Local Fuzzy Controllers Research Articles

Intelligent Energy Management Strategy Based on Artificial Neural Fuzzy for Hybrid Vehicle

This paper proposes an intelligent energy management strategy for a hybrid hydraulic–electric vehicle in order to minimize its total energy consumption. It proposes first to model the vehicle total energy consumption and investigates the minimization of an expended energy function, formulated as the sum of electrical energy provided by the on-board batteries and consumed fuel. More precisely, it is proposed in this paper an intelligent controller that shows its capabilities of increasing the overall vehicle energy efficiency and, therefore, minimizing total energy consumption. The proposed strategy consists of an advanced supervisory controller at the highest level (third), which corresponds to a fuzzy system deciding the most appropriate operating mode of the system. In the second level, an intelligent optimal control strategy is developed based on neuro-fuzzy logic. Then, in the first level, there are local fuzzy controllers to regulate vehicle subsystems set points to reach the best operational performance. The advantage of the proposed strategy could be summarized as follows: first, it can be implemented online and second, reduces total energy consumption compared with several traditional methods. The proposed strategy validations are performed using a mix of automotive TruckMaker and MATLAB/Simulink developed software on several (standard or not) driving cycles.

A new approach to control of multivariable systems through a hierarchical aggregation of fuzzy controllers

In this study, the main contribution is a new approach to control multivariable systems by engaging an idea of hierarchical aggregation of multiple fuzzy controllers. A two-level control architecture is developed in which in addition to local fuzzy controllers focused on control of individual subsystems, a higher level controller coordinating and adjusting control actions is designed. The performance of the approach is illustrated with the use of the benchmark problem of the three-tank water control. A statistical comparison is carried where the hierarchical control strategy is compared with the one when a collection of independent individual fuzzy controllers is involved. We demonstrate that the proposed method outperforms “conventional” fuzzy control. Genetic optimization (genetic algorithm) is used in the design of the overall control architecture.

Simulation of Fuzzy Logic Controller for PEM Fuel Cell Based Hybrid Cascaded Multilevel Inverter

The power generated in a proton exchange membrane fuel cell based system depends on the hydrogen and oxygen flows, the regulation of pressure and management of water and heat .One of the important operating variable is the reactant utilization which is directly proportional to fuel cell stack current. When a load is connected to the fuel cell system, the control system must control the flow rate of hydrogen in order to avoid degradation of fuel cell (FC) voltage. Therefore, the objective of the paper is to regulate the input fuel flow to achieve the desired output power. Various control strategies proposed in the literature do not consider the dynamic model of fuel cell system and fuel flow controller. This paper presents the development of fuzzy logic controller for fuel cell based Hybrid Cascaded MultiLevel Inverter(MLI). A MATLAB/SIMULINK control structure for the overall FC based system has been presented which includes the local fuzzy controllers for Interleaved Boost Converter (IBC), HCMLI and the fuel cell. The performance has been compared with PI controller.

Research and Simulation of Vehicle System Based on a Vehicular Waste-Heat Thermoelectric Generator

Study on the thermoelectric effect of electric on vehicle performance problems. Local fuzzy logic control strategy based on, the application of ADVISOR simulation software, The established vehicle model of the hybrid system simulation, the simulation results show that, better improve the vehicle fuel economy and emissions, make the motor work in high load area, high efficiency with low emissions. At the same time system engine, motor, transmission system and battery efficiency can be better maintained.

A hierarchical controller for the vibration of an automotive suspension system via magnetorheological dampers

Reducing the vibration of an automotive magnetorheological (MR) suspension system can contribute greatly to enhancing vehicle performance. However, it is difficult to design a control system that depends on a complicated whole-vehicle vibration model. This paper proposes a hierarchical controller that consists of a control level and a coordination level for heave, roll, and pitch vibration control of a vehicle with an MR suspension system. On the control level, a local fuzzy controller is designed for each quarter-vehicle MR suspension system, based on a hybrid control strategy of skyhook control and groundhook control. On the coordination level, a coordination controller is designed to tune four local independent fuzzy controllers by adjusting their output parameters on the basis of system feedback. A test and control system for MR suspensions is set up and implemented on a minibus equipped with four controllable MR dampers. The results on random rough roads confirm that the hierarchical controller can reduce automotive vertical vibration, roll motion, and pitch motion more effectively than a passive suspension or an MR suspension using a hybrid control strategy. It achieves better ride comfort and automobile handling stability, although data for bump input indicate that the hierarchical controller does not decrease automotive vertical vibration more effectively than hybrid control or a passive system. However, it yields better results in decreasing pitch and roll motions.

Integrated Longitudinal and Lateral Control System Design for Autonomous Vehicles

AbstractThis paper presents the design of an integrated longitudinal and lateral controller for autonomous vehicles. Firstly, the problem of longitudinal controller design is to concentrate on the design of spacing policy and its associated control law. A Safety Spacing Policy (SSP) is proposed, and a sliding mode controller is designed. String stability as well as traffic flow stability issues of the proposed SSP are studied. It's shown that the SSP can provide stable string operation and stable traffic flow under certain conditions. Secondly, a multi-model fuzzy controller is proposed to cope with the vehicle lateral control. This multi-model fuzzy controller contains four local fuzzy controllers which correspond to four velocity intervals. In order to avoid the undesired peaks which may appear during the commutation of the different local controllers, a fusion block based on a fuzzy type strategy is designed. Finally, the integration of the longitudinal and lateral controllers is presented, and the simulation results show that the proposed controller has good performances under different scenarios.

Fuzzy-model-based Control Systems Using Fuzzy Combination Techniques

This paper presents a fuzzy combined model and a fuzzy combined controller to handle nonlinear systems. A fuzzy combination of some local fuzzy models is employed to represent a nonlinear system. Based on this fuzzy combined model, a fuzzy controller combining some local fuzzy controllers is proposed to control the nonlinear system. Conditions are derived to guarantee the system stability. By using the fuzzy combination technique, the stability analysis is reduced to investigating only the stability of the local fuzzy control systems. The system that combines the local fuzzy systems will then be guaranteed stable. This property reduces the difficulty of finding the solution to the stability conditions even though the fuzzy combined model has effectively distributed the complex nonlinearity over the local fuzzy models. Furthermore, any sharp changes in the system states and control signals caused by the switching activities between local fuzzy control systems are smoothed out by the fuzzy combined controller. An application example will be given to show the merits of the proposed approach.

05/02693 Fuzzy control with random delays using invariant cones and its application to control of energy processes in microelectromechanical motion devices

In this paper, a class of microelectromechanical systems described by nonlinear differential equations with random delays is examined. Robust fuzzy controllers are designed to control the energy conversion processes with the ultimate objective to guarantee optimal achievable performance. The fuzzy rule base used consists of a collection of r fuzzy IF-THEN rules defined as a function of the conditional variable. The method of the theory of cones and Lyapunov functionals is used to design a class of local fuzzy control laws. A verifiably sufficient condition for stochastic stability of fuzzy stochastic microelectromechanical systems is given. As an example, we have considered the design of a fuzzy control law for an electrostatic micromotor.

Fuzzy Combination of Fuzzy and Switching State-Feedback Controllers for Nonlinear Systems Subject to Parameter Uncertainties

This paper presents a fuzzy controller, which involves a fuzzy combination of local fuzzy and global switching state-feedback controllers, for nonlinear systems subject to parameter uncertainties with known bounds. The nonlinear system is represented by a fuzzy combined Takagi-Sugeno-Kang model, which is a fuzzy combination of the global and local fuzzy plant models. By combining the local fuzzy and global switching state-feedback controllers using fuzzy logic techniques, the advantages of both controllers can be retained and the undesirable chattering effect introduced by the global switching state-feedback controller can be eliminated. The steady-state error introduced by the global switching state-feedback controller when a saturation function is used can also be removed. Stability conditions, which are related to the system matrices of the local and global closed-loop systems, are derived to guarantee the closed-loop system stability. An application example will be given to demonstrate the merits of the proposed approach.

Fuzzy control with random delays using invariant cones and its application to control of energy processes in microelectromechanical motion devices

In this paper, a class of microelectromechanical systems described by nonlinear differential equations with random delays is examined. Robust fuzzy controllers are designed to control the energy conversion processes with the ultimate objective to guarantee optimal achievable performance. The fuzzy rule base used consists of a collection of r fuzzy IF-THEN rules defined as a function of the conditional variable. The method of the theory of cones and Lyapunov functionals is used to design a class of local fuzzy control laws. A verifiably sufficient condition for stochastic stability of fuzzy stochastic microelectromechanical systems is given. As an example, we have considered the design of a fuzzy control law for an electrostatic micromotor.

Control of a six‐axis pneumatic robot

AbstractThe article presents a control system for a six‐degree of freedom (DOF) anthropomorphic robot powered entirely by pneumatic actuators. The control uses digital valves driven by pulse width modulation (PWM) to regulate air flow to the actuators. The robot is equipped with position sensors, which are used to provide feedback signals for local fuzzy controllers actuating the individual servoaxes. Trajectory tracking is guided by a module, which computes the robot's inverse kinematics, generating the references for the servoaxes. Experimental results illustrated in the article indicate that the controller is effective both in controlling single axes, and in tracking a trajectory. © 2002 Wiley Periodicals, Inc.

Alternative stabilisation design for fuzzy systems

In stabilising fuzzy systems, designers frequently suffer from the existence of the common P. An additional controller is introduced into each local fuzzy control such that the common P does not need to satisfy all Lyapunov equations. A practical system is given to illustrate its usefulness.

Fuzzy Control of Large Scale Systems

The scheme of fuzzy control for large scale systems - " Multilevel Fuzzy Control " (MFC) is proposed, and the methods to design the " Local Fuzzy Controller " (LFC) and the " Whole Fuzzy Coordinator " (WFC) are given.