scholarly journals Mathematical analysis of a simplified general type-2 fuzzy PID controller

2020 ◽  
Vol 17 (6) ◽  
pp. 7994-8036
Author(s):  
Jianzhong Shi ◽  
◽  
Ying Song
Keyword(s):  
Mathematical Analysis ◽  
Pid Controller ◽  
General Type ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller

scholarly journals Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID Controller

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 479
Author(s):  
Yao Chen ◽  
Tao Zhao ◽  
Songyi Dian ◽  
Xiaodong Zeng ◽  
Haipeng Wang
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
General Type ◽  
Fuzzy Logic Controller ◽  
Differential Operators ◽  
Power Line ◽  
State Variables ◽  
Fuzzy Pid ◽  
Robot System

In this study, a general type-2 fractional order fuzzy PID (GT2FO-FPID) controller is proposed to fulfil the balance adjustment of the Power-line Inspection (PLI) robot system. It is a combination of Mamdani general type-2 fuzzy logic controller (GT2-FLC) and fractional PID controller. Since the PLI robot system is an under-actuated system, it’s necessary to get complete information of the system. However, when all state variables are treated as input to the controller, there is a problem with the rule explosion. Because of this, the information fusion method is adopt to solve the problem and simplify the controller design. At the same time, fractional-order integral-differential operators and input-output scaling factors, which are taken as design variables and optimized by genetic algorithm (GA). To assess the performance of proposed controller based on symmetry criterion, we compared it against existing controllers, i.e., interval type-2 fractional order fuzzy PID (IT2FO-FPID), type-1 fractional order fuzzy PID (T1FO-FPID), and conventional fractional order (FOPID) controllers. Furthermore, to show the anti-inference ability of the proposed controller, three common perturbed process are tested. Finally, simulation results show that the GT2FO-FPID controller outperforms other controllers in the presence of external perturbations on the PLI robot system.

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