Current Issue : April - June Volume : 2017 Issue Number : 2 Articles : 6 Articles
To achieve the goal of driver-less underground mining truck, a fuzzy hyperbolic tangent model is established for path tracking on\nan underground articulated mining truck. Firstly, the sample data of parameters are collected by the driver controlling articulated\nvehicle at a speed of 3 m/s, including both the lateral position deviation and the variation of heading angle deviation. Then, according\nto the improved adaptive BP neural network model and deriving formula of mediation rate of error estimator by the method of\nCauchy robust, the weights are identified. Finally,...
This study proposes an adaptive fuzzy controller for attitude control system (ACS)\nof Innovative Satellite (InnoSAT) based on direct action type structure. In order to study new\nmethods used in satellite attitude control, this paper presents three structures of controllers:\nFuzzy PI, Fuzzy PD and conventional Fuzzy PID. The objective of this work is to compare the\ntime response and tracking performance among the three different structures of controllers. The\nparameters of controller were tuned on-line by adjustment mechanism, which was an approach\nsimilar to a PID error that could minimize errors between actual and model reference output.\nThis paper also presents a Model References Adaptive Control (MRAC) as a control scheme to\ncontrol time varying systems where the performance specifications were given in terms of the\nreference model. All the controllers were tested using InnoSAT system under some operating\nconditions such as disturbance, varying gain, measurement noise and time delay. In conclusion,\namong all considered DA-type structures, AFPID controller was observed as the best structure\nsince it outperformed other controllers in most conditions....
In this paper, the problem of adaptive fuzzy tracking control is considered for a class of uncertain nonaffine nonlinear systems with\nexternal disturbances, multiple time delays, and nonsymmetric saturation constrains. First, the mean value theorem is employed\nto deal with the nonaffine term with input nonlinearity. Then, a new adaptive fuzzy tracking controller with parameter updating\nlaws is designed by using fuzzy approximation technique. Moreover, it is shown that all the closed-loop signals are bounded and\nthe tracking errors can asymptotically converge to zero via the Lyapunov stability analysis. Finally, the simulation example for van\nder Pol oscillator system is worked out to verify the effectiveness of the proposed adaptive fuzzy design approach....
An adaptive hybrid fuzzy-proportional plus crisp-integral current control algorithm (CCA)\nfor regulating supply current and enhancing the operation of a shunt active power filter (SAPF) is\npresented. It introduces a unique integration of fuzzy-proportional (Fuzzy-P) and crisp-integral\n(Crisp-I) current controllers. The Fuzzy-P current controller is developed to perform gain tuning\nprocedure and proportional control action. This controller inherits the simplest configuration; it is\nconstructed using a single-input single-output fuzzy rule configuration. Thus, an execution of few\nfuzzy rules is sufficient for the controller�s operation. Furthermore, the fuzzy rule is developed using\nthe relationship of currents only. Hence, it simplifies the controller development. Meanwhile, the\nCrisp-I current controller is developed to perform integral control action using a controllable gain\nvalue; to improve the steady-state control mechanism. The gain value is modified and controlled\nusing the Fuzzy-P current controller�s output variable. Therefore, the gain value will continuously\nbe adjusted at every sample period (or throughout the SAPF operation). The effectiveness of the\nproposed CCA in regulating supply current is validated in both simulation and experimental work.\nAll results have proven that the SAPF using the proposed CCA is capable to regulate supply current\nduring steady-state and dynamic-state operations. At the same time, the SAPF is able to enhance its\noperation in compensating harmonic currents and reactive power. Furthermore, the implementation\nof the proposed CCA has resulted more stable dc-link voltage waveform....
This paper presents the establishing of a biconvex fuzzy variational (BFV) method with teaching learning based optimization\n(TLBO) for geometric image segmentation (GIS). Firstly, a biconvex object function is adopted to process GIS. Then, TLBO is\nintroduced to maximally optimize the length penalty item (LPI), which will be changed under teaching and learner phase of TLBO,\nmaking the LPI closer to the target boundary. Afterward, the LPI can be adjusted based on fitness function, namely, the evaluation\nstandards of image quality. Finally, the LP is combined item with the numerical order to get better results. Different GIS strategies\nare compared with various fitness functions in terms of accuracy. Simulations show that the presented method is more effective in\nthis area....
A novel electromagnetic active suspension with an energy-regenerative structure is proposed to solve the suspension�s control\nconsumption problem. For this new system, a 2-DOF quarter-car model is built, and dynamics performances are studied using the\nvariable universe fuzzy theory and the PD control approach.A self-powered efficiency concept is defined to describe the regenerative\nstructure�s contribution to the whole control consumption, and its in fluent factors are also discussed. Simulations are carried out\nusing software Matlab/Simulink, and experiments are conducted on the B-class road. The results demonstrate that the variable\nuniverse fuzzy control can recycle more than 18 percent vibration energy and provide over 11 percent power for the control demand.\nFurthermore, the new suspension system offers a smaller body acceleration and decreases dynamic tire deflection compared to the\npassive ones, so as to improve both the ride comfort and the safety....
Loading....