Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A new fuzzy controller for stabilization of parallel-type double inverted pendulum system
Fuzzy Sets and Systems
A proposal of SIRMs dynamically connected fuzzy inference model for plural input fuzzy control
Fuzzy Sets and Systems - Fuzzy control
Anti-swing and positioning control of overhead traveling crane
Information Sciences: an International Journal
Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers
Engineering Applications of Artificial Intelligence
Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic
Information Sciences: an International Journal
Interval type-2 fuzzy logic systems: theory and design
IEEE Transactions on Fuzzy Systems
A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots
IEEE Transactions on Fuzzy Systems
Interval Type-2 Fuzzy Logic Systems Made Simple
IEEE Transactions on Fuzzy Systems
Geometric Type-1 and Type-2 Fuzzy Logic Systems
IEEE Transactions on Fuzzy Systems
Discrete Interval Type 2 Fuzzy System Models Using Uncertainty in Learning Parameters
IEEE Transactions on Fuzzy Systems
A review on the design and optimization of interval type-2 fuzzy controllers
Applied Soft Computing
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The translational oscillations with a rotational proof-mass actuator (TORA) is a well-known benchmark for examining the advantages and limitations of different nonlinear control design techniques. In this paper, a single-input-rule-modules (SIRMs) based type-2 fuzzy logic control scheme is proposed for this nonlinear multivariable system. And, genetic algorithms (GAs) are adopted to determine the parameters and to improve the performance of the SIRMs based type- 2 fuzzy logic controller (SIRM-T2FLC). At last, simulations and comparisons are given to demonstrate the effectiveness, robustness and superiority of the proposed controller under three circumstances: normal case, the disturbance existing case, and the parameter varying case. From the design process and comparisons, it can be seen that: 1) this SIRMs based type- 2 fuzzy control scheme can alleviate the difficulty to design conventional type-2 fuzzy logic controllers (T2FLCs) for this multivariable TORA system, 2) the SIRM-T2FLC is much easier to design and understand compared with conventional nonlinear control strategies for the TORA system, 3) better performance can be achieved.