采用T-S模型建模,得到机械臂的模糊模型;然后设计出保证机械臂全局渐近稳定的滑模控制器。仿真结果表明,所设计的模糊变结构控制器与普通变结构控制器相比,可使机械臂无论在计算时间、误差上都具有更大的优势和更强的鲁棒性。     

轮式移动机械臂的鲁棒跟踪控制研究

移动机械臂系统一般由移动平台和机器臂组成,它既具有机器臂的操作灵活性,又具有移动机器人的可移动性,因此其应用范围要比单个系统宽得多。这篇文章研究了由非完整移动平台和完整机械臂构成的移动机械臂系统的鲁棒跟踪控制问题,基于误差动态方程和耗散不等式引理设计了一种鲁棒跟踪控制器,该控制器在出现外界干扰时能使系统渐近跟踪给定信号。使用Matlab6.5对系统进行了仿真研究,仿真结果表明所提出的鲁棒控制算法是正确有效的。     

基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统设计

为了保证机器人能够在保持稳定的情况下,按照规划轨迹执行工作任务,从硬件和软件两个方面,设计了基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统。装设机器人传感器与状态观测器,改装机器人鲁棒滑模跟踪控制器,完成系统硬件设计;综合机器人结构、运动机理和动力机制3个方面,构建机器人数学模型;根据状态数据采集结果与规划轨迹之间的偏差,计算机器人跟踪控制量;依据滑模运动与切换方程,利用Sigmoid函数生成机器人鲁棒滑模控制律,将生成控制指令作用在机器人执行元件上,实现系统的鲁棒滑模跟踪控制功能;在系统测试与分析中,所设计控制系统的平均位置跟踪控制误差为0.93 mm,与设定轨迹目标基本重合,机器人姿态角跟踪控制误差为0.06 mm,具有较好的鲁棒滑模跟踪控制效果,能够有效提高机器人鲁棒滑模跟踪控制精度。     

Robust adaptive uniform exact tracking control for uncertain Euler–Lagrange system

This paper offers a solution to the robust adaptive uniform exact tracking control for uncertain nonlinear Euler–Lagrange (EL) system. An adaptive finite-time tracking control algorithm is designed by proposing a novel nonsingular integral terminal sliding-mode surface. Moreover, a new adaptive parameter tuning law is also developed by making good use of the system tracking errors and the adaptive parameter estimation errors. Thus, both the trajectory tracking and the parameter estimation can be achieved in a guaranteed time adjusted arbitrarily based on practical demands, simultaneously. Additionally, the control result for the EL system proposed in this paper can be extended to high-order nonlinear systems easily. Finally, a test-bed 2-DOF robot arm is set-up to demonstrate the performance of the new control algorithm.     

On adaptive trajectory tracking of a robot manipulator usinginversion of its neural emulator

This paper is concerned with the design of a neuro-adaptive trajectory tracking controller. The paper presents a new control scheme based on inversion of a feedforward neural model of a robot arm. The proposed control scheme requires two modules. The first module consists of an appropriate feedforward neural model of forward dynamics of the robot arm that continuously accounts for the changes in the robot dynamics. The second module implements an efficient network inversion algorithm that computes the control action by inverting the neural model. In this paper, a new extended Kalman filter (EKF) based network inversion scheme is proposed. The scheme is evaluated through comparison with two other schemes of network inversion: gradient search in input space and Lyapunov function approach. Using these three inversion schemes the proposed controller was implemented for trajectory tracking control of a two-link manipulator. Simulation results in all cases confirm the efficacy of control input prediction using network inversion. Comparison of the inversion algorithms in terms of tracking accuracy showed the superior performance of the EKF based inversion scheme over others.     

Constrained dynamical systems,robust model reference adaptive control,and unreliable reference signals

ABSTRACT

In this paper, we address the robust control design problem for nonlinear dynamical systems tracking unreliable reference signals. Specifically, we present robust model reference adaptive control laws that guarantee uniform ultimate boundedness of the trajectory tracking error for nonlinear plants that are affected by matched, unmatched, and parametric uncertainties, and are subject to constraints on the state space and the measured output. These control laws guarantee satisfactory results even in case the reference trajectory or the reference output signal do not verify the given constraints and hence, may draw the plant's trajectory or measured output outside their constraint sets. A numerical example involving the attitude control of a spacecraft illustrates the feasibility of the theoretical results presented.     

State Space Constrained Iterative Learning Control for Robotic Manipulators

Real‐life work operations of industrial robotic manipulators are performed within a constrained state space. Such operations most often require accurate planning and tracking a desired trajectory, where all the characteristics of the dynamic model are taken into consideration. This paper presents a general method and an efficient computational procedure for path planning with respect to state space constraints. Given a dynamic model of a robotic manipulator, the proposed solution takes into consideration the influence of all imprecisely measured model parameters, making use of iterative learning control (ILC). A major advantage of this solution is that it resolves the well‐known problem of interrupting the learning procedure due to a high transient tracking error or when the desired trajectory is planned closely to the state space boundaries. The numerical procedure elaborated here computes the robot arm motion to accurately track a desired trajectory in a constrained state space taking into consideration all the dynamic characteristics that influence the motion. Simulation results with a typical industrial robot arm demonstrate the robustness of the numerical procedure. In particular, the results extend the applicability of ILC in robot motion control and provide a means for improving the overall trajectory tracking performance of most robotic systems.     

Robust Tracking Control of a Quadrotor Helicopter

In this paper, a robust tracking control method for automatic take-off, trajectory tracking, and landing of a quadrotor helicopter is presented. The designed controller includes two parts: a position controller and an attitude controller. The position controller is designed by the static feedback control method to track the desired trajectory of the altitude and produce the desired angles for pitch and roll angles. By combining the proportional-derivative (PD) control method and the robust compensating technique, the attitude controller is designed to track the desired pitch and roll angles and stabilize the yaw angle. It is proven that the attitude tracking error of each channel can converge to the given neighborhood of the origin ultimately. Experimental results demonstrate the effectiveness of the designed control method.