基于无模型自适应控制的自动泊车方案

提出一种基于无模型自适应控制的自动泊车方案.首先,通过车载传感器采集车周环境信息用于规划期望路径;然后,将自动泊车跟踪问题转化为预瞄偏差角跟踪问题,通过设计相应的无模型自适应控制算法实现自动泊车.该方案设计的优点是仅使用自动泊车过程中生成的前轮转角输入数据和预瞄偏差角输出数据,没有使用任何被控车辆的信息,因此可适用于不同车型. Matlab仿真以及与PID控制方案和Fuzzy控制方案的对比仿真结果验证了所提出方案的可行性.     

四轮转向车辆转向解耦的双点跟踪控制

针对四轮转向(4WS)无人车辆路径跟踪中的过约束问题, 本文提出一种前后轮转向解耦的双点跟踪控制策略. 建立4WS车辆单轨运动学模型, 约束前后轮转向角速度, 规划曲率连续的回旋曲线参考位姿序列, 将其解耦为前后轴中心的双点参考轨迹; 以前后轮中心点为控制点, 采用非线性反馈控制的预瞄方法分别获得转向控制率, 双点跟踪误差指数收敛于0. 仿真和实车验证结果表明, 所提出的双点跟踪控制策略横向误差标准差减少0.2 m, 横摆角误差标准差减小3.0?, 具有更大的前后轮转角控制域和较高的跟踪精度     

Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control

The core task of tracking control is to make the controlled plant track a desired trajectory. The traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps increases. In this paper, a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control problem. Unlike the regulator problem,the iterative value function of tracking control problem cannot be regarded as a ...     

Output tracking for nonlinear non-minimum phase systems with output delay and application to an F-16 jet fighter

In this article, output tracking for a class of nonlinear non-minimum phase systems with output delay is considered. By applying the first-order Padé approximation technique to deal with the time-delay function, the original control problem is reduced to the output-tracking problem of a new non-minimum phase system without delay. The bounded tracking profiles of the unstable internal dynamics in the new system are generated by using the nonlinear inversion-based method, and a complete sliding mode control scheme is proposed to stabilise the output-tracking error as well as the internal dynamics. Moreover, the proposed control scheme is applied to solve the flight-path angle tracking problem of an F-16 jet fighter.     

工作空间坐标下操作器的运动规划与控制

本文针对操作器的工作空间坐标下轨线跟踪,提出了直接利用跟踪误差进行规划和控制的设计方案.这一规划方案基于速度矢量的线性合成原理.同时借助于定义一个偏差超平面,利用滑动模控制的思想,将原非线性规划问题转化为线性规划问题,特别适用于具有冗余自由度的操作器,并且不再要求操作器参数、定位等非常精确;而这一控制方案将规划过程统一于控制器之中,直接对跟踪误差进行控制,可以得到更加优秀的外部品质.     

Dynamic control of a robot manipulator for high-performance conveyor tracking

A new robot control scheme for the specific application to conveyor tracking is presented. To improve the performance of conveyor tracking, the robot arm dynamics is incorporated into the control scheme. The tracking problem for the workpiece on a variable-speed conveyor is formulated as a stochastic optimal tracking problem with specified criteria. Dividing the conveyor speed into the nominal term and the perturbed term, a two-stage control strategy is employed to cope with the nonlinearity and uncertainty of the robot-conveyor system. Simulation results are given to verify the good tracking performance with fast cycle time and high accuracy obtained in a robotic workcell. © 1995 John Wiley & Sons, Inc.     

Tracking the visual focus of attention for a varying number of wandering people

We define and address the problem of finding the visual focus of attention for a varying number of wandering people (VFOA-W), determining where the people's movement is unconstrained. VFOA-W estimation is a new and important problem with mplications for behavior understanding and cognitive science, as well as real-world applications. One such application, which we present in this article, monitors the attention passers-by pay to an outdoor advertisement. Our approach to the VFOA-W problem proposes a multi-person tracking solution based on a dynamic Bayesian network that simultaneously infers the (variable) number of people in a scene, their body locations, their head locations, and their head pose. For efficient inference in the resulting large variable-dimensional state-space we propose a Reversible Jump Markov Chain Monte Carlo (RJMCMC) sampling scheme, as well as a novel global observation model which determines the number of people in the scene and localizes them. We propose a Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM)-based VFOA-W model which use head pose and location information to determine people's focus state. Our models are evaluated for tracking performance and ability to recognize people looking at an outdoor advertisement, with results indicating good performance on sequences where a moderate number of people pass in front of an advertisement.     

Multiple Lyapunov functions‐based adaptive neural network tracking control of uncertain switched nonlinear systems

In this paper, the problem of adaptive neural network (NN) tracking control of a class of switched strict‐feedback uncertain nonlinear systems is investigated by state‐feedback, in which the solvability of the problem of adaptive NN tracking control for individual subsystems is unnecessary. A multiple Lyapunov functions (MLFs)–based adaptive NN tracking control scheme is established by exploiting backstepping and the generalized MLFs approach. Moreover, based on the proposed scheme, adaptive NN controllers of all subsystems and a state‐dependent switching law simultaneously are constructed, which guarantee that all signals of the resulting closed‐loop system are semiglobally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. The scheme provided permits removal of a technical condition in which the adaptive NN tracking control problem for individual subsystems is solvable. Finally, the effectiveness of the design scheme proposed is shown by using two examples.     

Tracking Control of Multi-Agent Systems Using a Networked Predictive PID Tracking Scheme

With the rapid development of network technology and control technology, a networked multi-agent control system is a key direction of modern industrial control systems, such as industrial Internet systems. This paper studies the tracking control problem of networked multi-agent systems with communication constraints, where each agent has no information on the dynamics of other agents except their outputs. A networked predictive proportional integral derivative(PPID) tracking scheme is proposed t...     

An efficient continuous tracking system in real-time surveillance application

A tracking object must present a proper field of view (FOV) in a multiple active camera surveillance system; its clarity can facilitate smooth processing by the surveillance system before further processing, such as face recognition. However, when pan–tilt–zoom (PTZ) cameras are used, the tracking object can be brought into the FOV by adjusting its intrinsic parameters; consequently, selection of the best-performing camera is critical. Performance is determined by the relative positions of the camera and the tracking objects, image quality, lighting and how much of the front side of the object faces the camera. In a multi-camera surveillance system, both camera hand-off and camera assignment play an important role in automated and persistent tracking, which are typical surveillance requirements. This study investigates the use of automatic methods for tracking an object across cameras in a surveillance network using PTZ cameras. An automatic, efficient continuous tracking scheme is developed. The goal is to determine the decision criteria for hand-off using Sight Quality Indication (SQI) (which includes information on the position of the object and the proportion of the front of object faces the camera), and to perform the camera handoff task in a manner that optimizes the vision effect associated with monitoring. Experimental results reveal that the proposed algorithm can be efficiently executed, and the handoff method for feasible and continuously tracking active objects under real-time surveillance.     

A two-stage,two-level finite difference scheme for moving boundary problems

A two-stage, two-level finite difference scheme is devised which, after applying a coordinate transformation, requires only a single iteration of a modified Newton method to produce second-order approximations to the solution of nonlinear parabolic moving boundary problems. Numerical evidence of unconditional stability and second-order convergence (in space and time) to both the solution and the moving boundary is presented for two particular problems. The proposed scheme is expected to be competitive with most current ‘front tracking’ methods.     

Robust object tracking with occlusion handle

Occlusion is a major problem for object tracking algorithms, especially for subspace-based learning algorithms like PCA. In this paper, we introduce a novel incremental subspace (robust PCA)-based object tracking algorithm to deal with the occlusion problem. The three major contributions of our works are the introduction of robust PCA to object tracking literature, a robust PCA-based occlusion handling scheme and the revised incremental PCA algorithm. In order to handle the occlusion problem in the subspace learning algorithm framework, robust PCA algorithm is employed to select part of image pixels to compute coefficients rather than the whole image pixels as in traditional PCA algorithm, which can successfully avoid the occluded pixels and therefore obtain accurate tracking results. The occlusion handling scheme fully makes use of the merits of robust PCA and can avoid false updates in occlusion, clutter, noisy and other complex situations. Besides, the introduction of incremental PCA facilitates the subspace updating process and possesses several benefits compared with traditional R-SVD-based updating methods. The experiments show that our proposed algorithm is efficient and effective to cope with common object tracking tasks, especially with strong robustness due to the introduction of robust PCA.     

轮式移动机器人的数据驱动轨迹跟踪滑模约束控制

针对有输入饱和约束的轮式移动机器人(WMR)的轨迹跟踪问题,提出一种抗饱和无模型自适应积分终端滑模控制方案.该方案基于紧格式动态线性化技术,构建WMR系统的在线数据驱动模型.在积分终端滑模控制器设计过程中,引入动态抗饱和补偿器,以解决WMR系统轨迹跟踪过程中执行器饱和问题.控制器设计仅利用控制系统的输入输出数据,与WMR系统模型信息无关.因此,针对不同类型的WMR系统,该方案均可实现.最后,通过仿真实验将所提出的方法与PID方法的控制效果进行对比,仿真结果表明,所提出的控制算法的跟踪误差更小且响应速度更快.     

Active vision for controlling an electric wheelchair

Most of the electric wheelchairs available in the market are joystick-driven and therefore assume that the user is able to use his hand motion to steer the wheelchair. This does not apply to many users that are only capable of moving the head like quadriplegia patients. This paper presents a vision-based head motion tracking system to enable such patients of controlling the wheelchair. The novel approach that we suggest is to use active vision rather than passive to achieve head motion tracking. In active vision-based tracking, the camera is placed on the user’s head rather than in front of it. This makes tracking easier, more accurate and enhances the resolution. This is demonstrated theoretically and experimentally. The proposed tracking scheme is then used successfully to control our electric wheelchair to navigate in a real world environment.     

Approximate stochastic dynamic programming for sensor scheduling to track multiple targets

The problem of sensor scheduling is to select the number and combination of sensors to activate over time. The goal is usually to trade off tracking performance and sensor usage. We formulate a version of this problem involving multiple targets as a partially observable Markov decision process, and use this formulation to develop a nonmyopic sensor-scheduling scheme. Our scheme integrates sequential multisensor joint probabilistic data association and particle filtering for belief-state estimation, and use a simulation-based Q-value approximation method called completely observable rollout for decision making. We illustrate the effectiveness of our approach by an example with multiple sensors activated simultaneously to track multiple targets. We also explore the trade-off between tracking error and sensor cost using our nonmyopic scheme.     

不确定性系统的自适应鲁棒跟踪控制

针对存在未知干扰和未建模动态等不确定性的系统的自适应鲁棒跟踪控制问题进行了探讨.首选将l1优化控制器的有限拍设计方法结合给出了最优鲁棒稳态跟踪控制器的设计方法．然后利用集员辨识的思想,将名义模型的参数和未建模动态及干扰的大小作为未知参数,提出了一种递推参数估计方法.最后将上述研究结果结合起来提出了一种自适应鲁棒跟踪控制策略,证明了自适应算法的全局收敛性并给出了鲁棒跟踪性能指标的一下较紧的上界.与现有的结果相比,本文提出的自适应控制具有非保守的鲁棒稳定性,具有渐近最优的鲁棒跟踪性能.     

A front tracking method on unstructured grids

A numerical method is developed for tracking discontinuities which is integrated in a generalized finite-volume solution framework for systems of conservation laws on unstructured grids of arbitrary element type. The location, geometry and the movement of the discontinuities are described by a local level set method on a restricted, dynamic definition range. Special algorithms based on least square methods are developed for handling the transport and renormalization of the level set function within the restricted range. An additional error correction is employed to minimize topological errors of the tracked front geometry. The jump conditions at the front are updated by one-sided extrapolation which define the local front velocity and the Riemann problem. A flux separation concept enables the treatment of the discontinuity within the finite-volume concept. The front tracking method is demonstrated by a number of computational examples for shock wave problems.     

Neighborhood tracking for mobile ad hoc networks

In mobile ad hoc networks (MANETs), node mobility causes network topologies to change dynamically over time, which complicates such important tasks as broadcasting and routing. In a typical efficient localized approach, each node makes forwarding decisions based on a neighborhood local view constructed simply by collecting received “Hello” messages. That kind of neighborhood local view can become outdated and inconsistent, which induces a low-coverage problem for efficient broadcasting tasks and a low-delivery ratio problem for efficient routing tasks. In this paper, we propose a neighborhood tracking scheme to guarantee the accuracy of forwarding decisions. Based on historical location information, nodes predict the positions of neighbors when making a forwarding decision, and then construct an updated and consistent neighborhood local view to help derive more precise forwarding decisions. The inaccuracy factors of our scheme are also discussed and an accessory method is provided for possible usage. Simulation results illustrate the accuracy of our proposed tracking scheme. To verify the effectiveness of our scheme, we apply it to existing efficient broadcast algorithms. Simulation results indicate that our neighborhood tracking scheme can improve the protocols coverage ratio greatly.     

A multivariable MRAC scheme with application to a nonlinear aircraft model

This paper revisits the multivariable model reference adaptive control (MRAC) problem, by studying adaptive state feedback control for output tracking of multi-input multi-output (MIMO) systems. With such a control scheme, the plant-model matching conditions are much less restrictive than those for state tracking, while the controller has a simpler structure than that of an output feedback design. Such a control scheme is useful when the plant-model matching conditions for state tracking cannot be satisfied. A stable adaptive control scheme is developed based on LDS decomposition of the high-frequency gain matrix, which ensures closed-loop stability and asymptotic output tracking. A simulation study of a linearized lateral-directional dynamics model of a realistic nonlinear aircraft system model is conducted to demonstrate the scheme. This linear design based MRAC scheme is subsequently applied to a nonlinear aircraft system, and the results indicate that this linearization-based adaptive scheme can provide acceptable system performance for the nonlinear systems in a neighborhood of an operating point.     

Model reference output feedback fuzzy tracking control design for nonlinear discrete-time systems with time-delay

In this study, a model reference fuzzy tracking control design for nonlinear discrete-time systems with time-delay is introduced. First, the Takagi and Sugeno (TS) fuzzy model is employed to approximate a nonlinear discrete-time system with time-delay. Next, based on the fuzzy model, a fuzzy observer-based fuzzy controller is developed to reduce the tracking error as small as possible for all bounded reference inputs. The advantage of proposed tracking control design is that only a simple fuzzy observer-based controller is used in our approach without feedback linearization technique and complicated adaptive scheme. By the proposed method, the fuzzy tracking control design problem is parameterized in terms of a linear matrix inequality problem (LMIP). The LMIP can be efficiently solved using the convex optimization techniques. Simulation example is given to illustrate the design procedures and tracking performance of the proposed method.