Energy-Saving and Punctuality Combined Velocity Planning for the Autonomous-Rail Rapid Tram with Enhanced Pseudospectral Method

Autonomous-rail rapid transit(ART)is a new medium-capacity rapid transportation system with punctuality,comfort and convenience,but low-cost construction.Combined velocity planning is a critical approach to meet the requirements of energy-saving and punctuality.An ART velocity pre-planning and re-planning strategy based on the combination of punctuality dynamic programming(PDP)and pseudospectral(PS)method is proposed in this paper.Firstly,the longitudinal dynamics model of ART is established by a multi-particle model.Secondly,the PDP algorithm with global optimal characteristics is adopted as the pre-planning strategy.A model for determining the number of collocation points of the real-time PS method is proposed to improve the energy-saving effect while ensuring computation efficiency.Then the enhanced PS method is utilized to design the velocity re-planning strategy.Finally,simulations are conducted in the typical scenario with sloping roads,traffic lights,and intrusion of the pedestrian.The simulation results indicate that the ART with the proposed velocity trajectory optimization strategy can meet the punctuality requirement,and obtain better economy efficiency compared with the punctuality green light optimal speed advisory(PGLOSA).

Tracking Control for a Cushion Robot Based on Fuzzy Path Planning With Safe Angular Velocity

This study proposes a new nonlinear tracking control method with safe angular velocity constraints for a cushion robot. A fuzzy path planning algorithm is investigated and a realtime desired motion path of obstacle avoidance is obtained. The angular velocity is constrained by the controller, so the planned path guarantees the safety of users. According to Lyapunov theory, the controller is designed to maintain stability in terms of solutions of linear matrix inequalities and the controller's performance with safe angular velocity constraints is derived.The simulation and experiment results confirm the effectiveness of the proposed method and verify that the angular velocity of the cushion robot provided safe motion with obstacle avoidance.

Velocity Constraints Based Approach for Online Trajectory Planning of High‑Speed Parallel Robots

High-speed parallel robots have been extensively utilized in the light industry.However,the influence of the nonlinear dynamic characteristics of high-speed parallel robots on system’s dynamic response and stable operation cannot be ignored during the high-speed reciprocating motion.Thus,trajectory planning is essential for efficiency and stability from pick-and-place(PAP)actions.This paper presents a method for planning the equal-height pick-and-place trajectory considering velocity constraints to improve the PAP efficiency and stability of high-speed parallel robots.The velocity constraints in the start-and-end points can reduce vibration from picking and placing,making the trajectory more suitable to complex beltline situations.Based on velocity constraints,trajectory optimization includes trajectory smoothness and joint torque to optimize cycle time is carried out.This paper proposes an online trajectory optimization solution.By using back propagation(BP)neural networks,the solution is simplified and can be solved in real-time.Simulation and experiments were carried out on the SR4 parallel robot.The results show that the proposed method improves the efficiency,smoothness,and stability of the robot.This paper proposes an online trajectory planning method which is velocity constraints based and can improve the efficiency and stability of high-speed parallel robots.The work of this research is conducive to finely applying high-speed parallel robots.

Temperature Rise Calculation and Velocity Planning of Permanent Magnet Linear Synchronous Motor under Trapezoidal Speed

For permanent magnet linear synchronous motor(PMLSM) working at trapezoidal speed for long time, high thrust brings high temperature rise, while low thrust limits dynamic performance. Thus, it is crucial to find a balance between temperature rise and dynamic performance. In this paper, a velocity planning model of the PMLSM at trapezoidal speed based on electromagnetic-fluid-thermal(EFT) field is proposed to obtain the optimal dynamic performance under temperature limitation. In this model, the winding loss is calculated considering the acceleration and deceleration time. The loss model is indirectly verified by the temperature rise experiment of an annular winding sample. The actual working conditions of the PMLSM are simulated by dynamic grid technology to research the influence of acceleration and deceleration on fluid flow in the air gap, and the variation rule of the thermal boundary condition is analyzed. Combined with the above conditions, the temperature rise of a coreless PMLSM(CPMLSM) under the rated working condition is calculated and analyzed in detail. Through this method and several iterations, the optimal dynamic performance under the temperature limitation is achieved. The result is verified by a comparison between simulation and prototype tests, which can help improve the dynamic performance.

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution,few combine the connected vehicle technologies into braking velocity planning.If the braking intention is accessed by the vehicle-to-everything communication,the electric vehicles(EVs)could plan the braking velocity for recovering more vehicle kinetic energy.Therefore,this paper presents an energy-optimal braking strategy(EOBS)to improve the energy efficiency of EVs with the consideration of shared braking intention.First,a double-layer control scheme is formulated.In the upper-layer,an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm,which could derive the energy-optimal braking trajectory.In the lower-layer,the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system,then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety.Several simulations are conducted by jointing MATLAB and CarSim,the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy.Finally,the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration,battery charging power,and motor efficiency,which could be a guide to real-time control.

Corner Transition Toolpath Generation Based on Velocity-Blending Algorithm for Glass Edge Grinding

Sharp corners usually are used on glass contours to meet the highly increasing demand for personalized products,but they result in a broken wheel center toolpath in edge grinding.To ensure that the whole wheel center toolpath is of G1 continuity and that the grinding depth is controllable at the corners,a transition toolpath generation method based on a velocity-blending algorithm is proposed.Taking the grinding depth into consideration,the sharp-corner grinding process is planned,and a velocity-blending algorithm is introduced.With the constraints,such as traverse displacement and grinding depth,the sharp-corner transition toolpath is generated with a three-phase motion arrangement and with confirmations of the acceleration/deceleration positions.A piece of glass with three sharp corners is ground on a three-axis numerical-control glass grinding equipment.The experimental results demonstrate that the proposed algorithm can protect the sharp corners from breakage efficiently and achieve satisfactory shape accuracy.This research proposed a toolpath generation method based on a velocity-blending algorithm for the manufacturing of personalized glass products,which generates the transition toolpath as needed around a sharp corner in real time.

Trajectory Planning of High Precision Collaborative Robots

In order to satisfy the high efficiency and high precision of collaborative robots,this work presents a novel trajectory planning method.First,in Cartesian space,a novel velocity look-ahead control algorithm and a cubic polynomial are combined to construct the end-effector trajectory of robots.Then,the joint trajectories can be obtained through the inverse kinematics.In order to improve the smoothness and stability in joint space,the joint trajectories are further adjusted based on the velocity look-ahead control algorithm and quintic B-spline.Finally,the proposed trajectory planning method is tested on a 4-DOF serial collaborative robot.The experimental results indicate that the collaborative robot achieves the high efficiency and high precision,which validates the effectiveness of the proposed method.

Quadratic Programming-based Approach for Autonomous Vehicle Path Planning in Space

Path planning for space vehicles is still a challenging problem although considerable progress has been made over the past decades.The major difficulties are that most of existing methods only adapt to static environment instead of dynamic one,and also can not solve the inherent constraints arising from the robot body and the exterior environment.To address these difficulties,this research aims to provide a feasible trajectory based on quadratic programming（QP） for path planning in three-dimensional space where an autonomous vehicle is requested to pursue a target while avoiding static or dynamic obstacles.First,the objective function is derived from the pursuit task which is defined in terms of the relative distance to the target,as well as the angle between the velocity and the position in the relative velocity coordinates（RVCs）.The optimization is in quadratic polynomial form according to QP formulation.Then,the avoidance task is modeled with linear constraints in RVCs.Some other constraints,such as kinematics,dynamics,and sensor range,are included.Last,simulations with typical multiple obstacles are carried out,including in static and dynamic environments and one of human-in-the-loop.The results indicate that the optimal trajectories of the autonomous robot in three-dimensional space satisfy the required performances.Therefore,the QP model proposed in this paper not only adapts to dynamic environment with uncertainty,but also can satisfy all kinds of constraints,and it provides an efficient approach to solve the problems of path planning in three-dimensional space.

智能采煤机器人关键技术

采煤机是综采工作面的核心装备,研发智能采煤机器人是实现综采工作面智能化的关键。综合分析当前采煤机机器人化研究进程中的传感检测、位姿控制、速度控制、截割轨迹规划与跟踪控制等技术的研究现状,提出研发智能采煤机器人必须破解的“智能感知、位姿控制、速度控制、截割轨迹规划与跟踪控制、位-姿-速协同控制”五大关键技术,并给出解决方案。针对智能感知问题,提出了构建智能感知系统思路,给出了智能采煤机器人智能感知系统的架构,实现对运行状态、位姿、环境等全面感知,为智能采煤机器人安全、可靠运行提供保障;针对位姿控制问题,提出了智能PID位姿控制思路,给出了改进遗传算法的PID位姿控制方法,实现了智能采煤机器人位姿精准控制;针对速度控制问题,提出了融合“力-电”异构数据的截割载荷测量思路,给出了基于神经网络算法的截割载荷测量方法,实现了截割载荷的精准测量;提出牵引与截割速度自适应控制思路,给出了人工智能算法牵引与截割速度决策方法和滑模自抗扰控制的牵引与截割速度控制方法,实现了智能采煤机器人速度精准自适应控制;针对截割轨迹规划与跟踪控制问题,提出了截割轨迹精准规划思路,给出了融合地质数据和历史截割数据的截割轨迹规划模型,实现了截割轨迹的精准规划;提出了截割轨迹精准跟踪控制思路,给出了智能插补算法的截割轨迹跟踪控制方法,实现了智能采煤机器人截割轨迹高精度规划与精准跟踪控制;针对“位-姿-速”协同控制问题,提出了“位-姿-速”协同控制参数智能优化思路,给出了基于多系统互约束的改进粒子群“位-姿-速”协同控制参数优化方法,实现了智能采煤机器人智能高效作业。深入研究五大关键技术破解思路,有利于加快推动研发高性能、高效率、高可靠的智能采煤机器人。

矿用无人运输车辆精准停靠控制算法

以无人驾驶矿用运输车为平台,开展精准停靠控制试验研究。为尽可能精确地到达期望停靠位置,首先设计距离-速度规划方案,在此基础上提出1种前馈加反馈的执行器开度控制算法;其次,在底层控制中考虑加速度补偿项,并对制动切换逻辑进行优化;最后进行仿真测试和实车试验,通过测试纠正控制参数,避免掉烦琐的系统参数辨识。结果表明:采用精准停靠策略能降低干扰引起的速度波动,优化底层控制逻辑,有效提高停靠精度。

一种液压挖掘机最优能耗的轨迹规划方法

为了降低液压挖掘机的运动能量消耗,实现各关节的合理有效作业,提出了基于T型速度曲线的关节插值方法,以实现液压挖掘机最优能耗轨迹规划。该方法将各关节的速度设定为匀加速、匀速和匀减速的形式以保证液压挖掘机在作业过程中的平稳性,以关节角度、角速度和角加速度为约束条件,利用改进的自适应遗传算法优化求解各关节的匀加(减)速和匀速运动时间,获得了各关节最优运动曲线,实现了液压挖掘机最优能耗轨迹规划。对基于T型速度曲线的插值规划方法进行仿真实验,并在相同条件下与四次多项式插值结果进行了对比。结果表明,该方法规划的轨迹能耗低,避免了各关节产生不必要的运动,有效减少了摩擦损耗,使得挖掘机可平稳、低能耗地完成作业。

一种S型加减速组合的速度规划算法

针对传统NURBS曲线插补S型加减速的改进难以在加工柔性和加工效率上同时兼顾的问题,提出一种将多种S型加减速组合的速度规划算法。选取分别在加工柔性和加工效率上单独改进的两种S型加减速,并设计了一种兼顾柔性和效率的新改进S型加减速。在速度规划中,根据简化后的4种加减速形式,灵活组合这3种S型加减速,并采取合并曲线分段的速度平滑方式,减少了曲线段间的速度波动。仿真结果表明:该算法能在提高加工效率的同时满足加加速度的连续,最终实现加工柔性和加工效率的兼得。

基于HGS-IDWA算法的机器人路径规划研究

针对机器人路径规划问题,提出了融合饥饿游戏搜索(HGS)算法和改进动态窗口(IDWA)算法的优化思路。首先,利用HGS算法进行静态规划;其次,在动态规划阶段,针对传统DWA算法的路径选择不合理问题,引入新的目标函数以优化接近目标时的速度选择,在速度函数中加入障碍物数量以提升动态规划效率;最后,通过案例仿真与实地测试,分析机器人在规避动态障碍时获得的最佳路径。

针对移动平台的无人机自主降落的新型速度规划方法

针对现有的无人机降落存在过激的加速、减速以及反向飞行和多次振荡的问题,进行了无人机自主降落于移动平台过程中的速度规划方法研究,提出了一种基于移动平台梯度和风险权重的自主降落速度规划方法。仿真实验表明,与Fast-perching降落方法相比,所提方法减少了过激的加速、减速和振荡次数,避免了反向飞行,且降落时间效率提高了30.76%,水平方向降落效率提高了26.47%,垂直方向降落效率提高了37.5%,为无人机自主降落到移动平台速度规划问题提供了一种有效的解决方案,具有一定的工程实用价值。

6-UCU并联机器人轨迹规划研究

针对并联机器人笛卡尔空间内位姿插补的轨迹规划问题,设计了一种基于S型速度曲线的笛卡尔空间直线、圆弧与四元数相结合的位姿插补算法.归纳了采用数值法求解6-UCU并联机器人反解的计算步骤,分别对直线、圆弧的位置插补以及基于四元数的姿态插补进行数学推导;分析了7段S型的速度策略,并利用归一化时间算子的方式求出了位置插补与姿态插补相结合的齐次变换矩阵;通过Simulink进行仿真验证.结果表明:该算法可以成功被应用在并联机器人上,运用该算法的并联机器人动平台的几何中心点速度、加速度均满足S型加减速变化规律.该算法能够降低对并联机器人末端执行器的机械柔性冲击.

基于优化的离散空间轨迹规划算法

针对无人车离散空间轨迹规划时存在路径不平滑、速度不平稳、动态规划运算时间长等问题,提出一种基于优化的离散空间轨迹规划算法。将无人车所需搜索的空间解耦为纵向-横向空间(S-L空间)和纵向-时间空间(S-T空间),在S-L空间根据静态避障和路径平滑程度的要求设计代价函数进行动态规划,进而利用二次规划对动态规划结果进行优化;在S-T空间提出一种改进的动态规划方法,根据道路速度限制和不可倒车约束优化搜索,并引入启发函数加快对规划终点的搜索速度,减少算法计算量,提高运行效率。仿真实验结果表明,在静态避障和动态避障环境中,所提算法规划出的轨迹曲率更小、速度变化更平滑、运行时间更快,相比于传统动态规划算法单次规划时间减少了77.13%。

无级变速拖拉机跃度最优化调速控制

针对无人驾驶拖拉机加减速导致的作业平稳性低和燃油经济性差等问题,该研究基于CVT(constantly variable transmission,无级变速传动)拖拉机,设计了一种基于贝尔曼最优性原理的最小跃度多项式局部速度规划算法。基于贝尔曼最优性原理和最优控制思想设计全局规划目标、局部规划目标及约束,提出基于最小跃度多项式的局部速度规划算法并开发速度跟随控制系统。田间试验表明,相对于无最优化调速技术的对照组,U型掉头的速度误差平均值和均方根分别降低42.31%和50.75%,加速度平均值与方差分别降低8.26%和16.36%,跃度平均值与方差分别降低7.65%和14.23%,发动机转速方差降低63.36%,发动机扭矩百分比方差降低60.26%,瞬时油耗方差降低71.25%,总油耗降低2.37%。直线行驶调速效果呈现相同趋势,与对照组相比,速度误差平均值和均方根分别降低9.45%和11.14%,加速度平均值与方差分别降低6.03%和13.68%。跃度平均值和均方根分别降低1.55%和3.59%。发动机转速方差降低31.78%,发动机扭矩百分比方差降低25.13%,瞬时油耗方差降低31.82%,总油耗降低2.48%。所提方法满足无级变速拖拉机无人驾驶速度平稳切换需要,并提高了燃油经济性。

利用CNC多维约束的S型速度规划

经典控制模型中存在时间过耦合,而速度规划与实时轨迹控制都与时间关联,导致实时计算量、规划与控制协调性等不足的问题,提出利用CNC多维约束的S型速度规划方法.首先建立双重反馈的控制模型,内反馈继承经典控制模型将时间反馈到控制器,外反馈将非时间反馈到规划器;然后将影响速度规划的因素分为时间相关与时间无关,与时间相关因素在控制器中实时控制,与时间无关因素在规划器中进行非时间速度规划;在规划器中建立基于轨迹路径长度、轨迹几何特性、运动参数以及程序行号等信息的多维约束模型;最后以路径长度代替时间作为运动参考量,结合多维约束模型,考虑轨迹的几何特性与路径长度映射关系,使轨迹特性与非时间建立具有空间性关联.通过MATLAB仿真对控制模型的抗干扰能力进行验证,并通过CODESYS软件编程和实验的结果表明,所提方法是可行和有效的.

融合改进动态窗口法与速度障碍法的无人船局部路径规划

为解决传统动态窗口法未考虑无人船的运动特性,规划路径绕行于障碍物稠密区外围,路程偏长,且与动态障碍物距离过近,动态避障效果不佳等缺点,提出融合改进动态窗口法与速度障碍法的无人船局部路径规划算法。首先,对于无人船的运动特性,在速度选择中考虑艏摇角速度及漂角的影响;其次,提出障碍物搜索角这一概念,更好地处理障碍物对无人船航行造成的影响,使得无人船可穿行于障碍物稠密区而不发生碰撞,且可大大缩短航行的路程与时间;最后,融合速度障碍法,并根据无人船与动态障碍物的相对速度提出新的动态窗口法评价函数,使得无人船在避碰安全的情况下以较快的速度避开动态障碍物。数值仿真结果表明,改进方法规划的路径曲折少、更平滑,有利于无人船的航行,在路径长度、航行时间与平均速度等方面均优于传统算法,并且具有更强的动态避障调节能力。

车路协同的插电式汽车预测能量管理策略研究

为进一步改善插电式混合动力汽车(plug-in hybrid electric vehicle,PHEV)的能量经济性,提出了一种考虑市区道路交通信息的经济车速规划方法及基于模型预测控制(model predictive control,MPC)的能量优化管理策略。以某款P2构型的PHEV为研究对象,基于市区路口信号灯配时状态信息,分别采用动态规划与高斯伪普法优化求解经济车速。根据规划出的经济车速,提出了基于MPC的优化能量管理策略,其利用Dijkstra算法求解最优转矩分配。结果表明:对比基于规则的分段三角函数法,2种经济车速规划算法分别可降低6.31%、7.03%的PHEV等效油耗。基于MPC的优化能量管理策略相比于基于规则的能量管理策略可进一步提升4.98%的能量经济性。