The paper proposed to apply a hierarchical fuzzy-neural multi-model and Takagi–Sugeno (T–S) rules with recurrent neural procedural consequent part for systems identification, states estimation and adaptive control of complex nonlinear plants. The parameters and states of the local recurrent neural network models are used for a local direct and indirect adaptive trajectory tracking control syste...

In this paper, a novel peak observer based adaptive multi-input multi-output (MIMO) fuzzy proportional-integral-derivative (PID) controller has been introduced for MIMO time delay systems. The adaptation mechanism proposed by Qiao and Mizumoto [1] single-input single-output (SISO) systems enhanced system control. tracking, stabilization disturbance rejection performances of the have evaluated c...

Weight control system on the feeder conveyor determines the factor of the quality of products within an industry. The dynamics of the flow rate of material through the feeder conveyor weigh requires a good level of performance controllers. The base of current controllers such as FLC (Fuzzy Logic Controller) requires a certain amount of knowledge and expertise in its design that will make it dif...

a novel technique is investigated for pid controller adaptation in order to control thetemperature of a liquid-phase reactor tank by using a heat exchanger system. as for nonlinearity,time delay problems and model uncertainties introduced by the heat exchanger, an interval type-2fuzzy system (it2fs) is implemented to enhance and improve the total control performance.moreover, the fuzzy inferenc...

fuzzy controllers are being used in various control schemes. the aim of this work was adjusting hemodialysis machine parameters utilizing a fuzzy logic controller (flc) so that patient’s hemodynamic condition remains stable during hemodialysis treatment. for this purpose a comprehensive mathematical model of the arterial pressure response during hemodialysis, including hemodynamic, osmotic, and...

Aiming at the characteristics which variable air volume air conditioning system is multi-variable, nonlinear and uncertain system, normal fuzzy neural network is hard to meet the requirements which dynamic control of multi-variable. In this paper, we put forward a recursive neural network predictive control strategy based on wavelet neural network model. Through recursive wavelet neural network...

A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...

In this paper, a novel adaptive fuzzy sliding mode control method is proposed for the robust tracking control of robotic manipulators. The proposed controller possesses the advantages of adaptive control, fuzzy control, and sliding mode control. First, system stability and robustness are guaranteed based on the sliding mode control. Further, fuzzy rules are developed incorporating with adaptati...

This paper presents an adaptive neuro-fuzzy controller ANFIS (Adaptive Neuro-Fuzzy Inference System) for a bilateral teleoperation system based on FPGA (Field Programmable Gate Array). The proposed controller combines the learning capabilities of neural networks with the inference capabilities of fuzzy logic, to adapt with dynamic variations in master and slave robots and to guarantee good prac...

In this study, an adaptive fuzzy sliding-mode control (AFSMC) system is adopted to control the position of an induction servo motor. The AFSMC system comprises the fuzzy control design and the robust control design. In the fuzzy control design a fuzzy controller is designed to mimic an ideal control law. In the robust control design a robust controller is designed to compensate the approximatio...