Fuzzy Switching Control Research Articles

Online neural network-based model reduction and switching fuzzy control of a nonlinear large-scale fractional-order system

Online neural network-based model reduction and switching fuzzy control of a nonlinear large-scale fractional-order system

Multispectral Target Tracking with Robust Correlation and Optimal Position Prediction

Object tracking using only visible-light sensor is usually problematic when facing some challenging scenes related to a complex environment like darkness, strong light, rain, fog, etc. In this paper, we have taken images, both thermal and visible light spectrum, from RGBT234 dataset as inputs for our proposed tracker which works as follows: First, the single shot multibox detector (SSD) is proposed to produce automatically the initial position of the target for visible and infrared modes. Second, a switching fuzzy logic controller (FLC) has been proposed to ensure automatic selection and switching between tracking modes (visible-light or thermal infrared spectrum) when a new environment is detected using confidence measures on some relevant features of the frames for each mode. Finally, to improve the kernelized correlation filter as a base tracker and overcome the limitation of the multimodal visual tracking, especially during tracking mode switching when visual information is not available, robust optimal smooth variable structure filter (SVSF) is proposed. Experiments on the recently public benchmark RGB-T234 demonstrate the effectiveness of our proposed method when compared to other state-of-the-art trackers.

Research on Multi-Objective Compound Energy Management Strategy Based on Fuzzy Control for FCHEV

A compound energy management strategy is proposed to improve the fuel cell’s durability and the economy of fuel cell hybrid electric vehicles (FCHEV). A control strategy that combines fuzzy control and switching control is proposed, taking into account factors that affect the fuel cell’s durability and the supercapacitor park’s safety. To smooth the output power of fuel cells under frequent variable load conditions, a moving average filtering algorithm has been added. Finally, co-simulation using Advisor and Matlab/Simulink under the World Light Vehicle Test Cycle (WLTC) compares the proposed strategy with fuzzy control and power following strategies. The experimental results show that the proposed strategy ensures the safety of the supercapacitor park and improves the durability of the fuel cell while improving the economy of the whole vehicle.

Fixed-time stabilization of IT-2 T-S fuzzy control systems with discontinuous interconnections: Indefinite derivative Lyapunov method

Using the interval type-2 Takagi–Sugeno (IT-2 T-S) fuzzy control method, this paper formulates a class of non-autonomous interconnected dynamical system (IDS) with discontinuities. Under the differential inclusion (DI) framework, the fixed-time stabilization (FXTS) problem is studied via indefinite derivative Lyapunov approach, where the time-derivative of constructed Lyapunov function doesn’t have to be negative/semi-negative. By designing novel IT-2 T-S fuzzy switching control protocol possessing time-varying control gain coefficients, several sufficient stabilization conditions are obtained to determine the system’s stability in fixed time. Furthermore, the settling time (ST) of FXTS is estimated. Due to the time-varying property of control gain coefficients and indefiniteness of system’s parameters, the advantage of the IT-2 T-S fuzzy switching control protocol designed in this paper is that its control gain coefficients are not only more flexible, but also can affect the estimation of ST. Finally, the designed control protocols and FXTS results are confirmed by numerical example.

Fuzzy sliding mode control of piezo-driven stage.

The motion stage with flexible hinges as a guiding mechanism can realize nanometer-level precision positioning. This stage uses a piezoelectric (PZT) actuator as the driving unit. In order to describe the mechanical characteristics of this piezo-driven stage, a double-parallel four-bar mechanism based on eight flexible hinges is analyzed. The natural frequency and modal of this stage are analyzed with the finite element method. In order to reduce the hysteresis influence of the PZT actuator, the model parameters based on the Bouc-Wen hysteresis model are identified by using the particle swarm optimization algorithm, and the boundedness of the hysteresis phenomenon is determined by this model. On this basis, the PZT hysteresis is regarded as a disturbance, and a proportional-integral-differential (PID)-type fuzzy sliding mode control (FSMC) is designed. Taking errors and the derivation in the errors as input and the parameters of the PID sliding surface as the output, the fuzzy sliding mode function is constructed. In addition, taking the absolute value of the sliding mode function as the input and the adjustment factor of the switching control as the output, the fuzzy switching control is constructed. Finally, the effectiveness of the FSMC is verified through several experiments.

A multi-level fuzzy switching control method based on fuzzy multi-model and its application for PWR core power control

As the characteristics of complex system are usually multivariable, nonlinear, and wide operating range, it is difficult to achieve ideal control of complex nonlinear systems. To solve the problem, a multi-level fuzzy switching control method based on fuzzy multi-model is designed. The PD controller, the fuzzy controller and the fuzzy-PID controller are selected as the sub-controllers, and T-S fuzzy rules are used to realize smooth switching between sub-controllers. The multi-level fuzzy switching controller is designed as the parent controller. In this paper, the local model of PWR core is established by selecting five linear models at power levels of 20% FP, 40% FP, 60% FP, 80% FP and 100% FP, and the fuzzy multi-model of PWR core is established by weighting the five local models with triangular membership function. Then, the multi-level fuzzy switching controller with the core fuzzy multi-model is used for core power control, and the power control simulation of PWR core is carried out. The results show that the multi-level fuzzy switching controller designed based on the core fuzzy multi-model is suitable for PWR core power control.

Fuzzy Sampled-Data Control for DFIG-Based Wind Turbine With Stochastic Actuator Failures

The stabilization of fault-tolerant control problem for the doubly fed induction generator (DFIG)-based wind turbine (WT) model has been investigated with stochastic actuator faults by incorporating a Takagi-Sugeno (T-S) fuzzy technique. To depict such stochastic actuator faults, the proposed model is incorporated with Markovian switching parameters for denoting various faulty modes. Besides, a novel fault-tolerant fuzzy switching control with sampled-data (SD) inputs has also been employed for eliminating the stochastic faults so that the stabilization of the system and an optimal H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> level could be ensured simultaneously. Furthermore, the stability conditions are derived by employing fuzzy Lyapunov-Krasovskii functionals (LKFs), whose matrices are membership dependent functions. Finally, the proposed control method for the stabilization problem is validated through a numerical simulation performed on the DFIG-based WT model.

A control approach to regulate formaldehyde concentrations indoors a gross anatomy laboratory via a switched fuzzy logic system

In this paper, a switching fuzzy logic controller (SFLC) was proposed to reduce formaldehyde (FA) concentrations in a gross anatomy laboratory. At large vapor levels a hasty fuzzy logic controller (HFLC) first is activated to decrease the hazardous concentration. A switching criterion enables a second precise fuzzy logic controller (PFLC) that smoothly takes the systems output near the desired set-point. An adaptive algorithm allowed the SFLC to select the proper number of extraction systems from 3, 6, or 9 devices. The simulated performance of the fuzzy controller was satisfactorily decreasing and stabilizing the FA concentration even in the presence of parametric disturbances at set-point values of 0.37 mg/m3 and 0.29 mg/m3. However, the performance of the SFLC deteriorated as the number of dissection tables >35. The results showed that SFLC can be considered as a promising strategy to ensure indoor air quality in gross anatomy laboratories.

Enhanced multi-instant fuzzy switching control of nonlinear system with unreliable communication channels

The problem of enhancing the adaptability against unreliable communication channels for fuzzy system is investigated by proposing a new multi-instant fuzzy switching controller with a more flexible switching manner. Compared with recent methods in the reported literature, more switching modes have been designed according to the updated information at each sampling instant and thus much more freedom can be created by introducing and assigning additional variables for all the possible switching modes. As a result, the adaptability against unreliable communication channels can be enhanced from two aspects: for the same health quality of communication channels, much larger controllable domain can be provided; or for the same system parameters, a worse health quality of communication channels can be affordable. Finally, several advantages over previous fuzzy approaches are verified by means of numerical simulations.

Superior Performance of Switched Fuzzy Control Systems: An Overview and Simulation Experiments

This article gives a brief overview of the basic notions of switched fuzzy systems, their model construction and stability analysis, followed by the proposed concepts for building simulation algorithms for this type of systems. Using these concepts we have shown the whole process of modelling, stability analysis and design of stabilizing switching fuzzy logic controllers for the hovercraftvehicle as a typical nonholonomic system. MATLAB Simulator (Simulink model) and special MATLAB functions for the switching fuzzy controller of the hovercraft vehicle, along with the numerous simulation results, verify the correctness of the proposed concepts. Using this typical nonholonomic system we have also explored the good performance of switched fuzzy systems in comparison to the ordinary T-S fuzzy systems.

Enhanced Switching Stabilization of Discrete-Time Takagi–Sugeno Fuzzy Systems: Reducing the Conservatism and Alleviating the Online Computational Burden

This article proposes an enhanced switching stabilization of Takagi-Sugeno fuzzy systems by developing a new fuzzy switching controller. A distinctive feature of the proposed approach is the enhanced ability to utilize the updated information of the normalized fuzzy weighting functions at each sampling point. Compared with those recent results in the literature, two key performance indexes, i.e., reducing the conservatism and alleviating the online computational burden, can be improved together while the off-line computational burden increases as a tradeoff but is still affordable from the point of algorithmic complexity. As a result, the efficiency of fuzzy stabilization is enhanced and thus its scope of application can be enlarged much more than before. Finally, the superiority of the proposed approach is illustrated by some simulation comparisons.

Robust Diving Motion Control of an Autonomous Underwater Vehicle Using Adaptive Neuro-Fuzzy Sliding Mode Technique

This paper presents an adaptive neuro-fuzzy sliding mode control (ANFSMC) scheme for diving motion control of an autonomous underwater vehicle (AUV) in the presence of parameter perturbations and wave disturbances. In the derivation of diving motion equations of an AUV, the pitch angle of the vehicle is often assumed to be small in the vertical plane. This is a quite strong restricting condition in underwater operations and may cause serious modeling inaccuracies in AUV's dynamics. The problem of nonlinear uncertain diving behavior with restricting assumption on the pitch angle directly is resolved by a neural network (NN) based equivalent control. The online NN estimator is designed to approximate a part of the equivalent control term containing nonlinear unknown dynamics and external disturbances. Subsequently, corrective control based on an adaptive fuzzy proportional-integral control is applied to eliminate the chattering phenomenon by smoothing the switching signal and also compensate structured uncertainties. The weights of NN are updated such that the corrective control signal of the ANFSMC converges towards zero. The adaptive laws are developed to compute coefficients of PID sliding manifold and adjust the gain of fuzzy switching control. The simulation results are presented to shows the efficacy of the control performance.

Research on dual‐mode switching fuzzy PID servo algorithm based on micro‐linear motor

Micro-linear motor, is the key feed components which is based on macro–micro-motion control technology, the accuracy of its movement directly determines the accuracy of ultra-precision machining level. Based on the study of the open servo characteristics of POWER program multiple axis controller (PMAC), a fuzzy proportional integral derivative (PID) composite control technology is applied to the servo control of the motor. The fuzzy control is used to improve the response speed and dynamic performance of the system, and the precise PID control is used to realise the precise position control. In this study, based on the analysis of linear motor installation and load characteristics, the use of smooth switching fuzzy PID composite control algorithm is applied to the micro-feed motor control. Due to the introduction of the smoothing weighting function, the composite fuzzy PID servo control mode of dual mode switching is implemented without disturbance switching. Finally, the effect of the control algorithm is verified by experiments, especially in the case of small errors, this algorithm still reflects the ability to adapt to the impact of interference.

H∞ switching fuzzy control of solar power generation systems with asymmetric input constraint

AbstractThis paper aims at presenting a maximum power point tracking (MPPT) controller for photovoltaic (PV) systems subject to asymmetric input constraint. Indeed, the output voltage of the DC‐DC converter used for adjusting the photovoltaic output power can be controlled by means of variation of duty ratio limited between 1 and 0. The control design goal is to improve the efficiency of PV systems under asymmetric saturation of duty ratio. To achieve this goal, first, a Takagi‐Sugeno (T‐S) fuzzy model is used to represent the nonlinear behavior of the PV system. A T–S reference model is employed to give the ideal state direction which must be followed. To achieve a good steady state tracking, the integral of the state tracking error is used to define an extended system state vector. Second, the input characteristic is partitioned into several regions. In each region, the asymmetric saturation function can be considered as a symmetric saturation function. Furthermore, H∞ stabilization conditions for the resulting switching fuzzy control of the PV system under actuator saturation are formulated in term of linear matrix inequalities (LMI) using the Lyapunov approach. Simulation results are exhibited to demonstrate the effectiveness of the proposed design method.

Stable Switching Control Strategy of the Support Pressure and Velocity of Shield Machine Gripper Shoes

An electro‐hydraulic servo position and pressure compound control method was investigated considering the working principle of a hydraulic stepping motor of a shield machine gripper shoe and its practical working characteristics in the supporting process. The control targets were to improve the support efficiency and reduce the disturbance of gripper shoes on the surrounding rock. In this method, a fuzzy switching controller was used to switch between electro‐hydraulic position control and electro‐hydraulic pressure control. Numerical and prototype simulation experiments were conducted on the control method. The theoretical analysis and experimental results showed that the control method could effectively convert the gripper shoes from an unsupported state to a supported state in a short amount of time, as well as realize surge‐free switching between position control and pressure control. Thus, disturbance of the gripper shoes on the surrounding rock could be reduced. The results of this study provide a theoretical basis for research on control strategies of hydraulic stepping propulsion of shield machines.

Relaxed Real-Time Scheduling Stabilization of Discrete-Time Takagi–Sugeno Fuzzy Systems via An Alterable-Weights-Based Ranking Switching Mechanism

The problem of relaxed real-time scheduling stabilization of nonlinear systems in the Takagi–Sugeno fuzzy model form is studied by proposing a new alterable-weights-based ranking switching mechanism. Thanks to the proposed alterable-weights-based ranking switching mechanism, a new fuzzy switching controller is developed with a set of activated modes that are adjusted by the real-time joint distribution of normalized fuzzy weighting functions. It is worth noting that those existing real-time scheduling stabilization results can be improved without introducing additional offline computational burden while solving control gain matrices. More importantly, less conservative stabilization conditions lead to a smaller degree of the fuzzy homogenous polynomially parameter-dependent switching controller, and thus, less online computational burden is required in the actual application. The effectiveness and superiority of the proposed method are verified by two simulation examples in the numerical section.

Interval type-2 regional switching T–S fuzzy control for time-delay systems via membership function dependent approach

This paper investigates the stabilization problem of the interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy-model-based control systems with time delay. We extend the type-1 switching T–S fuzzy model to deal with the IT2 T–S fuzzy model, and the new constructed model is defined as the IT2 regional switching T–S fuzzy model in this paper. Furthermore, a new type state feedback controller, namely IT2 regional switching fuzzy controller which switches according to system states, is designed to perform the control process. Then, based on the piecewise membership functions, the membership function dependent approach is adopted specifically for time-delay systems, and hence several stability criteria are derived by utilizing the relaxed Lyapunov–Krasovskii functional. Since the membership function dependent approach considers more information of lower and upper membership functions, the conservatism of the stability conditions is reduced. Finally, two numerical examples are provided to demonstrate that the theoretical results are effective and the membership function dependent approach plays an important role in relaxing the stability criteria.

Finite-Time Stabilization of a Class of T–S Fuzzy Systems

This paper considers the finite-time stabilization problem for a class of nonlinear systems that can be described by Takagi–Sugeno (T–S) fuzzy models. We propose a novel finite-time switching fuzzy control scheme for T–S fuzzy models, and the scheme is based on the Lyapunov stability theory and the control Lyapunov function technique. It is shown that the finite-time fuzzy controller and the quadratic control Lyapunov function can be obtained at the same time by solving a set of linear matrix inequalities, which can be easily facilitated by available software packages. It is also shown that the potential control law singularity can be avoided with the proposed control scheme. Unlike many existing approaches to finite-time stabilization of general nonlinear systems, the proposed approach does not require the restrictive assumption on the existence of a control Lyapunov function before the corresponding control law is constructed. Furthermore, a finite upper bound on the settling time is estimated, which indicates that within the settling time, the system trajectory would arrive and stay at the origin thereafter. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed approach.

Active/semi-active hybrid isolation system with fuzzy switching controller

This article designs an active/semi-active hybrid isolator using magnetorheological elastomer isolator and piezoelectric stack actuator to suppress the wide-frequency vibration in precision platform, which can be switched to active isolator, semi-active one, and passive one according to the spectrum signature of the excitation. First, the structure of the hybrid isolator is introduced. Then, the dynamic model of the hybrid isolation system is established, the model parameters are identified, and the switching condition for the hybrid isolator is derived by experiments. Next, considering variable amplitude and frequency vibration of the isolated system, an active and semi-active fuzzy switch controller is designed for piezoelectric stack actuator and magnetorheological elastomer hybrid isolator, which are independent of the system model, self-tuning, and robust. Finally, the numerical simulations are conducted under variable frequency excitations to evaluate the performance of the designed fuzzy switch controller, and the results show that the hybrid isolator, combined with the fuzzy switch controller, can attenuate full frequency vibration effectively.

Improved Sensorless Direct Torque Control of Induction Motor Using Fuzzy Logic and Neural Network Based Duty Ratio Controller

This paper presents improvements in Direct Torque control of an induction motor using Fuzzy logic with Fuzzy logic and neural network based duty ratio controller. The conventional DTC (CDTC) of induction motor suffers from major drawbacks like high torque and flux ripples and poor transient response. Torque and flux ripples are reduced by replacing hysteresis controller and switching table with Fuzzy logic switching controller (FDTC). In FDTC the selected switching vector is applied for the complete switching time period. The FDTC steady state performance can be improved by using duty ratio controller, the selected switching vector is applied only for the time determined by the duty ratio (δ) and for the remaining time period zero switching vector is applied. The selection of duty ratio using Fuzzy logic and neural networks is projected in this paper. The effectiveness proposed methods are evaluated using simulation by Matlab/Simulink.