Real-time stable self-learning FNN controller using genetic algorithm

A kind of real-time stable self-learning fuzzy neural network (FNN) control system is proposed in this paper. The control system is composed of two parts: (1) A FNN controller which use genetic algorithm (GA) to search optimal fuzzy rules and membership functions for the unknown controlled plant; (2) A supervisor which can guarantee the stability of the control system during the real-time learning stage, since the GA has some random property which may cause control system unstable. The approach proposed in this paper combine a priori knowledge of designer and the learning ability of FNN to achieve optimal fuzzy control for an unknown plant in real-time. The efficiency of the approach is verified by computer simulation.     

A new method of digital simulation for an aircraft gas turbine engine control system

An LD-9 aircraft gas turbine engine with its control system is simulated digitally by a new method, called the ‘method of spare parts’. The computer program of simulation possesses the main capabilities of a real engine altitude test facility and is called a ‘digital engine altitude simulator’. The results of simulation show that the capabilities of this new method are much better than that of the ordinary ‘method of block diagram’. The method can be used for modelling and simulating any type of gas turbine engines or industrial process control systems.     

Simulation of quasi-dimensional combustion model for predicting diesel engine performance

In order to improve the precision of quasi-dimensional combustion model for predicting diesel engine performance and promote the real time operating performance of the simulation model, a new phase-divided spray mixing model is proposed and the quasi-dimensional combustion model of diesel engine working process is developed. The software MATLAB/Simulink is utilized to build the quasi-dimensional combustion model of diesel engine working process, and the performance for diesel engine is simulated. The simulation results agree with experimental data quite well. The comparisons between them show that the relative error of power and brake specific fuel consumption is less than 2.8% and the relative error of nitric oxide and soot emissions is less than 9.1%. By utilization of this simulation model with personal computer, the average computational time for one diesel engine working process is 36 s, which presents good real time operating performance of the model. At the same time, the influence of parameters in calculation of air entrainment on prediction precision of diesel engine’s simulation model is analyzed.     

Large eddy simulation of in-cylinder turbulent flows in a DISI gasoline engine

A large eddy simulation (LES) approach is used to study the in-cylinder turbulent flows of a direct injection gasoline engine, with emphasis on the relationship between the in-cycle turbulent fluctuations and the inter-cycle, i.e. cycle-to-cycle variation (CCV). In total 13 continuous cycles have been calculated, both the single cycle result and phase-averaged result have been compared with our PIV measurements, and reasonable agreements are obtained. Computational results show that, the in-cylinder turbulence is induced primarily by the intake jet. At the early stage of the intake stroke, both the turbulent fluctuations and cyclic variations are intensive and they are of the same magnitude order. While in the compression stroke, the decay of turbulent fluctuations are greater than that of the cyclic variations, and the ratio between them is less than 15%, and the flow field tends to be isotropic. This study demonstrated that LES is capable to describe more realistically details and rules of the in-cylinder turbulent flow and the cycle-to-cycle variations. By using LES coupled with the Q-criterion, the large scale coherent structures in the turbulent flow field can be identified.     

Fuzzy guaranteed cost controller for trajectory tracking in nonlinear systems

In this paper, we propose a fuzzy logic based guaranteed cost controller for trajectory tracking in nonlinear systems. Takagi–Sugeno (T–S) fuzzy model is used to represent the dynamics of a nonlinear system and the controller design is carried out using this fuzzy model. State feedback law is used for building the fuzzy controller whose performance is evaluated using a quadratic cost function. For designing the fuzzy logic based controller which satisfies guaranteed performance, linear matrix inequality (LMI) approach is used. Sufficient conditions are derived in terms of matrix inequalities for minimizing the performance function of the controller. The performance function minimization problem with polynomial matrix inequalities is then transformed into a problem of minimizing a convex performance function involving standard LMIs. This minimization problem can be solved easily and efficiently using the LMI optimization techniques. Our controller design method also ensures that the closed-loop system is asymptotically stable. Simulation study is carried out on a two-link robotic manipulator tracking a reference trajectory. From the results of the simulation study, it is observed that our proposed controller tracks the reference trajectory closely while maintaining a guaranteed minimum cost.     

The design of a controller in Fuzzy Petri net

This paper designs a class of Fuzzy Petri net controller based on the character of place invariant in Petri net. This controller is simple in operation and is easy to put into practice. It has satisfying effects and can provide methods to do research in designing and optimizing the performance of system in solving the dead lock phenomenon in concurrent system.     

Mathematical modelling of a diesel common-rail system

In diesel common-rail systems, the exact knowledge of the injection pressure is important to accurately control the injected diesel mass and thus the combustion process. This paper focuses on the mathematical modelling of the hydraulic and mechanical components of a common-rail system in order to describe the dynamics of the diesel rail pressure. Based on this model, an average model is derived to reduce the model complexity and to allow for a fast calculation of the mass flow into the rail for different crank shaft revolution speeds and openings of the fuel metering unit. The main purpose of this average model is to serve as a basis for a model-based (non-linear) controller design. The stationary accuracy of the models is validated by means of measurement data.     

Drying process of tobacco leaves by using a fuzzy controller

This paper presents the first results from a research project devoted to the application of the fuzzy control based technology to the drying process of tobacco leaves, which the authors are carrying out in the province of Pinar del Rio (Cuba). The fuzzy controller here reported has been designed and implemented by means of a fuzzy rule base constructed from the knowledge of the expert curers taking part in the natural drying process. The preliminary results obtained are very promising.     

Fuzzy值Fuzzy测度的完备化

引入Fuzzy值Fuzzy测度的完备化定义,证明Fuzzy值Fuzzy测度的完备化定理,讨论完备化Fuzzy值Fuzzy测度的某些重要性质。     

Real-time distributed control: A fuzzy and model predictive control approach for a nonlinear problem

Nowadays the study of faults and their consequences has become an issue for highly safety critical computer network systems. How to bound the effects of a fault and how to tackle them in a dynamic system is still an open field. Here, an approach to studying this problem is presented as a hybrid strategy. The use of a multi-model technique from the point of view of real-time systems and intelligent control structure is described, in order to accomplish one challenge: to overcome the problem of the presence of local faults and the respective time delays within a real-time distributed system. This approach is pursued as a reconfigurable strategy according to communication time delays within a real-time distributed system. In fact, it is pursued as a reconfigurable strategy according to communication delays and local faults where the control strategy is modified from several perspectives.     

Application of a rule self-regulating fuzzy controller for robotic deburring on unknown contours

Most metal parts made by machining operations contain burrs, which can be removed by robotic manipulators. Modeling a deburring robot on unknown contours is a relatively difficult task. In this study, we present a novel compliant motion controller that uses a modified on-line rule self-regulating fuzzy control (RSFC) and depends on no mathematical models. In the proposed controller, a Cartesian robot on which a grinding tool is mounted rigidly performs edge following (precision deburring) and chamfering on unknown contours. The manipulator is controlled along the tangential direction of a constrained surface and its cutting force is maintained at a desired level. Experimental results demonstrate the effectiveness of this control strategy in terms of automatically deburring the edges of parts with an unknown geometrical configuration.     

Fuzzy facility location-allocation problem under the Hurwicz criterion

Facility location-allocation (FLA) problem has been widely studied by operational researchers due to its many practical applications. Many researchers have studied the FLA problem in a deterministic environment. However, the models they proposed cannot accommodate satisfactorily various customer demands in the real world. Thus, we consider the FLA problem with uncertainties. In this paper, a new model named α-cost model under the Hurwicz criterion is presented with fuzzy demands. In order to solve this model, the simplex algorithm, fuzzy simulations and a genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, some numerical examples are presented to illustrate the effectiveness of the proposed algorithm.     

Fuzzy level control of a tank with optimum valve movement

This paper presents a fuzzy-based controller chip to control the level of a tank. A motor valve controls the tank level. The significant aim of this paper is to present a controller for minimizing the movement of the motor valve, at the same time, setting the level of the tank at defined points. The advantages of this type of control are to reduce both motor and input valve amortization and to increase their useful lifetime. On the other hand, simple and inexpensive elements are used in order to measure tank level and output flow. This is another advantage of the method. The controller is designed by fuzzy techniques in CMOS technology. The die size of the chip is .     

Selection of parameters for a fuzzy logic controller

The fuzzy logic controller is reviewed and its parameter are explicitly identified. The problem of initial selection and subsequent adjustment of the parameters are discussed in detail by example.     

LPV identification of a turbocharged diesel engine

This work proposes a methodology of identifying linear parameter varying (LPV) models for nonlinear systems. First, linear local models in some operating points, by applying standard identifications procedures for linear systems in time domain, are obtained. Next, a LPV model with linear fractional dependence (LFR) with respect to measured variables is fitted with the condition of containing all the linear models identified in previous step (differential inclusion). The fit is carried out using nonlinear least squares algorithms. Finally, this identification methodology will then be applied to a nonlinear turbocharged diesel engine.     

模糊逻辑在机器人逆运动学求解中的应用

冗余机器人逆运动学求解的方法很多，多数都不能很好的满足实时控制的要求，本文运用模糊逻辑的思想，构造了一种逆运动学求解方法，其计算量较其它方法大大减小，且满足实时控制的要求，仿真结果也证明了该方法的可行性。     

典型模糊控制器的结构分析

为了深入认识和研究模糊控制的本质，本文用统一的形式系统地总结了典型模糊控制结构分析的主要研究成果。     

模糊向量空间中模糊基的判定方法及其维数的计算

本文在（１）的基础上给出了模糊基的另一种构造方法，由此得到了模糊基的判定方法。研究了基的μ值分布状况，最后给出了模糊向量空间维数的计算方法。     

Real-time control of freight forwarder transportation networks by integrating multimodal transport chains

Western European freight forwarders are continually being forced to increase the efficiency of their transportation processes because of the liberalization and deregulation of the European transport market. This paper proposes a new real-time-oriented control approach in order to expand load consolidation, reduce empty vehicle trips, and handle dynamic disturbances. This approach integrates multimodal transportation and multiple transshipments for the first time. Thus, it enables the flexible generation and adaptation of transportation processes. In order to be able to handle occurring disturbances, an optimization procedure that adapts the transportation processes is continually applied. Vehicle breakdowns or deceleration of vehicles, traffic congestion, and street blockages are integrated as possible disturbance scenarios. At the same time, dynamically incoming transportation requests are also dealt with. Moreover, cooperative agreements between freight forwarders, which are gaining increasing importance, are integrated by mapping hubs and external services. The efficiency of the new real-time approach is validated by several computational experiments. In particular, the use of the entire execution time for plan adaptation as well as the integration of multiple transshipments has shown promising results.