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—This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using dynamic fuzzy rules. Temporal relations are embedded in the network by adding feedback connections in the second layer of(More)
— This paper proposes a new intelligent scheme using type-2 fuzzy inference system in neural network structure. This type-2 fuzzy neural network system (type-2 FNN) combines the advantages of type-2 fuzzy logic systems (FLSs) and neural networks (NNs). The general FNN system (called type-1 FNN system) has the properties of parallel computation scheme, easy(More)
In this paper, we propose a design method of fractional order PID controller via hybrid of electromagnetism-like (EM) algorithm and genetic algorithm (GA). The hybrid algorithm improves the performance of EM algorithm by using GA, called IEMGA. The main modification is that the randomly neighborhood local search is changed by genetic algorithm for designing(More)
—The tracking control problem with saturation constraint for a class of unicycle-modeled mobile robots is formulated and solved using the backstepping technique and the idea from the LaSalle's invariance principle. A global result is presented in which several constraints on the linear and the angular velocities of the mobile robot from recent literature(More)
This paper presents a type-2 fuzzy neural network system (type-2 FNN) and its learning using genetic algorithm. The so-called type-1 fuzzy neural network (FNN) has the properties of parallel computation scheme, easy to implement, fuzzy logic inference system, and parameters convergence. And, the membership functions (MFs) and the rules can be designed and(More)
Keywords: PID control Fractional-order PID control Electromagnetism-like algorithm Genetic algorithm a b s t r a c t Based on the electromagnetism-like algorithm, an evolutionary algorithm, improved EM algorithm with genetic algorithm technique (IEMGA), for optimization of fractional-order PID (FOPID) controller is proposed in this article. IEMGA is a(More)
In this paper, an adaptive parallel control architecture to stabilize a class of nonlinear systems which are nonminimum phase is proposed. For obtaining an on-line performance and self-tuning controller, the proposed control scheme contains recurrent fuzzy neural network (RFNN) identifier, nonfuzzy controller, and RFNN compensator. The nonfuzzy controller(More)