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A fuzzy control structure that stabilizes the MWP was originally developed in [2] , [13]. The spectrum of brain waves is very sensitive to the mental and emotional states of the brain, so this attribute is used to monitor mental activity [19]. For full functionality of ResearchGate it is necessary to enable JavaScript. In this way, the frequency distributions as a spectrum of brain waves can be observed by using FFT algorithm after filtering, for example Kalman filters [47].

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Novel optimized and adaptive solutions. The study in [2] compared the fuzzy anti-sway speed control structure with a linear-quadratic-Gaussian LQG controller elaborated in [3].

Calculating lock-in range by using Evan's root-locus. A fuzzy control structure that stabilizes the MWP was originally developed in [2][13]. The fuzzy inference can be defined with heuristic IF-THEN rules which are collected based on both the observations related to system dynamics and human common sense [1].

PID vs Fuzzy Logic. Moreover, the control performance achieved with the preceding fuzzy control structure was analyzed by evaluating different error integrals and transient responses.

The measurement results related to the real system dynamics showed that the proposed fuzzy control structure provided better overall control performance, however, the LQG control strategy showed faster system dynamics for transient events. Here are the instructions how to solieworks JavaScript in your web browser. In this way, the frequency distributions as a spectrum of brain waves can be observed by using FFT algorithm after filtering, for example Kalman filters [47].

Ad you may be interested in. Test bench built for the identification of the Szabad ka -II hexapod robot leg prototypes.

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This approximate reasoning allows to cover model imprecision and uncertainties, moreover, the broadly defined fuzzy sets yield robust and smooth control action which in many cases provides superior control performance compared to linear solutions [2] - [6]. The MEMS-based localization approach has been widely investigated and motlr widely utilized in robotics [1] [2] [3][4][5][6][7], human position tracking [8,9], medical fields [10], sports equipment [11,12], and automated driving [13][14][15][16][17] combine the accelerometer and gyroscope sensors, utilizing their individual features to provide accurate and robust orien- tation results.

The soliworks of brain waves slidworks very sensitive to the mental and emotional states of the brain, so this attribute is used to monitor mental activity [19]. These sensors are generally applied to solve the relative localization problem, where the positions and orientation informa- tion of moving objects are determined using a MEMS-based inertial measurement unit IMU composed of the aforemen- tioned MEMS sensors.

Get access to 30 million figures. For full functionality of ResearchGate it is necessary to enable JavaScript. Solidworks CAD model of the robot.

Kalman filter for mobile-robot attitude estimation: Inspired by the results of [17], this paper introduces a protective PI-type FLC and applies it in the aforementioned control structure.

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