Fuzzy Control Optimization of Loading Paths for Hydroforming of Variable Diameter Tubes

The design of the loading path is one of the important research contents of the tube hydroforming process.Optimization of loading paths using optimization algorithms has received attention due to the inefficiency of only finite element optimization.In this paper,the hydroforming process of 5A02 aluminum alloy variable diameter tube was as the research object.Fuzzy control was used to optimize the loading path,and the fuzzy rule base was established based on FEM.The minimum wall thickness and wall thickness reduction rate were determined as input membership functions,and the axial feeds variable value of the next step was used as output membership functions.The results show that the optimized loading path greatly improves the uniformity of wall thickness and the forming effect compared with the linear loading path.The round corner lamination rate of the tube is 91.2%under the fuzzy control optimized loading path,which was increased by 47.1%and 22.6%compared with linear loading Path 1 and Path 2,respectively.Based on the optimized loading path in the experiment,the minimum wall thickness of the variable diameter tube was 1.32 mm and the maximum thinning rate was 12.4%.The experimental results were consistent with the simulation results,which verified the accuracy of fuzzy control.The research results provide a reference for improving the forming quality of thin-walled tubes and plates.

A fuzzy control and neural network based rotor speed controller for maximum power point tracking in permanent magnet synchronous wind power generation system

When the wind speed changes significantly in a permanent magnet synchronous wind power generation system,the maximum power point cannot be easily determined in a timely manner.This study proposes a maximum power reference signal search method based on fuzzy control,which is an improvement to the climbing search method.A neural network-based parameter regulator is proposed to address external wind speed fluctuations,where the parameters of a proportional-integral controller is adjusted to accurately monitor the maximum power point under different wind speed conditions.Finally,the effectiveness of this method is verified via Simulink simulation.

A Two-Layer Fuzzy Control Strategy for the Participation of Energy Storage Battery Systems in Grid Frequency Regulation

To address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and the loadwhen a large number of newenergy sources are connected to the grid,a two-layer fuzzy control strategy is proposed for the participation of the energy storage battery system in FM.Firstly,considering the coordination of FM units responding to automatic power generation control commands,a comprehensive allocation strategy of two signals under automatic power generation control commands is proposed to give full play to the advantages of two FM signals while enabling better coordination of two FM units responding to FM commands;secondly,based on the grid FM demand and battery FM capability,a double-layer fuzzy control strategy is proposed for FM units responding to automatic power generation control commands in a coordinated manner under dual-signal allocation mode to precisely allocate the power output depth of FM units,which can control the fluctuation of frequency deviation within a smaller range at a faster speed while maintaining the battery charge state;finally,the proposed Finally,the proposed control strategy is simulated and verified inMatlab/Simulink.The results show that the proposed control strategy can control the frequency deviation within a smaller range in a shorter time,better stabilize the fluctuation of the battery charge level,and improve the utilization of the FM unit.

Intelligent Home Using Fuzzy Control Based on AIoT

The Internet of Things has grown rapidly in recent years,and the technologies related to it have been widely used in various fields.The idea of this paper is to build a set of Internet of Things systems in a smart home wireless network environment,with the purpose of providing people with a more comfortable,convenient,and safe life.In the sensing layer of the Internet of Things,we discuss the uses of common sensing technologies on the Internet and combine these with Arduino microprocessors to integrate temperature sensing modules,humidity sensing modules,gas sensing modules,and particulate matter 2.5(PM2.5)sensing modules.In the network layer,we discuss using the Wi-Fi wireless networking function composed of a home router and a wireless Wi-Fi chip Espressif system 8266(ESP8266)to transmit the collected home-sensing data to the ThingSpeak cloud database.Finally,in the application layer part,the system uses a mobile device with fuzzy calculation optimization software.The system is also connected remotely for home environment monitoring,so the home environment can be optimized anytime,anywhere.

Research on Obstacle Avoidance Method of Intelligent Car Based on Optimized Fuzzy Control Algorithm

In order to realize the accurate obstacle avoidance function of intelligent car, we propose an intelligent car obstacle avoidance system based on optimized fuzzy control algorithm. Firstly, the kinematics model of intelligent car obstacle avoidance is established, and an efficient environment information collection system composed of multiple sensors is designed to realize the comprehensive collection of obstacle information. Then, the optimized fuzzy control system is adopted to improve the position control accuracy and obstacle avoidance ability. Through the physical debugging and joint simulation of the intelligent car fuzzy controller in the MATLAB and Simulink environment, the simulation results show that the control method can make the collision-free path planned by the intelligent car from the initial state to the obstacle avoidance smoother, and at the same time, the obstacle avoidance of the intelligent car. The actual running distance is reduced by about 16%, which can ensure the practicability of the obstacle avoidance system, provide a new guarantee for the safe operation of the car, and also provide a new idea for the development of the unmanned car.

Dynamically Scaled Fuzzy Control of Autonomous Intelligent Actor

The article presents an approach toward the implementation of an Autonomous Intelligent Actor’s (AIA) [1] fuzzy control mechanism, when each step of it is based on dynamically defined scale. Such a scale is directed by fuzzy conditional inference rule. The approach, offered in the article, allows “soft landing” of AIA on a Target even in a case of “unfriendly” docking situation.

The Optimized Disign of the Fuzzy Controller(Ⅰ)——The predigested disquisition of rules of fuzzy control

To improve the ability and precisions of the fuzzy control,this thesis points out the adjusted fuzzy control method,realizes the precision of the fuzzy quantity, and reduces the number of the fuzzy control rules,so that it can predigest the process of disigns and realize the methods without influencing the idiocratic control,which are on the base of the domain flexing.

Direct adaptive fuzzy control based on integral-type Lyapunov function

A new scheme of direct adaptive fuzzy controller for a class of nonlinear systems with unknown triangular control gain structure is proposed. The design is based on the principle of sliding mode control and the approximation capability of the first type fuzzy systems. By introducing integral-type Lyapunov function and adopting the adaptive compensation term of optimal approximation error, the closed-loop control system is proved to be globally stable, with tracking error converging to zero. Simulation results demonstrate the effectiveness of the approach.

A simplified adaptive interval Type-2 fuzzy control in practical industrial application

Adaptive Type-2 fuzzy control possesses control performance better than the traditional adaptive fuzzy control.However,heavy computation burden obviously blocks the utilization of adaptive Type-2 fuzzy control in industrial application.By adopting novel piecewise fuzzy sets and center-average type-reduction,a simplified adaptive interval Type-2 fuzzy controller involving less computation is developed for practical industrial application.In the proposed controller,the inputs are divided into several subintervals and then two piecewise fuzzy sets are used for each subinterval.With the manner of piecewise fuzzy sets and a novel fuzzy rules inference engine,only part of fuzzy rules are simultaneously activated in one control loop,which exponentially decreases the computation and makes the controller appropriate in industrial application.The simulation and experimental study,involving the popular magnetic levitation platform,shows the predicted system with theoretical stability and good tracking performance.The analysis indicates that there is far less computation of the proposed controller than the traditional adaptive interval Type-2 fuzzy controller,especially when the number of fuzzy rules and fuzzy sets is large,and the controller still maintains good control performance as the traditional one.

Analysis of one dimensional and two dimensional fuzzy controllers

The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.

ADAPTIVE FUZZY CONTROL FOR ROBOT ARM MANIPULATOR WITH 5-DOF

To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.

Obstacle Avoidance of Flapping⁃Wing Air Vehicles Based on Optical Flow and Fuzzy Control

The flapping-wing air vehicle(FWAV)is a kind of bio-inspired robot whose wings can flap up and down like bird and insect wings.A vision-based obstacle avoidance method for FWAVs is proposed in this paper.First,the Farneback algorithm is used to calculate the optical flow field of the first-view video frames taken by the on-board image transmission camera.Based on the optical flow information,a fuzzy obstacle avoidance controller is then designed to generate the FWAV steering commands.Experimental results show that the proposed obstacle avoidance method can accurately identify obstacles and achieve obstacle avoidance for FWAVs.

Fuzzy Control of Nitrate Recirculation and External Carbon Addition in A/O Nitrogen Removal Process

Nitrogen and phosphorous concentrations of effluent water must be taken into account for the design and operation of wastewater treatment plants. In addition, the requirement for effluent quality is becoming strict. Therefore, intelligent control approaches are recently required in removing biological nutrient. In this study, fuzzy control has been successfully applied to improve the nitrogen removal. Experimental results showed that a close relationship between nitrate concentration and oxidation-reduction potential (ORP) at the end of anoxic zone was found for anoxic/oxic (A/O) nitrogen removal process treating synthetic wastewater. ORP can be used as online fuzzy control parameter of nitrate recirculation and external carbon addition. The established fuzzy logic controller that includes two inputs and one output can maintain ORP value at - 86 mV and - 90 mV by adjusting the nitrate recirculation flow and external carbon dosage respectively to realize the optimal control of nitrogen removal, improving the effluent quality and reducing the operating cost.

Adaptive Fuzzy Control System of Servomechanism for Electro-Discharge Machining Combined with Ultrasonic Vibration

For electro-discharge machining, only in the optimum state could the highest material removal rate be realized. In practical machining process, the timely elevation of the tool electrode is needed to eliminate chipping, which ordinarily occupies quite a lot of time. Therefore, besides the control of the machining parameters, the control of the optimum discharge gap and the conversion of different machining states is also needed. In this paper, the adaptive fuzzy control system of servomechanism for EDM combined with ultrasonic vibration is studied, the servomechanism of which is composed of the stepping motor comprising variable steps and the inductive synchronizer. The fuzzy control technology is used to realize the control of the frequency and the step of the servomechanism. The adaptive fuzzy controller has three inputs and two outputs, which can well meet the actual control requirements. The constitution of the fuzzy control regulation for the step frequency is the key to the design of the whole fuzzy control system of the servomechanism. The step frequency is mainly determined by the position error and the change rate of the position error. When the value of the position error is high or medium, the controlled parameters are selected to eliminate the error; when the position error is lower, the controlled parameters are selected to avoid the over-orientation and thus keep the stability of the system. According to these, a fuzzy control table is established in advanced, which is used to express the relations between the fuzzy input parameters and the fuzzy output parameters. The input parameters and the output parameters are all expressed by the level-values in fuzzy field. Therefore, the output parameters used for control can be obtained for the fuzzy control table according to the detected actual input parameters, by which the EDM combined with ultrasonic vibration is improved and the machining efficiency is increased. In addition, a stimulation program is designed by means of Microsoft Visual Basic

A practical fuzzy controllers scheme of overhead crane

This paper presents fuzzy-based design for the control of overhead crane. Instead of analyzing the complex nonlinear crane system, the proposed approach uses simple but effective way to control the crane. There are twin fuzzy controllers which deal with the feedback information, the position of trolley crane and the swing angle of load, to suppress the sway and accelerate the speed when the crane transports the heavy load. This approach simplifies the designing procedure of crane controller; besides, the twin controller method reduces the rule number when fulfilling the fuzzy system. Finally, experimental results through the crane model demonstrate the effectiveness of the scheme.

Robust adaptive fuzzy control for a class of perturbed pure-feedback nonlinear systems

A new design scheme of direct adaptive fuzzy controller for a class of perturbed pure-feedback nonlinear systems is proposed. The design is based on backstepping and the approximation capability of the first type fuzzy systems. A continuous robust term is adopted to minify the influence of modeling errors or disturbances. By introducing the modified integral-type Lyapunov function, the approach is able to avoid the requirement of the upper bound of the first time derivation of the high frequency control gain. Through theoretical analysis, the closed-loop control system is proven to be semi-globally uniformly ultimately bounded, with tracking error converging to a residual set.

Study of Interval Type-2 Fuzzy Controller for the Twin-tank Water Level System

For dealing with large static error due to poor immunity of the traditional fuzzy control, a novel interval type-2 fuzzy control system is proposed. By extending the typical membership functions to interval type-2 membership functions, the proposed control system can efficiently reduce the uncertain disturbance from real environment without increasing the design complexity. The simulation results on the water tank level control system showed that the proposed method succeeded in better static and dynamic control with stronger robust performance than the traditional fuzzy control method.

Signal frequency based self－tuning fuzzy controller for semi－active suspension system

A new kind of fuzzy control scheme, based on the identification of the signal' s main frequency and the behavior of the ER damper, is proposed to control the semi-active suspension system. This method ad-justs the fuzzy controller to achieve the best isolation effect by analyzing the main frequency' s characters and inspecting the change of system parameters. The input of the fuzzy controller is the main frequency and the op-timal damping ratio is the output. Simulation results indicated that the proposed control method is very effec-tive in isolating the vibration.

Fuzzy control on automatic frequency tracking of ultrasonic vibration system with high power and high quality factor Q

In order to realize automatic tracking drift of resonance frequency of ultrasonic vibration system with high power and high quality factor Q, adaptive fuzzy control was studied with a self-fabricated ultrasonic plastic welding machine. At first, relations between amplitude of vibration and frequency as well as main loop current and amplitude of vibration were analyzed. From this analysis, we deduced that frequency tracking process of the vibration system can be concluded as an optimizing problem of one dimensional fluctuant extremum of main loop current in vibration system. Then a method of self-optimizing fuzzy control, used for the realization of automatic frequency tracking in vibration system, is presented on the basis of serf-optimizing adaptive control approach and fuzzy control approach. The result of experiments shows that the fuzzy self-optimizing method can solve the problem of tracking frequency drift very well. Response time of tracking in the system is less than 50 ms, which basically meets the requirements of frequency tracking in ultrasonic plastic welding machine.

Type-2 Fuzzy Control for Driving State and Behavioral Decisions of Unmanned Vehicle

In this paper, interval type-2 fuzzy sets, fuzzy comprehensive evaluation and the fuzzy control rules are synthesized to realize the control of unmanned vehicle in driving state and behavioral decisions. Compared to the type-1 fuzzy set, type-2 fuzzy sets have more advantages in handling the model based on uncertainties, linguistic information because the membership functions are fuzzy sets. Different membership functions are established for each factor when the unmanned vehicle is driving at different speed intervals. In addition, a new evaluation method is developed to analyze unmanned vehicle’s driving state. Finally, a set of dynamic fuzzy rules are sorted out, which can be applied to the unmanned vehicle’s behavioral decision-making and provide a new idea to related research.