Planning Optimal Motions for a DELTA Parallel Robot

Afroun, Mohamed; Chettibi, Taha; Hanchi, S.

doi:10.1109/med.2006.328835

Cited by 14 publications

(3 citation statements)

References 7 publications

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“…In order to analyze the control performance of the designed robust PID controller in the time domain, a trajectory planning was implemented using the modified trapezoidal acceleration curve method, in which acceleration and jerk is small for pick-and-place task [28,29]. Table III shows the waypoints of the track for the control simulation of the Delta parallel robot.…”

Section: Simulation Resultsmentioning

confidence: 99%

Robust PID optimal tuning of a Delta parallel robot based on a hybrid optimization algorithm of particle swarm optimization and differential evolution

Pak¹,

Kong²,

Ri³

2022

Robotica

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In this paper, we propose an approach to tune optimal parameters of a robust PID controller by means of computed torque control (CTC) strategy for trajectory tracking of a Delta parallel robot, using a hybrid optimization algorithm of Particle Swarm Optimization (PSO) and differential evolution (DE). It differs from previous works that they propose robust PID controller parameters tuning based on conventional gradient-based optimization algorithms and apply them to process control. First, we reduce the tuning problem of a robust PID controller with CTC strategy satisfying requirements including robustness and disturbance attenuation to an optimization problem with nonlinear constraints by considering the nonlinear dynamic model of a Delta parallel robot. Second, we set up the design characteristics for the trajectory tracking of a Delta parallel robot. Then, we propose a robust PID controller in a way of obtaining the global optimization solution of the nonlinear optimization problem by running a PSO-DE hybrid optimization algorithm of finding the global optimal solution by maintaining the diversity of swarm during evolution based on the evolution of cognitive experience. Simulation and experimental results demonstrate that the proposed controller outperforms previous works with respect to robust performance and active disturbance attenuation when it is applied to tracking control of a Delta parallel robot.

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Section: Simulation Resultsmentioning

confidence: 99%

Robust PID optimal tuning of a Delta parallel robot based on a hybrid optimization algorithm of particle swarm optimization and differential evolution

Pak¹,

Kong²,

Ri³

2022

Robotica

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show abstract

“…Due to the closed kinematic structure, Delta robots present better performance in accuracy, rigidity and payload capacity over their serial counterparts. All these advantages make this robot a good platform in many areas of engineering [12–15]. However, the Delta robot system is a kind of nonlinear, strong coupling system with time-varying parameters, and traditional controllers cannot provide a satisfactory control performance.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design and Tuning of PID-Type Interval Type-2 Fuzzy Logic Controllers for Delta Parallel Robots

Liu

2016

International Journal of Advanced Robotic Systems

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In this work, we propose a new method for the optimal design and tuning of a Proportional-Integral-Derivative type (PID-type) interval type-2 fuzzy logic controller (IT2 FLC) for Delta parallel robot trajectory tracking control. The presented methodology starts with an optimal design problem of IT2 FLC. A group of IT2 FLCs are obtained by blurring the membership functions using a variable called blurring degree. By comparing the performance of the controllers, the optimal structure of IT2 FLC is obtained. Then, a multi-objective optimization problem is formulated to tune the scaling factors of the PID-type IT2 FLC. The Non-dominated Sorting Genetic Algorithm (NSGA-II) is adopted to solve the constrained nonlinear multi-objective optimization problem. Simulation results of the optimized controller are presented and discussed regarding application in the Delta parallel robot. The proposed method provides an effective way to design and tune the PID-type IT2 FLC with a desired control performance.

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“…The experimental results showed that the algorithm was capable of determining the required velocity profiles and corresponding actuator efforts in a computationally-efficient manner even in the case of highly complex dynamic constraints. Afroum et al [12] presented an approach for planning the trajectories of a 3-DOF DELTA parallel robot in which the operational coordinates of the moving platform were parameterized within the task space and the optimal solutions were derived using a sequential quadratic programming method. However, these studies only considered the single objective trajectory planning of PKMs.…”

Section: Introductionmentioning

confidence: 99%

Trajectory planning in parallel kinematic manipulators using a constrained multi-objective evolutionary algorithm

Chen

Pham

2011

Nonlinear Dyn

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Generating manipulator trajectories considering multiple objectives with kinematics and dynamics constraints is a non-trivial optimization. In this paper, a constrained multi-objective genetic algorithm (MOGA) based technique is proposed to address this problem for a general motor-driven parallel kinematic manipulator. The planning process is composed of searching for a motion ensuring the accomplishment of the assigned task, minimizing the traverse time, and expended energy subject to various constraints imposed by the associated kinematics and dynamics of the manipulator. This problem is treated via an adequate parametric path representation in the task space of the moving platform, and then the use of the constrained MOGA for solving the resulted nonlinear multi-objective optimization problem. Simulation results are presented for the trajectories of the parallel kinematic manipulator, and a subsequent comparison with the weighted sum method is also carried out.

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Planning Optimal Motions for a DELTA Parallel Robot

Cited by 14 publications

References 7 publications

Robust PID optimal tuning of a Delta parallel robot based on a hybrid optimization algorithm of particle swarm optimization and differential evolution

Robust PID optimal tuning of a Delta parallel robot based on a hybrid optimization algorithm of particle swarm optimization and differential evolution

Optimal Design and Tuning of PID-Type Interval Type-2 Fuzzy Logic Controllers for Delta Parallel Robots

Trajectory planning in parallel kinematic manipulators using a constrained multi-objective evolutionary algorithm

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