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Aiming at modeling and controlling a kind of nonlinear dynamic systems and dealing with the uncertainties coursing by the changing of modeling parameters, a Dynamic Fuzzy Neural Intelligent Controller (DFNIC) is presented in this paper. A dynamic fuzzy neural networks (DFNN) with a PID controller are integrated in DFNIC, in which the structure and parameters are adjusted online, and the fuzzy rules...
This paper presents hybrid control strategy for robust trajectory tracking control for a class of uncertain nonlinear mechanical systems. The design combines adaptive fuzzy system with robust adaptive control algorithm. Adaptive fuzzy system approximates unknown nonlinear system dynamics while a robustifying adaptive control term is used to cope with uncertainties due to the presence of external disturbance,...
The uncertainties coursing by the changing of modeling parameters should be considered when modeling and controlling a kind of nonlinear dynamic systems. A Dynamic Fuzzy Neural Adaptive Control (DFNAC) algorithm is presented in the paper. The DFNAC combines a Dynamic Fuzzy Neural Networks (DFNN) with a PID controller. DFNN adjusts its structure and parameters online, and generates the fuzzy rules...
In this article a direct adaptive fuzzy control methodology is developed to handle formation control and target tracking problems in a class of multi-agent systems with nonlinear and uncertain dynamics. The proposed adaptive method guarantees stability and achievement of the desired tracking and formation tasks. The effectiveness of the algorithm is verified with numerical simulations.
In this paper, we first present some dynamic TS fuzzy subsystems to approximate a nonlinear system. To make the subsystems asymptotically stable, the reference model with the same fuzzy sets of the system rule is established. A feedback controller is designed based on an exact approximation model. The control gain can be solved by LMI approach. Since in practical plant, there are parameters uncertainty...
Considering the pitching channel of air breathing hypersonic vehicle X-43A as plant, flight control system was designed according to the 6 degree of freedom nonlinear model. The flight control system includes two loops, of which the structure is conventional mode. The guidance loop is a PD controller, while the control loop is composed of two fuzzy logic controllers. The guidance loop leads the vehicle...
A new approach about design for super-sonic anti-ship missiles guidance laws (GLs) was proposed in this study. Firstly, the normal form of the fourth order state equation for integrated guidance and control loop about the yaw plane was formulated considering target uncertainties and control loop dynamics. Next the proposed GLs adopts the sliding mode control approach with adaptation for known bound...
In this paper, adaptive hierarchical fuzzy CMAC neural network controller (HFCMAC), for a certain class of nonlinear dynamical system is presented. The main advantages of adaptive HFCMAC control are: Better performance of the controller because adaptive HFCMAC can adjust itself to the changing enviroment and can be implemented in real time applications. The proposed method provides a simple control...
In unit steam-boiler generation, a coordinated control strategy is required to ensure a higher rate of load change without violating thermal constraints. The process is characterized by nonlinearity and uncertainty. While neural networks can model highly complex nonlinear dynamical systems, they produce black box models. This has led to significant interest in neuro-fuzzy networks (NFNs) to represent...
In unit steam-boiler generation, a coordinated control strategy is required to ensure a higher rate of load change without violating thermal constraints. The process is characterized by nonlinearity and uncertainty. While neural networks can model highly complex nonlinear dynamical systems, they produce black box models. This has led to significant interest in neuro-fuzzy networks (NFNs) to represent...
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