The Experts below are selected from a list of 1731 Experts worldwide ranked by ideXlab platform

Ming Liu - One of the best experts on this subject based on the ideXlab platform.

  • Self-learning interval type-2 fuzzy neural network controllers for trajectory control of a Delta parallel Robot
    Neurocomputing, 2018
    Co-Authors: Xingguo Lu, Yue Zhao, Ming Liu
    Abstract:

    This paper presents a self-learning interval type-2 fuzzy neural network (SLIT2FNN) control scheme for trajectory tracking problem of a Delta Robot. This intelligent control scheme is computationally efficient and can be easily applied to existing equipment. The controller has a parallel structure, which combines an interval type-2 fuzzy neural network (IT2FNN) controller and a traditional proportional-derivative (PD) controller. We use the PD controller to compensate the transient performance, and use the IT2FNN to learn the dynamic characteristics of the system. A novel arrangement of trapezoidal interval type-2 fuzzy membership functions (IT2MF) is proposed, the arrangement enables the adaptation laws to have an analytical form. A learning algorithm based on sliding mode control (SMC) theory is proposed for the parameter training of the IT2FNN system. The control algorithm learns from the feedback error online and tunes the parameters of the IT2FNN, and will become the main source of the control signal after several learning iterations. Unlike model-based control, this control method has no requirement of prior information and constraint conditions from the Robot plant. Lyapunov stability method is employed to prove asymptotic stability of the proposed approach. The structure of the SLIT2FNN and the operations in each layer are introduced in detail. The performance and robustness of the proposed controller is demonstrated on the Delta Robot trajectory tracking problems in the presence of structured and unstructured uncertainties. Simulation results illustrate that the proposed SLIT2FNN control approach produces higher trajectory tracking accuracy and more robust to uncertainties as compared to its counterparts.

  • design and optimization of interval type 2 fuzzy logic controller for Delta parallel Robot trajectory control
    International Journal of Fuzzy Systems, 2017
    Co-Authors: Ming Liu, Jianxing Liu
    Abstract:

    In the view of the problem of designing and optimization of interval type-2 fuzzy logic controller (IT2 FLC) for Delta Robot trajectory control, a systematic design method is put forward in this paper. A type-1 fuzzy logic controller (T1 FLC) is designed and optimized. Then, three kinds of method to blur the T1 fuzzy membership functions are proposed to generate IT2 fuzzy sets from the optimized T1 fuzzy sets. A systematic analysis is carried out to study the relationship between blur methods, blur degree and output control surface of IT2 FLC. Output signal enhance coefficient is proposed to make sure the IT2 FLC to provide enough output signal. The optimized IT2 FLC is validated through a set of simulations and by comparing against its type-1 counterpart in the presence of external and internal uncertainties. The simulation results show the optimized IT2 FLC can provide better trajectory tracking performance.

  • a fuzzy logic controller tuned with pso for Delta Robot trajectory control
    Conference of the Industrial Electronics Society, 2015
    Co-Authors: Ming Liu
    Abstract:

    In the view of the problem of tuning the parameters of the fuzzy logic controller (FLC) for Delta Robot trajectory control, a method is put forward to tune the parameters of membership functions and the gains of the controller with particle swarm optimization (PSO). A PSO with dynamic parameters is proposed which makes the PSO has better performance in global search and faster convergence. The fitness function of the PSO was designed by using the time domain indices and integral of time-weighted-squared-error (ITSE) to optimize the performance of the controller. The simulation results show that FLC tuned by PSO has better performance and more robust than the PSO tuned PID controller for the Delta Robot trajectory control.

Karol Miller - One of the best experts on this subject based on the ideXlab platform.

  • optimal kinematic design of spatial parallel manipulators application to linear Delta Robot
    Journal of Mechanical Design, 2003
    Co-Authors: Michael Stock, Karol Miller
    Abstract:

    An optimal kinematic design method suited for parallel manipulators is developed. The kinematic optimization process yields a design that delivers the best compromise between manipulability and a new performance index, space utilisation. It is shown that the exhaustive search minimization algorithm is effective for as many as four independent design variables and presents a viable alternative to advanced nonlinear programming methods. The proposed kinematic optimization method is applied to the Linear Delta: a three degree of freedom translational manipulator. The kinematics of the Linear Delta are solved via the polynomial method. The mobility, workspace and manipulability characteristics are examined. It is shown that the Linear Delta's manipulability generally exhibits relatively little variation when compared to space utilization. The tendency exists for the solution to converge on a zero workspace size architecture when manipulability is optimized alone. The inclusion of the space utilization index in the cost function is crucial for obtaining realistic design candidates.

  • Experimental verification of modeling of Delta Robot dynamics by direct application of Hamilton's principle
    Proceedings - IEEE International Conference on Robotics and Automation, 1995
    Co-Authors: Karol Miller
    Abstract:

    This contribution presents the experimental verification of the\nnewly developed Hamilton-based dynamic model of Delta direct drive\nparallel Robot by measurements of Delta Robot's motor torques. The\nstrain gage technology was applied. The experiment is in author's\nopinion the first ever for Robot Delta. The experimental results\nvalidate the modelling of Robot Delta as a system of rigid bodies,\nconnected by frictionless joints. The results obtained from the model\nbased on the direct application of Hamilton's principle in extended\nspace, taking into account the differences between real and desired\naccelerations, agreed with measurements to at least 5%. The motor torque\nmeasuring system may be in future used in force control of Delta Robot\n

Haojian Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Time-Optimal Trajectory Planning for Delta Robot Based on Quintic Pythagorean-Hodograph Curves
    IEEE Access, 2018
    Co-Authors: Tingting Su, Jun Zheng, Yunkuan Wang, Xu Liang, Long Cheng, Haojian Zhang
    Abstract:

    In this paper, a time-optimal trajectory planning method based on quintic PythagoreanHodograph (PH) curves is proposed to realize the smooth and stable high-speed operation of the Delta parallel Robot. The trajectory is determined by applying the quintic PH curves to the transition segments in the pick-and-place operation trajectory and the 3-4-5 polynomial motion law to the trajectory. The quintic PH curves are optimized to reduce the cycle time of the pick-and-place operation. In addition, a comparison between different trajectory planning methods has been implemented so as to observe the performance of the obtained results. The MATLAB simulation results reveal that compared with the trajectory planning based on vertical and horizontal motion superposition, the trajectory planning based on quintic PH curves is completed with a shorter motion cycle time and more stable motion performance, with the velocities, accelerations, and jerks in joint space bounded and continuous. Experiments carried out on the prototype also confirm that the trajectory planning based on quintic PH curves has a shorter cycle time, which is of great importance to high-speed operations of Delta parallel Robots.

  • Sorting system algorithms based on dynamic picking for Delta Robot
    2017 Seventh International Conference on Information Science and Technology (ICIST), 2017
    Co-Authors: Tingting Su, Jianzhang Chang, Hongsheng Sun, Haojian Zhang, Shaohong Wu, Jun Zheng, Yunkuan Wang, Shuhai Zhang
    Abstract:

    In this paper, different conditions of pick-and-place trajectory are analyzed, and on this basis, the dynamic picking algorithm for the workpieces on the conveyor belt is proposed by using the Ferrari's method. Then, the trajectory planning algorithm of sorting multiple types of workpieces is proposed by analyzing the trajectory planning model of two types of workpieces. The workpiece to be sorted is determined first, and then will be picked up at the picking point calculated by dynamic picking algorithm. Experiments show that the dynamic picking algorithm is accurate and fast; does not need to set the initial value and is suitable for practical engineering applications. And the algorithm of trajectory planning for multiple types of workpieces has high accuracy and stability.

Djamel Boukhetala - One of the best experts on this subject based on the ideXlab platform.

  • model free iterative learning control with nonrepetitive trajectories for second order mimo nonlinear systems application to a Delta Robot
    IEEE Transactions on Industrial Electronics, 2021
    Co-Authors: Chems Eddine Boudjedir, Mohamed Bouri, Djamel Boukhetala
    Abstract:

    A model-free iterative learning control strategy (ILC) in nonrepetitive trajectories, applied to Robotic manipulators is presented in this article. The development of this ILC controller is derived in general case for second-order nonlinear multi-input multi-output (MIMO) systems subjected to external disturbances. Unlike most of the ILC implementations in the literature, which considers both the resetting condition and periodic trajectories; the proposed ILC controller is model-free and works under the practical alignment condition and noncyclic desired trajectories. Furthermore, these trajectories may vary in magnitude and in the starting and terminal points. The Lyapunov stability approach is combined with a time scale transformation to synthesize the control law. The asymptotic convergence of both the position and velocity tracking errors are demonstrated along the iteration axis. Finally, experimental results in pick and place operations of a parallel Delta Robot are presented and discussed. These results are very effective and clearly point out the high potential of the developed model-free ILC technique for industrial Robotic applications.

  • nonlinear pd control of a parallel Delta Robot expermentals results
    International Conference on Electrical Sciences and Technologies in Maghreb, 2018
    Co-Authors: Chems Eddine Boudjedir, Djamel Boukhetala, Mohamed Bouri
    Abstract:

    In this paper, a nonlinear proportional derivative control (NPD) is proposed to solve the trajectory tracking problem of a parallel Delta Robot. In order to handle the strong coupling effect and external disturbances as well as to realise high-precision trajectory tracking, the proportional and derivative gains are adapted through time using the tracking error and its time derivative respectively. Experiments are carried out on the parallel Delta-4 Robot, and it is shown the effectiveness and the superiority of the NPD controller over the fixed gains PD controller.

Tingting Su - One of the best experts on this subject based on the ideXlab platform.

  • Time-Optimal Trajectory Planning for Delta Robot Based on Quintic Pythagorean-Hodograph Curves
    IEEE Access, 2018
    Co-Authors: Tingting Su, Jun Zheng, Yunkuan Wang, Xu Liang, Long Cheng, Haojian Zhang
    Abstract:

    In this paper, a time-optimal trajectory planning method based on quintic PythagoreanHodograph (PH) curves is proposed to realize the smooth and stable high-speed operation of the Delta parallel Robot. The trajectory is determined by applying the quintic PH curves to the transition segments in the pick-and-place operation trajectory and the 3-4-5 polynomial motion law to the trajectory. The quintic PH curves are optimized to reduce the cycle time of the pick-and-place operation. In addition, a comparison between different trajectory planning methods has been implemented so as to observe the performance of the obtained results. The MATLAB simulation results reveal that compared with the trajectory planning based on vertical and horizontal motion superposition, the trajectory planning based on quintic PH curves is completed with a shorter motion cycle time and more stable motion performance, with the velocities, accelerations, and jerks in joint space bounded and continuous. Experiments carried out on the prototype also confirm that the trajectory planning based on quintic PH curves has a shorter cycle time, which is of great importance to high-speed operations of Delta parallel Robots.

  • Sorting system algorithms based on dynamic picking for Delta Robot
    2017 Seventh International Conference on Information Science and Technology (ICIST), 2017
    Co-Authors: Tingting Su, Jianzhang Chang, Hongsheng Sun, Haojian Zhang, Shaohong Wu, Jun Zheng, Yunkuan Wang, Shuhai Zhang
    Abstract:

    In this paper, different conditions of pick-and-place trajectory are analyzed, and on this basis, the dynamic picking algorithm for the workpieces on the conveyor belt is proposed by using the Ferrari's method. Then, the trajectory planning algorithm of sorting multiple types of workpieces is proposed by analyzing the trajectory planning model of two types of workpieces. The workpiece to be sorted is determined first, and then will be picked up at the picking point calculated by dynamic picking algorithm. Experiments show that the dynamic picking algorithm is accurate and fast; does not need to set the initial value and is suitable for practical engineering applications. And the algorithm of trajectory planning for multiple types of workpieces has high accuracy and stability.