Parallel Fuzzy P+Fuzzy I+Fuzzy D Controller:Design and Performance Evaluation

In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP＋FI＋FD） controller is proposed. It is derived from the conventional parallel proportional-integral-derivative （PID） controller. It preserves the linear structure of a conventional parallel PID controller, with analytical formulas. The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller. Computer simulations are performed to evaluate the performance of the FP＋FI＋FD controller for setpoint tracking and load-disturbance rejection for some complex processes, such as first- and second-order processes with delay, inverse response process with and without delay and higher order processes. Also, the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve. The simulation and real time control is done using National InstrumentTM hardware and software （LabVIEWTM）. The response of the FP＋FI＋FD controller is compared with the conventional parallel PID controller, tuned with the Ziegler-Nichols （Z-H） and /~strSm- H^gglund （A-H） tuning technique. It is observed that the FP＋FI＋FD controller performed much better than the conventional PI/PID controller. Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP＋FI＋FD controller.

Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-Control for Intelligent Vehicles

Intelligent vehicles can effectively improve traffic congestion and road traffic safety.Adaptive cruise followingcontrol(ACFC)is a vital part of intelligent vehicles.In this paper,a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model,type-2 fuzzy control,feedforward+fuzzy proportion integration(PI)feedback(F+FPIF)control,and inverse longitudinal dynamics model of vehicles.Firstly,a traditional variable time headway model is improved considering the acceleration of the lead car.Secondly,an interval type-2 fuzzy logic controller(IT2 FLC)is designed for the upper structure of the ACFC system to simulate the driver's operating habits.To reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration,the control strategy of F+FPIF is given for the lower control structure.Thirdly,the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method(no lower controller for tracking desired acceleration)separately.Meanwhile,the proportion integration differentiation(PID),linear quadratic regulator(LQR),subsection function control(SFC)and type-1 fuzzy logic control(T1 FLC)are respectively compared with the IT2 FLC in control performance under different scenes.Finally,the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.

Quasi-Z Source Inverter Control of PV Grid-Connected Based on Fuzzy PCI

The photovoltaic grid-connected inverter is an important interface between the photovoltaic power generation system and power grid.Its high-quality operation is directly related to the output power quality of the power grid.In order to further optimize the control effect of the quasi-Z source grid-connected photovoltaic inverter,a fuzzy proportional complex integral control(PCI)method is proposed for the current internal loop control.This method can eliminate the steady-state error,and has the characteristic of zero steady-state error adjustment for the AC disturbance signal of a specific frequency.The inductance-capacitance-inductance(LCL)filter is adopted in the grid-connected circuit,and the feedback capacitive current is taken as the control variable of the inner loop to form the active damping control method,which can not only effectively suppress the resonance of the LCL circuit,but also significantly inhibit the high-order harmonics in the grid-connected current.Finally,a system simulation model is built in MATLAB/Simulink to verify the superiority and effectiveness of the proposed method.

A Novel Asymmetric Three-Phase Cascaded 21 Level Inverter Fed Induction Motor Using Multicarrier PWM with PI and Fuzzy Controller

Multilevel inverters are gaining popularity in high power applications. This paper proposes a new ladder type structure of cascaded three-phase multilevel inverter with reduced number of power semiconductor devices which is used to drive the induction motor. The ultimate aim of the paper is to produce multiple output levels with minimum number of semiconductor devices. This paper uses only 11 switches along with 3 diodes and 4 asymmetrical sources to produce an output voltage of 21 levels. The modulation technique plays a major role in commutation of the switches. Here we implement the multicarrier level shifting pulse width modulation technique to produce the commutation signals for the inverter. The proposed multilevel inverter is used to drive the three-phase induction motor. The mathematical modeling of three-phase induction motor is done using Simulink. Furthermore the PI and fuzzy logic controllers are also used to produce the reference waveform of the level shifting technique which in turn produces the commutation signals of the proposed multilevel converter. The controllers are used to control the speed of the induction motor. The effectiveness of the proposed system is proved with the help of simulation. The simulation is performed in MATLAB/Simulink. From the simulation results, it shows that the proposed multilevel inverter works properly to generate the multilevel output waveform with minimum number of semiconductor devices. The PI and fuzzy logic controller performances are evaluated using the results which indicate that with the help of controllers the harmonics has been reduced and the speed control of induction motor is achieved under different loading conditions.

Stability Analysis of Parallel Fuzzy P + Fuzzy I + Fuzzy D Control Systems

The study presented in this paper is in continuation with the paper published by the authors on parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP ＋ FI ＋ FD） controller. It addresses the stability analysis of parallel FP ＋ FI ＋ FD controller. The famous＂small gain theorem＂ is used to study the bounded-input and bounded-output （BIBO） stability of the fuzzy controller. Sufficient BIBO-stability conditions are developed for parallel FP ＋ FI ＋ FD controller. FP ＋ FI ＋ FD controller is derived from the conventional parallel proportional plus integral plus derivative （PID） controller. The parallel FP ＋ FI ＋ FD controller is actually a nonlinear controller with variable gains. It shows much better set-point tracking, disturbance rejection and noise suppression for nonlinear processes as compared to conventional PID controller.

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.