A survey of fuzzy control for stabilized platforms

This paper focusses on the application of fuzzy control techniques (fuzzy type-1 and type-2) and their hybrid forms (Hybrid adaptive fuzzy controller and fuzzy-PID controller) in the area of stabilized platforms. It represents an attempt to cover the basic principles and concepts of fuzzy control in stabilization and position control, with an outline of a number of recent applications used in advanced control of stabilized platform. Overall, in this survey we will make some comparisons with the classical control techniques such us PID control to demonstrate the advantages and disadvantages of the application of fuzzy control techniques

Intelligent control of a class of nonlinear systems

The objective of this study is to improve and propose new fuzzy control algorithms for a class of nonlinear systems. In order to achieve the objectives, novel stability theorems as well as modeling techniques are also investigated. Fuzzy controllers in this work are designed based on the fuzzy basis function neural networks and the type-2 Takagi-Sugeno fuzzy models. For a class of single-input single-output nonlinear systems, a new stability condition is derived to facilitate the design process of proportional-integral Mamdani fuzzy controllers. The stability conditions require a new technique to calculate the dynamic gains of nonlinear systems represented by fuzzy basis function network models. The dynamic gain of a fuzzy basis function network can be approximated by finding the maximum of norm values of the locally linearized systems or by solving a non-smooth optimal control problem. Based on the new stability theorem, a multilevel fuzzy controller with self-tuning algorithm is proposed and simulated in a tower crane control system. For a class of multi-input multi-output nonlinear systems with measurable state variables, a new method for modeling unstructured uncertainties and robust control of unknown nonlinear dynamic systems is proposed by using a novel robust Takagi-Sugeno fuzzy controller. First, a new training algorithm for an interval type-2 fuzzy basis function network is presented. Next, a novel technique is derived to convert the interval type-2 fuzzy basis function network to an interval type-2 Takagi-Sugeno fuzzy model. Based on the interval type-2 Takagi-Sugeno and type-2 fuzzy basis function network models, a robust controller is presented with an adjustable convergence rate. Simulation results on an electrohydraulic actuator show that the robust Takagi-Sugeno fuzzy controller can reduce steady-state error under different conditions while maintaining better responses than the other robust sliding mode controllers can. Next, the study presents an implementation of type-2 fuzzy basis function networks and robust Takagi-Sugeno fuzzy controllers to data-driven modeling and robust control of a laser keyhole welding process. In this work, the variation of the keyhole diameter during the welding process is approximated by a type-2 fuzzy-basis-function network, while the keyhole penetration depth is modelled by a type-1 fuzzy basis function network. During the laser welding process, a CMOS camera integrated with the welding system was used to provide a feedback signal of the keyhole diameter. An observer was implemented to estimate the penetration depth in real time based on the adaptive divided difference filter and the feedback signal from the camera. A robust Takagi-Sugeno fuzzy controller was designed based on the fuzzy basis function networks representing the welding process with uncertainties to adjust the laser power to ensure that the penetration depth of the keyhole is maintained at a desired value. Experimental results demonstrated that the fuzzy models provided an accurate estimation of both the welding geometry and its variations due to uncertainties, and the robust Takagi-Sugeno fuzzy controller successfully reduced the penetration depth variation and improved the quality of the welding process

Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control

Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which the magnitude of the force applied to the target is of crucial importance, the force generated by CPAs needs to be accurately controlled. In this paper, a fuzzy logic (FL) controller with a Mamdani inference system is designed to control the blocking force of a trilayer CPA with polypyrrole electrodes, which operates in air. The particle swarm optimization (PSO) method is employed to optimize the controller\u27s membership function parameters and therefore enhance the performance of the FL controller. An adaptive neuro-fuzzy inference system model, which can capture the nonlinear dynamics of the actuator, is utilized in the optimization process. The optimized Mamdani FL controller is then implemented on the CPA experimentally, and its performance is compared with a non-optimized fuzzy controller as well as with those obtained from a conventional PID controller. The results presented indicate that the blocking force at the tip of the CPA can be effectively controlled by the optimized FL controller, which shows excellent transient and steady state characteristics but increases the control voltage compared to the non-optimized fuzzy controllers

A CENTER MANIFOLD THEORY-BASED APPROACH TO THE STABILITY ANALYSIS OF STATE FEEDBACK TAKAGI-SUGENO-KANG FUZZY CONTROL SYSTEMS

The aim of this paper is to propose a stability analysis approach based on the application of the center manifold theory and applied to state feedback Takagi-Sugeno-Kang fuzzy control systems. The approach is built upon a similar approach developed for Mamdani fuzzy controllers. It starts with a linearized mathematical model of the process that is accepted to belong to the family of single input second-order nonlinear systems which are linear with respect to the control signal. In addition, smooth right-hand terms of the state-space equations that model the processes are assumed. The paper includes the validation of the approach by application to stable state feedback Takagi-Sugeno-Kang fuzzy control system for the position control of an electro-hydraulic servo-system

Fuzzy practical exponential tracking of an electrohydraulic servosystem

Cilj ovog rada je da doprinese teorijskoj i praktičnoj primeni fazi logičkog upravljanja korišćenjem koncepta praktičnog praćenja. Predlaže se novi fazi upravljački algoritam za ostvarivanje željenog kvaliteta praćenja jednog elektrohidrauličkog pozicionog servosistema, koji se može naći u mnogim industrijskim uređajima. Fazi logički kontroler je jedan od najjednostavnijih. On koristi samo jednu ulaznu veličinu, sa linearnom metodom zaključivanja. Fazi prateći algoritam upravljanja je zasnovan na principu samoprilagodljivosti. Strukturna karakteristika takvog sistema upravljanja je postojanje dve povratne sprege: globalne, negativne po izlaznoj veličini i lokalne, pozitivne po upravljačkoj veličini. Takva struktura obezbeđuje sintezu upravljanja bez poznavanja unutrašnje dinamike objekta i bez merenja poremećajnih veličina. Predloženi fazi prateći algoritam upravljanja obezbeđuje promenu greške izlazne veličine po unapred definisanom eksponencijalnom zakonu. Prezentuju se rezultati simulacije nelinearnog matematičkog modela hidrauličkog servosistema.The aim of this paper is to contribute to the theoretical and practical applications of fuzzy logic control using practical tracking concept. A new fuzzy control algorithm is proposed to achieve the desired tracking performance of a nonlinear electrohydraulic position servo system, which can be found in many manufacturing devices. The fuzzy logic controller is one of the simplest. It employs only one input, with linear fuzzy inference method. The practical tracking control algorithm is based on the selfadjustment principle. The structural characteristic of such a control system is the existence of two feedback sources: the global negative of the output value and the local positive of the control value. Such a structure ensures the synthesis of the control without the internal dynamics knowledge and without measurements of disturbance values. The proposed fuzzy practical control algorithm ensures the change of the output error value according to a prespecified exponential law. The simulation results of the nonlinear mathematical model of the hydraulic servo system are presented

Fuzzy practical exponential tracking of an electrohydraulic servosystem

Cilj ovog rada je da doprinese teorijskoj i praktičnoj primeni fazi logičkog upravljanja korišćenjem koncepta praktičnog praćenja. Predlaže se novi fazi upravljački algoritam za ostvarivanje željenog kvaliteta praćenja jednog elektrohidrauličkog pozicionog servosistema, koji se može naći u mnogim industrijskim uređajima. Fazi logički kontroler je jedan od najjednostavnijih. On koristi samo jednu ulaznu veličinu, sa linearnom metodom zaključivanja. Fazi prateći algoritam upravljanja je zasnovan na principu samoprilagodljivosti. Strukturna karakteristika takvog sistema upravljanja je postojanje dve povratne sprege: globalne, negativne po izlaznoj veličini i lokalne, pozitivne po upravljačkoj veličini. Takva struktura obezbeđuje sintezu upravljanja bez poznavanja unutrašnje dinamike objekta i bez merenja poremećajnih veličina. Predloženi fazi prateći algoritam upravljanja obezbeđuje promenu greške izlazne veličine po unapred definisanom eksponencijalnom zakonu. Prezentuju se rezultati simulacije nelinearnog matematičkog modela hidrauličkog servosistema.The aim of this paper is to contribute to the theoretical and practical applications of fuzzy logic control using practical tracking concept. A new fuzzy control algorithm is proposed to achieve the desired tracking performance of a nonlinear electrohydraulic position servo system, which can be found in many manufacturing devices. The fuzzy logic controller is one of the simplest. It employs only one input, with linear fuzzy inference method. The practical tracking control algorithm is based on the selfadjustment principle. The structural characteristic of such a control system is the existence of two feedback sources: the global negative of the output value and the local positive of the control value. Such a structure ensures the synthesis of the control without the internal dynamics knowledge and without measurements of disturbance values. The proposed fuzzy practical control algorithm ensures the change of the output error value according to a prespecified exponential law. The simulation results of the nonlinear mathematical model of the hydraulic servo system are presented

Artificial Hydrocarbon Networks Fuzzy Inference System

This paper presents a novel fuzzy inference model based on artificial hydrocarbon networks, a computational algorithm for modeling problems based on chemical hydrocarbon compounds. In particular, the proposed fuzzy-molecular inference model (FIM-model) uses molecular units of information to partition the output space in the defuzzification step. Moreover, these molecules are linguistic units that can be partially understandable due to the organized structure of the topology and metadata parameters involved in artificial hydrocarbon networks. In addition, a position controller for a direct current (DC) motor was implemented using the proposed FIM-model in type-1 and type-2 fuzzy inference systems. Experimental results demonstrate that the fuzzy-molecular inference model can be applied as an alternative of type-2 Mamdani’s fuzzy control systems because the set of molecular units can deal with dynamic uncertainties mostly present in real-world control applications

Neuro-fuzzy software for intelligent control and education

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Major Automação). Faculdade de Engenharia. Universidade do Porto. 200

Multi-objective evolutionary–fuzzy augmented flight control for an F16 aircraft

In this article, the multi-objective design of a fuzzy logic augmented flight controller for a high performance fighter jet (the Lockheed-Martin F16) is described. A fuzzy logic controller is designed and its membership functions tuned by genetic algorithms in order to design a roll, pitch, and yaw flight controller with enhanced manoeuverability which still retains safety critical operation when combined with a standard inner-loop stabilizing controller. The controller is assessed in terms of pilot effort and thus reduction of pilot fatigue. The controller is incorporated into a six degree of freedom motion base real-time flight simulator, and flight tested by a qualified pilot instructor

Fuzzy-logic-based control, filtering, and fault detection for networked systems: A Survey

This paper is concerned with the overview of the recent progress in fuzzy-logic-based filtering, control, and fault detection problems. First, the network technologies are introduced, the networked control systems are categorized from the aspects of fieldbuses and industrial Ethernets, the necessity of utilizing the fuzzy logic is justified, and the network-induced phenomena are discussed. Then, the fuzzy logic control strategies are reviewed in great detail. Special attention is given to the thorough examination on the latest results for fuzzy PID control, fuzzy adaptive control, and fuzzy tracking control problems. Furthermore, recent advances on the fuzzy-logic-based filtering and fault detection problems are reviewed. Finally, conclusions are given and some possible future research directions are pointed out, for example, topics on two-dimensional networked systems, wireless networked control systems, Quality-of-Service (QoS) of networked systems, and fuzzy access control in open networked systems.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61374039, 61473163, and 61374127, the Hujiang Foundation of China under Grants C14002 andD15009, the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany