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This paper investigates the development and evaluation of a robust control system for a wood drying kiln process incorporating decentralized variable structure control (DVSC) such that the moisture content of lumber will reach and be stabilized at the desired set point. A description of the dynamics of the wood drying process by means of the time-delay neural network is also presented, in which the...
This paper addresses some of the potential benefits of using ANFIS controllers to control an inverted pendulum system. The stages of the development of a four input Adaptive-neuro fuzzy inference structure (ANFIS)model were presented. The main idea of this paper is to implement and optimized neuro-fuzzy logic control algorithms in order to balance the inverted pendulum and at the same time reducing...
The traditional PID controller and the structure of the Neural Net model adaptive controller are discussed in this paper, and the infection of the parameter to the system performance is the emphasis. The step response of the system and wave symbol is gained. Corresponding control strategy is presented for the pneumatic position control system. Based on this model, compute digital simulation is completed...
This paper presents a neural network proportion integral differential (PID) controller for automatic gauge control (AGC) System of rolling mill, it is an high non-linear and time-varying system. The traditional PID controller has the invariable parameters. However in the actual factory, the environment of the controlled object is often changed. If the three parameters of PID controller can't adjusted...
In order to actualize decoupling control for nonlinear multivariate coupling system, A multivariate self-adapting decoupling control method based on CMAC and PID was proposed in this studies, and its algorithm was designed in detail. The control strategy utilizes PID controller and CMAC to combine a composite controller. Outputs of multiple same composite controllers are mapped by MIMO linear neural...
In this paper, a novel model reference adaptive control (MRAC) scheme based on neural network (NN) is proposed for servo system tracking control to achieve high-precision position control. This scheme consists of an MRAC controller and an online NN controller in velocity-loop and a traditional PID controller in position-loop. For reducing influence which arose from modeling error, unknown model dynamics,...
The composition control method based on cerebellar model articulation controller (CMAC) and PID controller is proposed to regulate the number of vehicles entering a freeway entrance point. First, the freeway traffic flow dynamic model is built. Then the algorithm of the composition controller of CMAC and PID is formulated. In conjunction with nonlinear feedback theory, the on-ramp metering rate of...
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