Abstract
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.
Highlights
Fuzzy logic controllers have been commonly adopted in many areas of engineering over the last few decades [1,2,3,4]
We presented a systematic procedure for optimal design and tuning of a PID-type interval type-2 fuzzy logic controller (IT2 FLC)
A variable called the blurring degree was introduced to find the optimal structure of IT2 FLC
Summary
Fuzzy logic controllers have been commonly adopted in many areas of engineering over the last few decades [1,2,3,4]. Due to the closed kinematic structure, Delta robots present better performance in accuracy, rigidity and payload capacity over their serial counterparts. All these advantag‐ es make this robot a good platform in many areas of engineering [12,13,14,15]. An optimal design and tuning method was developed for PID-type IT2 FLCs applied to Delta parallel robots’ trajectory tracking control. The passive arms are a parallelogram structure, which ensures the travelling platform remains parallel to the robot base. The rigid-body dynamic equation of the Delta robot considering Coulomb and viscous frictions is obtained:. 3. PID-type IT2 Fuzzy Logic Controller Structure Design for the Delta Parallel Robot
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