Technical analysis of adaptive neuron fuzzy intelligent system in tennis serve

Serving is the most important hitting technique in tennis, and a good service receiving can instantly reverse the active and passive relationship between serve and receive on the tennis court, and control the rhythm of the court. The purpose of this study is to use an adaptive neuron fuzzy intelligent system to analyze some techniques of tennis serve. In this study, eight male players from the school tennis team were selected as the experimental subjects, whose sports level was above the national tennis level II. Ten weeks before the simulation test, the training time and frequency of 8 subjects were the same. In other words, 5 times a week, 2.5 hours±0.5 hours. The work engineering of adaptive fuzzy system firstly, in the off-line modeling stage, the adaptive fuzzy system uses the rule self splitting technology to generate the initial fuzzy rules, and uses the improved adaptive neural network algorithm to optimize the calculation; then according to the error between the system input and the predicted output, the independent variable is adjusted and replaced; at the same time, the adaptive fuzzy system is further used for calculation In the process of tennis serving, the nonlinear control variables are obtained online and applied to the fuzzy system for control. Next, in the experiment, the system was used to record the body’s movement and service scores during service. The experimental results show that during the service process, the maximum trunk torsion amplitude can reach 48.26 ° and the minimum is only 5.41 ° and the service score accounts for 81.41% and 80.47% of the total scores of the two sections respectively. This shows that the fuzzy system in this study can effectively analyze the service posture and score of athletes. It is concluded that the accurate calculation and analysis of tennis serve by adaptive neuron intelligent fuzzy system in this study is conducive to improve the tennis serviceability and competition performance of players. This research has made a certain contribution to the intellectualization of sports.

Expert system for Robotic Path Planning

Robotic planning to find the target our goal point/s is most important subject with the minimum distance and the fastest speed with obstacle avoidance expert system has been proposed. In this paper we try to compare and consider different scenario by taking two or more moving robot figure out the short path from the initial and the final point automatically through the map of many regular and irregular obstacles. Firstly, the adaptive fuzzy expert system is present where the fuzzy rule has been adaptive recursively through the robot moving, and then the potential field algorithm has been compared with the adaptive fuzzy system, the results demonstrated that the adaptive fuzzy is faster than the potential field but the accuracy moving of the potential field robotic path planning is much better. All the algorithms were failed when two robots moving from two different initial points to one final target point the why we have proposed particle swarm optimization (PSO) algorithm to solve such problem.

Unscented Kalman Filter Based on Spectrum Sensing in a Cognitive Radio Network Using an Adaptive Fuzzy System

In this paper, we proposed the unscented Kalman filter (UKF) based on cooperative spectrum sensing (CSS) scheme in a cognitive radio network (CRN) using an adaptive fuzzy system—in this proposed scheme, firstly, the UKF to apply the nonlinear system which is used to minimize the mean square estimation error; secondly, an adaptive fuzzy logic rule based on an inference engine to estimate the local decisions to detect a licensed primary user (PU) that is applied at the fusion center (FC). After that, the FC makes a global decision by using a defuzzification procedure based on a proposed algorithm. Simulation results show that the proposed scheme achieved better detection gain than the conventional schemes like an equal gain combining (EGC) based soft fusion rule and a Kalman filter (KL) based soft fusion rule under any conditions. Moreover, the proposed scheme achieved the lowest global probability of error compared to both the conventional EGC and KF schemes.

A fuzzy-based dynamic inversion controller with application to vibration control of vehicle suspension system subjected to uncertainties

Uncertainty or the model error always exists in depicting technique systems. In many cases, the model error is implicitly the time-varying tendency such as in the semi-active railway vehicle suspensions using magneto-rheological damper, where the hysteretic response and time varying of physical parameter value of the magneto-rheological fluid due to system temperature variation are inherent features. To exploit well these systems, a becomingly compensative and adaptive mechanism needs to be set up to deal with both uncertainty and external disturbance. In this study, a new fuzzy-based dynamic inversion controller for semi-active railway vehicle suspensions using magneto-rheological dampers subjected to uncertainty and external disturbance is proposed. The fuzzy-based dynamic inversion controller faces uncertainty and disturbance individually. Regarding external disturbance, a disturbance observer is designed to estimate the compensative quantity. While for the model error influence, a combination of the inference ability of an adaptive fuzzy system and the competence to reach and keep the system stability states of sliding mode control is established via a model so-called fuzzy sliding mode control. First, an optimal sliding mode controller is designed, which is then used as a framework for building the adaptive fuzzy system. Based on Lyaponov theory, adaptive update law for the adaptive fuzzy system is discovered to adjust the sliding mode control adaptive to the system status. Surveys via quarter and half train-car vehicle suspension models including a real system of semi-active railway vehicle suspensions using magneto-rheological damper have been performed, which reflected the positive ability of the proposed method to stamp out vibration.