Fuzzy self-tuning PID control of the operation temperatures in a two-staged membrane separation process

A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As the conventional PID controller is difficult to make the operation temperatures steady, a fuzzy self-tuning PID control algorithm is proposed. The application shows that the algorithm is effective, the operation temperatures of both stages can be controlled steadily, and the operation flexibility and adaptability of the hydrogen recovery unit are enhanced with safety. This study lays a foundation to optimize the control of the membrane separation process and thus ensure the membrane performance.

Stabilization of CSTR w ith Self-tuning Sliding Mode Controller Using T-S Fuzzy Linearization

A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Combing the traits of SMC and CSTR,three fuzzy rules can meet the requirements of controlled system.The self-tuning switch control law which can drive the state variables to the sliding surface as soon as possible is designed to ensure the robustness of uncertain fuzzy system.Lyapunov equation is applied to proving the stability of the sliding surface.The simulations show that the proposed approach can achieve desired performance with less chattering problem.

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.

Motion Control of Omnidirectional Mobile Platform based on Fuzzy PID

The omnidirectional mobile platform has three degrees of freedom that make it widely applicable to all areas of industry, while the Mecanum wheel has the disadvantages wheel omnidirectional mobile platform is always difficult in of large vibration, the trajectory precision of Mecanum the omnidirectional mobile platform. To control the trajectory of the omnidirectional mobile platform better, this paper proposes a fuzzy self-tuning PID control model, through establishing the motion model of omnidirectional mobile platform in Adams software, then combined with Simulink simulation, analysis of fuzzy PID controller to improve the accuracy of the speed control of omnidirectional mobile platform, improve the control method of a precise trajectory of the omnidirectional mobile platform motion.

Modeling the Spike Response for Adaptive Fuzzy Spiking Neurons with Application to a Fuzzy XOR

A spike response model(SRM)based on the spikes generator circuit(SGC)of adaptive fuzzy spiking neurons(AFSNs)is developed.The SRM is simulated in MatlabTM environment.The proposed model is applied to a configuration of a fuzzy exclusive or(fuzzy XOR)operator,as an illustrative example.A description of the comparison of AFSNs with other similar methods is given.The novel method of the AFSNs is used to determine the value of the weights or parameters of the fuzzy XOR,first with dynamic weights or self-tuning parameters that adapt continuously,then with fixed weights obtained after training,finally with fixed weights and a dynamic gain or self-tuning gain for a fine adjustment of amplitude.

TYPICAL ARCHITECTURES FOR FUZZY CONTROL

Some typical structural schemes of Fuzzy control have been surveyed. Besides general structure of fuzzy logic controller (FLC), the structural schemes include PID fuzzy controller, self-organizing fuzzy controller, selftuning fuzzy controller, self-learning fuzzy controller, and expect fuzzy controller, etc. This survey focuses on the control principle, and provides a basis for potential applications. Most of the structures have been used in various control fields, one of application areas is in the metallurgy industry, e. g., the temperature control of the electric furnace, the control of the aluminum smelting process, etc. According to the application requirements, one can choose a structural scheme for special use.

Modeling and Simulation of Two Axes Gimbal Using Fuzzy Control

The application of the guided missile seeker is to provide stability to the sensor’s line of sight toward a target by isolating it from the missile motion and vibration.The main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling approach.The paper is started by deriving the mathematical model for gimbals motion using Newton’s second law,followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors and sensors using MATLAB/SimMechanics.Then,a Mamdani-type fuzzy and a Proportional-Integral-Derivative(PID)controllers were designed using MATLAB software.The performance of both controllers was evaluated and tested for different types of input shapes.The simulation results showed that self-tuning fuzzy controller provides better performance,since no overshoot,small steady-state error and small settling time compared to PID controller.

Smith Prediction Monitor AGC System Based on Fuzzy Self-Tuning PID Control

In accordance with the feature of pure delay in monitor AGC system for cold rolling mill, a new fuzzy selftuning PID Smith prediction controller is developed. The position control model is deduced based on a single stand cold rolling mill, and the fuzzy controller for monitor AGC system is designed. The analysis of dynamic performance for traditional PID Smith prediction controller and fuzzy self-tuning PID Smith prediction controller is done by MAT- LAB toolbox. The simulation results show that fuzzy self-tuning PID Smith controller has stronger robustness, faster response and higher static accuracy than traditional PID Smith controller.

Indirect Output Voltage Control in Negative Output Elementary Super Lift Luo Converter Using PIC plus FLC in Discontinuous Conduction Mode

In this paper, the design of a proportional integral controller (PIC) plus fuzzy logic controller (FLC) for the negative output elementary super lift Luo converter (NOESLLC) operated in discontinuous conduction mode (DCM) is presented. In spite of the many benefits viz. the high voltage transfer gain, the high efficiency, and the reduced inductor current and the capacitor voltage ripples, it natured with non-minimum phase. This characteristic makes the control of NOESLLC cumbersome. Any attempt of direct controlling the output voltage may erupt to instability. To overcome this problem, indirect regulation of the output voltage based on the two-loop controller is devised. The savvy in the inductor current control improves the dynamic response of the output voltage. The FLC is designed for the outer (voltage) loop while the inner (current) loop is controlled by the PIC. For the developed ?19.6 V NOESLLC, the dynamic performances for different perturbations (line, load and component variations) are obtained for PIC plus FLC and compared with PIC plus PIC. The study of two cases is performed at various operating regions by developing the MATLAB/Simulink model.

Power quality improvement using fuzzy logic controller for five-level shunt active power filter under distorted voltage conditions

In this paper, a five-level inverter is used as a shunt active power filter （APF）, taking advantages of the multilevel inverter such as low harmonic distortion and reduced switching losses. It is used to compensate reactive power and eliminate harmonics drawn from a thyristor rectifier feeding an inductive load （RL） under distorted voltage conditions. The APF control strategy is based on the use of self-tuning filters （STF） for reference current generation and a fuzzy logic current controller. The use of STF instead of classical extraction filters allows extracting directly the voltage and current fundamental components in the a-fl axis without phase locked loop （PLL）. The MATLAB fuzzy logic toolbox is used for implementing the fitzzy logic control algorithm. The obtained results show that the proposed shunt APF controller has produced a sinusoidal supply current with low harmonic distortion and in phase with the line voltage.

Some Investigations on Fuzzy P+Fuzzy I+Fuzzy D Controller for Non-stationary Process

The paper addresses the adaptive behaviour of parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller. The parallel FP+FI+FD controller is actually a non-linear adaptive controller whose gain changes continuously with output of the process under control. Two non-stationary processes, whose characteristics change with time, are considered for simulation study. Simulation is performed using software LabVIEW TM . The set-point tracking response of parallel FP+FI+FD is compared with conventional parallel proportional plus integral plus derivative (PID) controller, tuned with the Ziegler-Nichols (Z-N) tuning technique. Simulation results show that conventional PID controller fails to track the set-point and becomes unstable as the process changes its characteristic with time. But the parallel FP+FI+FD controller shows considerably much better set-point tracking response and does not deviate from steady state. Also, a huge spike is observed in the output of PID controller as the reference set-point and process parameters are changed, while the FP+FI+FD controller gives spike free control signal.

Study of Multi media Streams Dynamic Rate Control Based on Fuzzy Adaptive PID

A Multimedia streams dynamic rate control algorithm based on Fuzzy adaptive PID （MFPID） has been proposed to implement multimedia streams＇ end sending rate on-line self-regulating and smoothing, and to track system resources in time, so that it can avoid system＇s regulating oscillation and guarantee system＇s stability. And, some work has been done to analyze adaptive session model of multimedia streams, to implement future available bandwidth estimation of IP network, to achieve PID parameters＇ on-line self-tuning by fuzzy controlling. Simulation validated the theoretical results of MFPID.