Fuzzy Proportional Plus Integral Research Articles

A Supervisory Control Algorithm of Hybrid Electric Vehicle Based on Adaptive Equivalent Consumption Minimization Strategy with Fuzzy PI

This paper presents a new energy management system based on equivalent consumption minimization strategy (ECMS) for hybrid electric vehicles. The aim is to enhance fuel economy and impose state of charge (SoC) charge-sustainability. First, the relationship between the equivalent factor (EF) of ECMS and the co-state of pontryagin’s minimum principle (PMP) is derived. Second, a new method of implementing the adaptation law using fuzzy proportional plus integral (PI) controller is developed to adjust EF for ECMS in real-time. This adaptation law is more robust than one with constant EF due to the variation of EF as well as driving cycle. Finally, simulations for two driving cycles using ECMS are conducted as opposed to the commonly used rule-based (RB) control strategy, indicating that the proposed adaptation law can provide a promising blend in terms of fuel economy and charge-sustainability. The results confirm that ECMS with Fuzzy PI adaptation law is more robust than ECMS with constant EF as well as PI adaptation law and it achieves significant improvements compared with RB in terms of fuel economy, which is enhanced by 4.44% and 14.7% for china city bus cycle and economic commission of Europe (ECE) cycle, respectively.

Smart Wheelchair Stair Lift Using RFID Detection Method and Fuzzy-PI with PLC Ladder Control

This paper presents the development of wheelchair stair lift with an intelligent control system that aim to apply for helping the mobility of ageing, disabled and wheelchair people who are suffered from any inconvenience causes of building stair usages and also served for the fire stair evacuation path in the same time. The stair lift is controlled by PLC with the fuzzy proportional plus integral (F-PI) controller combined on their driver functions called as fuzzy ladder control which can generate an appropriate setting voltage and torque to maintain a target position and speed of stair lift when it move along the stair path with shorter time of accessing, travelling and dwelling process. To gain the precise value of target position and speed , the DC motor drive with smart steering gear box that are coupled on two stair guide rails is designed for acting easily as a linear moving control by F-PI controller. By several tests of the unknown characteristics of wheelchair users, the F-PI controller can solve this kind of problems with more efficiency because of the main advantage of fuzzy logic is that no mathematical model is required but can be achieved higher performance with the effective tuning parameters especially in an initial setting process. For more efficiency, the RFID detection method is applied to use for identifying and automatically accessing of wheelchair users who want to use this stair lift with some important data such as their name, age or weight as the prior knowledge data of the initial setting process. By applying the proposed system, performance has been improved by mathematical analysis, solid work simulation, matlab simulation and several tests at laboratory room and real building stair. The results are better than the conventional PI control with more accuracy, correctly, smoothly, stability and safety. Finally, the all system can work well as design concept and the future work will further improve the system performance both in mechanical and control part for more practical to use in any real stair usage.

Design of a Novel Fuzzy PI Controller Based on Artificial Bee Colony Algorithm for VSC-HVDC Transmission Link

This paper presents a continuous time state space model for a VSC-HVDC transmission link in the d-q reference frame. An Artificial Bee Colony (ABC) algorithm based Fuzzy proportional plus integral (FPI) controller is proposed for a decoupled back to back VSC-HVDC transmission link single machine power system. Here, the ABC approach is used for selecting the nonlinear variable gain parameters of scaling factors of Fuzzy controller to enhance its performance. Simulation result has been presented to show and validate the efficiency of new approach for damping oscillations over a wide range of operating conditions and compared with the conventional PI controller tuned by Ziggler-Nichol technique, and Fuzzy PI controller without optimization. It has been found that the proposed controller is quite effective in enhancing the power system dynamic stability significantly.

Speed and torque control of permanent magnet synchronous motor using hybrid fuzzy proportional plus integral controller

This paper presents an improved fuzzy logic controller (FLC) for a permanent magnet synchronous motor (PMSM) for high performance industrial drive applications. The performance of the PMSM using proportional plus integral (PI) controllers and general fuzzy controllers are poor under load disturbances and transient conditions. The FLC is developed to have a smaller computational burden which makes it suitable for real time implementation, particularly at constant speed operating conditions. Hybrid control has the advantage of integrating a superiority of two or more control techniques for better control performances. A fuzzy controller offers better speed responses for startup and large speed errors. If the nature of the load torque is varied, the steady state speed error of the PMSM drive with an FLC becomes significant. To enhance the performance of the system, a new control method, hybrid fuzzy PI control and accelerated fuzzy PI control is proposed. The effectiveness of the proposed method is verified by a simulation based on MATLAB. The proposed hybrid fuzzy controller has good adaptability over load toque variation and can maintain constant speed.

New self-tuning fuzzy PI control of a novel doubly salient permanent-magnet motor drive

In a doubly salient permanent-magnet (DSPM) motor drive, it is difficult to get satisfied control characteristics by using a normal linear proportional plus integral (PI) controller due to the high nonlinearity between speed and current or torque. Hence, a new self-tuning fuzzy PI controller with conditional integral, which is performed by a single-chip N87C196KD, is proposed. The initial parameters of the controller are optimized by using genetic arithmetic. Simulation and experiments on the newly proposed 8/6-pole DSPM machine have shown that the proposed new self-tuning fuzzy PI controller offers better adaptability than the normal linear PI control and that the developed motor drive offers better steady-state and dynamic performances.

A comparative analysis of fuzzy logic and PI speed control in high-performance AC drives using experimental approach

One of the frequently discussed applications of artificial intelligence in motion control is the replacement of a standard proportional plus integral (PI) speed controller with a fuzzy logic (FL) speed controller. Regardless of all the work, it appears that a thorough comparison of the drive behavior under PI and FL speed control is still missing. This paper attempts to fill in this gap, by providing an in-depth comparison of operation of a vector-controlled permanent-magnet synchronous motor, using at first an experimental rig. Speed responses, obtained under PI and FL speed control, are recorded and compared for a variety of operating conditions. The transients studied include response to a large step speed command from standstill with nominal inertia and an increased inertia, response to small step speed reference change, and response to step load torque application. The transient behavior is examined for various initial speed settings, so that a thorough comparison is enabled. Experimental results are further supplemented with a set of simulation results, obtained using a different permanent-magnet machine and a different FL controller. Better generalization of the results is enabled in this way. It is shown that superiority of the FL speed control is less pronounced than it is often portrayed in the literature on the basis of limited comparisons. Indeed, in a number of cases, PI speed control provides a superior speed response.

Robust PI controller design for nonlinear systems via fuzzy modeling approach

The design problem of proportional and proportional-plus-integral (PI) controllers for nonlinear systems is studied. First, a Takagi-Sugeno fuzzy model with parameter uncertainties is used to approximate the nonlinear systems. Then a numerically tractable algorithm based on the technique of iterative linear matrix inequalities is developed to design a proportional (static output feedback) controller for the robust stabilization of the system in Takagi-Sugeno fuzzy model. Thirdly, we transform the problem of PI controller design to that of proportional controller design for an augmented system and thus bring the solution of the former problem into the configuration of the developed algorithm. Finally, the proposed method is applied to the design of robust stabilizing controllers for the excitation control of power systems. Simulation results show that the transient stability can be improved by using a fuzzy PI controller when large faults appear in the system, compared to the conventional PI controller designed by using a linearization method around the steady state.

Adaptive fuzzy power control for CDMA mobile radio systems

Introduces a new application of fuzzy-logic control (FLC) to power control in a DS/CDMA cellular system over mobile fading radio channels. The conventional feedback power control algorithms allow the base station to send a power command to raise/lower each user transmitting signal power level by a fixed power step and then keep the received powers almost equal. The fixed-step approach is actually an integral control whose power increment is determined according to the bang-bang-like control policy. However, this control scheme suffers from several disadvantages. To tackle these difficulties, a fuzzy proportional-plus-integral (PI) control, whose input variables are the received power error and error change, is introduced to determine each user's transmitting power in order to maintain simultaneously all users' signal power received at the base station nearly equal and to achieve better system stability and control performance. The derivation of the fuzzy PI control has been carried out by analyzing both the closed-loop steady state behavior and transient response of the system with a priori knowledge of the dynamics of the CDMA mobile fading channels. In fuzzy control, linguistic descriptions of actions in controlling a process are represented as fuzzy rules. This fuzzy-rule base is used by an inference mechanism in conjunction with some knowledge of the states of process in order to determine control actions. These actions would lead to the fast rise time, minimum overshoot, and small root-mean-squared (rms) tracking error. Additional advantages of fuzzy PI control over conventional control theories are discussed.

Adaptive fuzzy proportional integral power control for a cellular CDMA system with time delay

We investigate the use of fuzzy logic control techniques for adaptive power control in a direct-sequence code-division multiple-access (DS/CDMA) cellular system over the mobile fading radio channels with propagation time delay. A fuzzy PI (proportional-plus-integral) control whose input variables are the received power error and error change is introduced to determine each user transmitting power in order to simultaneously equalize all users' signal powers received at the base station and achieve better system stability and control performance. This control strategy can ensure long loop transmission delays without causing the system to become unstable. According to the well-known phase-plane method, the derivation of the fuzzy PI control has been carried out by analyzing the response areas, cross-over, and extreme points of the system step response with apriori knowledge of the dynamics of the CDMA mobile fading channels. For a long time-delay fading process, a methodology is developed to modify the rule base to contain the delay information for reducing the deadtime effects of the process. Moreover, the additional advantages of fuzzy PI control over conventional control theories are: increased robustness in spite of interference and the ability to handle the time-delay process whose parameters are not accurately known. Simulation results show that a good performance can be achieved both in RMS tracking error and traffic capacity by use of fuzzy PI power control, especially in poor interuser interference and long time delay conditions.