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

Composite Disturbance Filtering: A Novel State Estimation Scheme for Systems With Multi-Source, Heterogeneous, and Isomeric Disturbances

State estimation has long been a fundamental problem in signal processing and control areas. The main challenge is to design filters with ability to reject or attenuate various disturbances. With the arrival of big data era, the disturbances of complicated systems are physically multi-source, mathematically heterogenous, affecting the system dynamics via isomeric (additive, multiplicative and recessive) channels, and deeply coupled with each other. In traditional filtering schemes, the multi-source heterogenous disturbances are usually simplified as a lumped one so that the "single" disturbance can be either rejected or attenuated. Since the pioneering work in 2012, a novel state estimation methodology called {\it composite disturbance filtering} (CDF) has been proposed, which deals with the multi-source, heterogenous, and isomeric disturbances based on their specific characteristics. With the CDF, enhanced anti-disturbance capability can be achieved via refined quantification, effective separation, and simultaneous rejection and attenuation of the disturbances. In this paper, an overview of the CDF scheme is provided, which includes the basic principle, general design procedure, application scenarios (e.g. alignment, localization and navigation), and future research directions. In summary, it is expected that the CDF offers an effective tool for state estimation, especially in the presence of multi-source heterogeneous disturbances

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 control of the dual-stage feeding system consisting of a piezoelectric actuator and a linear motor for electrical discharge machining

Gap width is an important factor that affects material removal rate, surface finish, and machining stability in electrical discharge machining processes. This research is to develop a novel control method for a new hybrid positioning system which consists of a linear motor and a piezoelectric actuator for high-efficiency electrical discharge machining processes. In the new system, the linear motor provides the macro feeding while the piezoelectric actuator feeds the workpiece in micro scale at high frequency. To reduce the delay caused by separate movements of the linear motor and piezoelectric actuator, a new control algorithm was developed to synchronize the movements of the motor and piezoelectric actuator. A fuzzy control system was used to control the feeding process. Piezoelectric actuator position and its speed were selected as the fuzzy inputs, while the fuzzy output was the linear motor speed. Cutting experiments were conducted, and results show that the fuzzy system is more powerful than the conventional algorithm and the new algorithm with constant motor speed. An increase in material removal rate of 1.6 times was achieved using the proposed fuzzy control algorithm

The generation of dual wavelength pulse fiber laser using fiber bragg grating

A stable simple generation of dual wavelength pulse fiber laser on experimental method is proposed and demonstrated by using Figure eight circuit diagram. The generation of dual wavelength pulse fiber laser was proposed using fiber Bragg gratings (FBGs) with two different central wavelengths which are 1550 nm and 1560 nm. At 600 mA (27.78 dBm) of laser diode, the stability of dual wavelength pulse fiber laser appears on 1550 nm and 1560 nm with the respective peak powers of -54.03 dBm and -58.00 dBm. The wavelength spacing of the spectrum is about 10 nm while the signal noise to ratio (SNR) for both peaks are about 8.23 dBm and 9.67 dBm. In addition, the repetition rate is 2.878 MHz with corresponding pulse spacing of about 0.5 μs, is recorded

System integration for a novel positioning system using a model based control approach

This dissertation presents a model-based approach to perform system integration of a novel positioning sensing method, termed \u27Direct Position Sensing.\u27 Direct Position Sensing can actively monitor the planar position changes of motion control devices without the dependency of the conventional position sensor combined with kinematic model to estimate the planar position. Instead, Direct Position Sensing uses the technology of computer vision and digital display to directly monitor the planar position displacement of a motion control device by actively tracking the desired position of the device based on the displayed target showed on the digital screen. The integration of the computer vision as the feedback system to the motion controller, introduces intermittency and latency in the controller\u27s feedback loop. In order to integrate the slower computer vision sensor to the motion controller, a model-based controller architecture, Smith Predictor approach was first implemented to the Direct Position Sensing system. The Smith Predictor uses a mathematical plant model that is running in parallel with the actual plant so that the model predicts the plant output when the actual output of the system is unavailable. Due to the intermittency feedback of the system, a path prediction algorithm was developed to minimize the model residual during the intermittent feedback so that the tracking performance of the system can be improved. Furthermore, a model input corrector was also developed to correct the control action to the plant model based on the model residual to enhance the path prediction. Simulations and hardware experiments results show that the model-based strategy provides improved tracking performance of the system when latency and intermittency exist in the controller feedback loop