Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅰ)

Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Car-tesian space mainly through increasing the number of knots on the path and the number of the path′s segments, which results in the heavier online computational burden for the robot controller. Aiming at overcoming this drawback, the authors propose a new kind of real-time accurate hand path tracking and joint trajectory planning method. Through selecting some extra knots on the specified hand path by a certain rule and introducing a sinusoidal function to the joint displacement equation of each segment, this method can greatly raise the path tracking accuracy of robot′s hand and does not change the number of the path′s segments. It also does not increase markedly the computational burden of robot controller. The result of simulation indicates that this method is very effective, and has important value in increasing the application of industrial robots.

Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅱ)

Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Cartesian space mainly through increasing the number of knots on the path and the segments of the path. But, this method resulted in the heavier on line computational burden for the robot controller. In this paper, aiming at this drawback, the authors propose a new kind of real time accurate hand path tracking and joint trajectory planning method for robots. Through selecting some extra knots on the specified hand path by a certain rule, which enables the number of knots on each segment to increase from two to four, and through introducing a sinusoidal function and a cosinoidal function to the joint displacement equation of each segment, this method can raise the path tracking accuracy of robot′s hand greatly but does not increase the computational burden of robot controller markedly.

Real-Time Iterative Compensation Framework for Precision Mechatronic Motion Control Systems

With regard to precision/ultra-precision motion systems,it is important to achieve excellent tracking performance for various trajectory tracking tasks even under uncertain external disturbances.In this paper,to overcome the limitation of robustness to trajectory variations and external disturbances in offline feedforward compensation strategies such as iterative learning control(ILC),a novel real-time iterative compensation(RIC)control framework is proposed for precision motion systems without changing the inner closed-loop controller.Specifically,the RIC method can be divided into two parts,i.e.,accurate model prediction and real-time iterative compensation.An accurate prediction model considering lumped disturbances is firstly established to predict tracking errors at future sampling times.In light of predicted errors,a feedforward compensation term is developed to modify the following reference trajectory by real-time iterative calculation.Both the prediction and compen-sation processes are finished in a real-time motion control sampling period.The stability and convergence of the entire control system after real-time iterative compensation is analyzed for different conditions.Various simulation results consistently demonstrate that the proposed RIC framework possesses satisfactory dynamic regulation capability,which contributes to high tracking accuracy comparable to ILC or even better and strong robustness.

Application Research of an Intelligent Detection Algorithm for Vehicle Trajectory Route Deviation

In the vehicle trajectory application system, it is often necessary to detect whether the vehicle deviates from the specified route. Trajectory planning in the traditional route deviation detection is defined by the driver through the mobile phone navigation software, which plays a more auxiliary driving role. This paper presents a method of vehicle trajectory deviation detection. Firstly, the manager customizes the trajectory planning and then uses big data technologies to match the deviation between the trajectory planning and the vehicle trajectory. Finally, it achieves the supervisory function of the manager on the vehicle track route in real-time. The results show that this method could detect the vehicle trajectory deviation quickly and accurately, and has practical application value.

车辆轨迹模型预测控制器的算法研究

为提高无人驾驶汽车行驶控制中的跟踪精度和车辆稳定性,提出了一个改进的模型预测控制器(MPC)。首先,为解决高速转弯工况下轮胎侧偏刚度的强非线性特性导致的车辆失稳问题,建立了轮胎动态侧偏刚度估计器进行实时估计;在此基础上,利用改进粒子群算法对现有模型预测控制器的时域参数进行优化,以提高算法跟踪精度和稳定性;最后,为验证控制器的效果,选取合适的工况进行了联合仿真测试。结果表明,改进控制器在高速转弯的工况下,跟踪精度误差降为4.9%,横摆角误差降为2.6%,比传统模型预测控制器分别提高了67.8%和62.3%,比模糊控制算法优化的控制器分别提高了55.8%和58%。

Real-time predictive sliding mode control method for AGV with actuator delay

In this paper,a predictive sliding mode control method based on multi-sensor fusion is proposed to solve the problem of insufficient accuracy in trajectory tracking caused by actuator delay.The controller,based on the kinematics model,uses an inner and outer two-layer structure to achieve decoupling of position control and heading control.A reference positional change rate is introduced into the design of controller,making the automatic guided vehicle(AGV)capable of real-time predictive control ability.A stability analysis and a proof of predictive sliding mode control theory are provided.The experimental results show that the new control algorithm can improve the performance of the AGV controller by referring to the positional change rate,thereby improving the AGV operation without derailing.

筒型平台拖带偏航风险预警研究

为保障海上拖航安全、预防水上交通事故的发生,提出一种筒型平台拖带偏航风险预警方法。首先基于分离式操纵运动模型(MMG)和悬链线模型,构建3自由度筒型平台拖带系统运动模型,得到拖带系统运动状态;采用卡尔曼滤波算法构建拖带系统轨迹实时预测模型,实时预测拖带系统中拖船与筒型平台的运动轨迹;最后基于指标预警准则,建立拖带系统偏航风险预警模型,并根据拖航实际情况,确定预警的指标、条件、方式和流程。仿真试验结果表明,所提预警方法,能提前识别潜在偏航风险,发出警报,并结合实际拖航水域通航环境,给出相应的缓解和消除风险的措施,为船舶驾驶人员和海事管理人员提供操纵指导。

基于在线相位角辨识的改进落点预测修正算法

针对目前弹丸在实际飞行过程中,二维弹道修正引信修正指令离线补偿存在相位角偏移量估计误差问题,提出了基于在线相位角辨识的改进落点预测修正算法。采用导航位置信息估计当前时刻实时过载,根据当前时刻时间,对落点预测弹道存储的预测弹道过载信息进行插值,得到预测弹道此时弹丸过载信息,通过计算当前过载估计值与预测弹道理论解算值之间误差,结合实际测量得到的修正翼面滚转角信息,对修正指令补偿项相位角进行在线辨识。仿真结果表明:基于在线相位角辨识的改进落点预测修正算法能够根据弹丸实际飞行状态在线估计出修正指令相位角偏移量,与离线补偿算法相比,能够有效补偿弹丸飞行过程中由于射击、气象等条件扰动所带来的对修正指令相位角偏移量的影响,克服修正指令离线补偿存在相位角偏移量估计误差问题,弹丸对目标打击CEP提升至少25%。同时该算法实现简单,具有较好的工程可实现性。

缓动点目标检测技术中候选轨迹确定算法

本文讨论了低信噪比条件下缓动点目标检测技术中候选轨迹的确定算法。文章首先给出了计数积累和线性预测的一般方法，然后提出了一种基于计数积累、线性预测和轨迹约束的候选轨迹确定以及实现检测的算法，最后是算法性能分析。

Online Decision-Making and Control of Power System Stability Based on Super-Real-Time Simulation

During power grid cascading failure,the operating point changes frequently,resulting in a mismatch or inaccuracy of online pre-decision making emergency control strategy.To solve this problem,an online power system stability decisionmaking and control method based on super-real-time simulation is presented in this paper.A decision-making and control system is developed in which the three main operation modes,offline pre-decision-making,online pre-decision-making,and real-time control,are all coordinated.To verify the method,ADPSS(advanced digital power system simulator)is used to simulate a digital power grid with about 20,000 buses.The closed-loop operation of the digital power grid and the online decisionmaking and control system are implemented.Test results show that when online pre-decision making control strategies are mismatched,aided real-time control works well and can prevent power grid stability loss.

基于比例因子的改进落点预测修正算法

针对以前的落点预测修正算法由算法误差引起的落点散布圆概率误差偏大的问题,提出了基于比例因子的改进落点预测修正算法。该算法以经典落点预测修正算法为基础,取二维弹道修正引信每秒纵向与横向最大修正能力的比值为比例因子,改进引信控制滚转角的计算。该算法和以前的落点预测修正算法相比,充分考虑了二维弹道修正引信修正能力变化情况,提高了算法精度,从而减小由算法误差引起的落点散布圆概率误差。仿真结果表明,该算法有效减小了由算法误差引起的落点散布圆概率误差。

Model Checking Real-Time Value-Passing Systems

In this paper, to model check real-time value-passing systems, a formallanguage Timed Symbolic Transition Graph and a logic system named Timed Predicate μ-Calculus areproposed. An algorithm is presented which is local in that it generates and investigates thereachable state space in top-down fashion and maintains the partition for time evaluations as coarseas possible while on-the-fly instantiating data variables. It can deal with not only data variableswith finite value domain, but also the so called data independent variables with infinite valuedomain. To authors knowledge, this is the first algorithm for model checking timed systemscontaining value-passing features.

Scalable and Adaptive Joins for Tra jectory Data in Distributed Stream System

As a fundamental operation in LBS(location-based services),the trajectory similarity of moving objects has been extensively studied in recent years.However,due to the increasing volume of moving object trajectories and the demand of interactive query performance,the trajectory similarity queries are now required to be processed on massive datasets in a real-time manner.Existing work has proposed distributed or parallel solutions to enable large-scale trajectory similarity processing.However,those techniques cannot be directly adapted to the real-time scenario as it is likely to generate poor balancing performance when workload variance occurs on the incoming trajectory stream.In this paper,we propose a new workload partitioning framework,ART(Adaptive Framework for Real-Time Trajectory Similarity),which introduces practical algorithms to support dynamic workload assignment for RTTS(real-time trajectory similarity).Our proposal includes a processing model tailored for the RTTS scenario,a load balancing framework to maximize throughput,and an adaptive data partition manner designed to cut off unnecessary network cost.Based on this,our model can handle the large-scale trajectory similarity in an on-line scenario,which achieves scalability,effectiveness,and efficiency by a single shot.Empirical studies on synthetic data and real-world stream applications validate the usefulness of our proposal and prove the huge advantage of our approach over state-of-the-art solutions in the literature.