Guaranteed cost control of tracking problems with large plant uncertainty

A linear tracking problem with large plant uncertainty is studied. The guaranteed cost method is applied to design the controller so that the system responses follow the reference model. A modified Riccati matrix equation is obtained. From the numerical simulation of a second-order system, it is shown that the present method provides good performance in both tracking property and sensitivity immunity.     

含有参数不确定性的挠性航天器姿态跟踪滑模控制

对有不确定参数的挠性航天器姿态跟踪控制, 提出了一种基于滑模控制的姿态跟踪控制律. 挠性航天器动力学采用混合坐标法进行建模; 构造挠性模态观测器对挠性模态变量进行观测. 基于Lyapunov稳定性原理得到含有挠性模态观测器的滑模控制律, 并给出了全局渐近稳定性的证明. 对各个仿真结果进行比较, 显示出本文提出的滑模控制律针对航天器惯量阵不确定性具有良好的鲁棒性, 而且具有较强的扰动抑制能力.     

神经网络自适应滑模控制的不确定机器人轨迹跟踪控制

提出一种针对机器人跟踪控制的神经网络自适应滑模控制策略。该控制方案将神经网络的非线性映射能力与滑模变结构和自适应控制相结合。对于机器人中不确定项,通过RBF网络分别进行自适应补偿,并通过滑模变结构控制器和自适应控制器消除逼近误差。同时基于Lyapunov理论保证机器手轨迹跟踪误差渐进收敛于零。仿真结果表明了该方法的优越性和有效性。     

Reduction of the uncertainty in feature tracking

It is difficult to establish feature correspondences between distant viewpoints for panoramic images. For reliable navigation and development a human-like capability of interaction with the surrounding environment, we need a method of reduction of the uncertainty in feature tracking. To obtain a method of reduction of the uncertainty in feature tracking, we propose to use an algorithm for the problem of the longest common subsequence for a set of circular strings. We consider an explicit reduction from the problem of the longest common subsequence for a set of circular strings to the satisfiability problem. This reduction allows to obtain an efficient algorithm for finding the longest common subsequence for a set of circular strings. We present a general scheme of the method of reduction of the uncertainty in feature tracking. We considered the visual homing task to demonstrate the capabilities of our approach to solve the problem of reduction of the uncertainty in feature tracking. We present experimental results for the method of reduction of the uncertainty in feature tracking and novel robot visual homing methods.     

基于三步法的机械臂轨迹跟踪控制

考虑机械臂末端轨迹跟踪控制问题,以跟踪逆运动学求解出的末端期望轨迹对应的各关节期望角度为控制目标.设计了一种基于三步法的控制器,该控制器由类稳态控制、可变参考前馈控制和误差反馈控制3部分组成.证明了该控制器可以通过控制机械臂的各关节力矩实现各关节实际角度对期望角度的状态跟踪,进而使得末端轨迹渐近跟踪期望轨迹,并且跟踪误差是输入到状态稳定的.仿真表明基于三步法控制器的空间机械臂末端可以渐近跟踪期望轨迹,并且该算法可以克服系统的末端负载质量变化等不确定性的影响.     

On trajectory and force tracking control of constrained mobile manipulators with parameter uncertainty

This paper studies the trajectory and force tracking control problem of mobile manipulators subject to holonomic and nonholonomic constraints with unknown inertia parameters. Adaptive controllers are proposed based on a suitable reduced dynamic model, the defined reference signals and the mixed tracking errors. The proposed controllers not only ensure the entire state of the system to asymptotically converge to the desired trajectory but also ensure the constraint force to asymptotically converge to the desired force. A detailed numerical example is presented to illustrate the developed methods.     

Two trajectory tracking control methods for space hyper-redundant cable-driven robots considering model uncertainty

Multibody System Dynamics - Space hyper-redundant cable-driven robots (SHCDRs) have a slender body structure and high dexterity, which is very suitable for complex and limited unstructured space...     

A neural network assisted computed torque method for manipulator tracking control problems

Based on the structure of the computed torque method, this paper develops a neural control method for manipulator trajectory tracking problems. Compared with conventional approaches, the proposed method has the following novel features. First, by using a neural network as the plant model, the proposed method can handle structural as well as unstructural uncertainties. Secondly, with a simple compensation scheme, the proposed approach can effectively avoid tracking performance degradation caused by unmodelled dynamics and/or neural network learning errors. Computer simulation results are given to demonstrate the feasibility of the proposed control method.     

Deadbeat control system with time-varying uncertainty: Minimization of worst case steady-state tracking error

This paper poses and solves a new problem of the synthesis of a controller that minimizes the worst case steady-state controlled error in the presence of time-varying unstructured uncertainty. We present an easy, straightforward design method for obtaining a controller that minimizes the worst case steady-state controlled error under the assumption that the plant is strictly proper. The detailed contributions are as follows. First, we derive a new, simple expression for calculating the worst steady-state error, which gives useful and interesting suggestions about the controller design. We then show that the synthesis problem is reduced to a simple and tractable l1 -norm minimization problem. Therefore, this reduction provides a feasible method for solving the design problem of a controller that minimizes the worst case steadystate error. Second, a deadbeat tracking control problem is considered and a straightforward design method is presented for obtaining a deadbeat controller with given settling steps both to guarantee robust stability and to minimize the worst case steady-state error. The proposed controller is easily obtained by solving a simple linear programming problem. Finally, we show that the proposed controller minimizes the maximum error bound of the controlled output to persistent bounded disturbance.     

Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic

Many robot controllers require not only joint position measurements but also joint velocity measurements; however, most robotic systems are only equipped with joint position measurement devices. In this paper, a new output feedback tracking control approach is developed for the robot manipulators with model uncertainty. The approach suggested herein does not require velocity measurements and employs the adaptive fuzzy logic. The adaptive fuzzy logic allows us to approximate uncertain and nonlinear robot dynamics. Only one fuzzy system is used to implement the observer-controller structure of the output feedback robot system. It is shown in a rigorous manner that all the signals in a closed loop composed of a robot, an observer, and a controller are uniformly ultimately bounded. Finally, computer simulation results on three-link robot manipulators are presented to show the results which indicate good position tracking performance and robustness against payload uncertainty and external disturbances.     

A neural network-based method for tracking features from satellitesensor images

A new approach for feature tracking on sequential satellite sensor images using neural networks has been developed. The method defines the correspondence problem between features as the minimization of a cost function using a Hopfield neural network. It has been tested on Meteosat radiometer images by tracking a cloud with rotational movement and compared to the maximum cross-correlation method. The Hopfield net was found to be more accurate and faster.     

A robust adaptive tracking control method for a rehabilitative walker using random parameters

The present paper investigates stochastic modelling and a new nonlinear reliable tracking control method for a rehabilitative training walker. The stochastic model is constructed by considering random parameters. A new nonlinear tracking method against actuator fault is proposed based on redundant degree of freedom and a state feedback controller is designed by exploiting an adaptive control technique. It is proved that the mean square of the trajectory tracking error can be made arbitrarily small by choosing appropriate design parameters. As an application, simulation results confirm the effectiveness of the proposed method and verify that the walker with random parameters can provide safe sequential motion when one wheel actuator is at fault.     

一种摄像机变焦镜头焦距测量的新方法

为实现摄像系统小型化,提出了一种结合摄像机镜头自身结构,以发光二极管和光敏三极管构成光电传感器来检测镜头的焦距,实现了焦距自动测量的新方法。简述了测量原理,分析了系统的误差,同时,证明了该测量方法的可行性。测量系统满足了相对误差(短焦≤2%、长焦≤5%)的指标要求。     

Global tracking control of underactuated ships by Lyapunov's direct method

This paper studies the global tracking problem for an underactuated ship with only two propellers. Under sufficient conditions of persistent excitation, two constructive solutions are proposed by application of Lyapunov's direct method. Both solutions exploit the inherent cascade interconnected structure of the ship dynamics and generate explicit Lyapunov functions. A common feature of the second solution and the recent cascade approach of Lefeber (Tracking control of nonlinear mechanical systems, Ph.D. Thesis, University of Twente, 2000) is that global exponential tracking is achieved, but at the expense of transient performance. Extension to unmeasured thruster dynamics is also considered. Simulation results validate the proposed tracking methodology.     

Trajectory tracking control of multirotors from modelling to experiments: A survey

International Journal of Control, Automation and Systems - Multirotors have received a great attention from researchers and the general public, as a platform on which various ideas can be easily...     

振镜激光跟踪系统的鲁棒复合控制方法

为提高振镜激光跟踪系统的跟踪性能,针对振镜系统在使用过程中存在不确定性的问题,设计了一种基于前馈与反馈的复合控制方法;该控制方法通过零相差跟踪控制器(ZPETC)提高了振镜系统的跟踪性能,并采用了加性分解输出器抑制由系统的不确定性所带来的干扰,然后再通过差分进化算法设计无超调PID控制器来补偿剩余误差;在振镜系统辨识的基础上进行Matlab仿真实验,给辨识模型加入扰动模拟系统参数摄动,通过比较不同控制器下系统的跟踪误差,验证各控制器的作用;仿真结果表明,组合控制器在跟踪过程中能有效降低系统不确定性带来的影响,确保振镜系统拥有良好的跟踪性能。     

移动机器人的免疫非时间参考路径跟踪控制

针对移动机器人非时间参考控制方法的不足之处,借鉴生物免疫反馈响应过程的调节规律,提出了移动机器人的免疫非时间参考路径跟踪控制方法。该方法既有不依时间规划调节输出控制的特性,而且充分考虑到机器人机械结构与电机力矩特性的要求,实现了在误差较大时对控制量的限幅;通过选取合适参数,还能减小系统的超调量,进一步改善整个控制系统的性能。对于动态事件,采用插入算法,提高机器人对动态环境适应能力,使控制方法更适宜实际应用。仿真与实物实验,验证了该方法的有效性。     

一种鲁棒的自适应带宽跟踪方法

在自适应带宽均值移动算法的基础上, 引入粒子滤波, 提出一种新的目标跟踪方法. 该方法通过更新带宽矩阵以适应目标尺度的变化; 采用加权和方法融合定位检测结果, 使跟踪不易陷入局部最优状态; 对粒子进行收敛采样, 维持粒子多样性, 减小累积误差; 提出一种目标扩展搜索策略, 用于目标丢失后重新搜索跟踪目标. 实验结果表明, 所提出的跟踪方法在复杂场景中表现出了较好的鲁棒性, 且跟踪轨迹平滑.

     

A message-array-based mechanism for tracking control effects in supervisory control software

Supervisory control is a very popular paradigm for computer-controlled systems. Knowledge and tracking the control effect of every control operation is crucial to the control tasks. In the paper, we present a message-array-based mechanism to track control effects in supervisory control software. A novel data type, message array, is designed to efficiently support this tracking mechanism. The operation algorithms, adding algorithm (AA), removing algorithm (RA), and scheduler algorithm (SA) are proposed to operate the tracking messages in message array, which forms the special first input X output (FIXO) strategy of message array. Automatically tracking, recording, and rolling back are the characteristics of our tracking mechanism. We implement this messagearray-based mechanism on the famous human machine interface (HMI) software platform-proficy iFix, and construct experiments to evaluate the performance of the mechanism in various cases. The results show our mechanism can be well satisfied with supervisory control software.