scholarly journals An Adaptive Control of Fractional-Order Nonlinear Uncertain Systems with Input Saturation

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Changhui Wang ◽  
Mei Liang ◽  
Yongsheng Chai
Keyword(s):  
Fuzzy Logic ◽  
Fractional Order ◽  
Uncertain Systems ◽  
Input Saturation ◽  
Fuzzy Logic System ◽  
Distributed Model ◽  
Unknown Parameters ◽  
External Disturbances ◽  
Nonlinear Uncertain Systems ◽  
Logic System

This paper develops a fractional-order adaptive fuzzy backstepping control scheme for incommensurate fractional-order nonlinear uncertain systems with external disturbances and input saturation. Based on backstepping algorithm, the fuzzy logic system is used to approximate the unknown nonlinear uncertainties in each step of the backstepping, and the fractional-order parameters update laws for fuzzy logic system, unknown parameters, and the external disturbances are proposed. With the aids of the frequency distributed model of fractional integrator for the fractional-order systems in the procedure of controller design, the stability of the closed-loop system is established. To verify the effectiveness and robustness of the proposed controller, two simulation examples are demonstrated at last.

scholarly journals Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7084
Author(s):  
Song Kang ◽  
Yongfeng Rong ◽  
Wusheng Chou
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Entire System ◽  
Actuator Faults ◽  
Extended State ◽  
Parameter Uncertainties ◽  
External Disturbances ◽  
Measurement Noises ◽  
Fuzzy Adaptive ◽  
Logic System

In this paper, an output-feedback fuzzy adaptive dynamic surface controller (FADSC) based on fuzzy adaptive extended state observer (FAESO) is proposed for autonomous underwater vehicle (AUV) systems in the presence of external disturbances, parameter uncertainties, measurement noises and actuator faults. The fuzzy logic system is incorporated into both the observers and controllers to improve the adaptability of the entire system. The dynamics of the AUV system is established first, considering the external disturbances and parameter uncertainties. Based on the dynamic models, the ESO, combined with a fuzzy logic system tuning the observer bandwidth, is developed to not only adaptively estimate both system states and the lumped disturbances for the controller, but also reduce the impact of measurement noises. Then, the DSC, together with fuzzy logic system tuning the time constant of the low-pass filter, is designed using estimations from the FAESO for the AUV system. The asymptotic stability of the entire system is analyzed through Lyapunov’s direct method in the time domain. Comparative simulations are implemented to verify the effectiveness and advantages of the proposed method compared with other observers and controllers considering external disturbances, parameter uncertainties and measurement noises and even the actuator faults that are not considered in the design process. The results show that the proposed method outperforms others in terms of tracking accuracy, robustness and energy consumption.

scholarly journals Suppression the Disturbance of Robotic Manipulators Based on Nonlinear Disturbance Observer and Fuzzy Logic System

2020 ◽  
Vol 24 (7) ◽  
pp. 846-854
Author(s):  
Wangyong He ◽  
Haogui Li ◽  
Yuanjiang Wang ◽  
Sanqiu Liu ◽  
◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Disturbance Observer ◽  
Robot Manipulator ◽  
Robotic Manipulators ◽  
Fuzzy Logic System ◽  
External Disturbances ◽  
Nonlinear Disturbance Observer ◽  
Coupling System ◽  
Nonlinear Disturbance ◽  
Logic System

Robotic Manipulators (RM) are nonlinear and coupling system with time-variant and model uncertainties. In addition, RM are subject to different types of disturbances in practice, such as joint frictions, unknown payloads, and interferences from external systems. In this paper, these adverse factors are regarded as disturbance, and classifies them into internal disturbances and external disturbances. In order to achieve high-precision control, a Nonlinear Disturbance Observer (NDO) is designed to suppress external disturbances, and a Fuzzy Logic System (FLS) is designed to compensate internal disturbances. The scheme can effectively suppress the disturbance and improve the control accuracy. The validity of the scheme is shown by computer simulations of a two-link robot manipulator.

scholarly journals Robust Tracking Control for Robotic Manipulator via Fuzzy Logic System andH∞Approaches

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Kun Mu ◽  
Cong Liu ◽  
Jinzhu Peng
Keyword(s):  
Fuzzy Logic ◽  
Tracking Control ◽  
Robotic Manipulator ◽  
Fuzzy Logic System ◽  
Torque Control ◽  
Robust Tracking ◽  
Robust Tracking Control ◽  
External Disturbances ◽  
Control Scheme ◽  
Logic System

Based on fuzzy logic system (FLS) andH∞control methodologies, a robust tracking control scheme is proposed for robotic system with uncertainties and external disturbances. FLS is employed to implement the framework of computed torque control (CTC) method via its approximate capability which is used to attenuate the nonlinearity of robotic manipulator. The robustH∞control can guarantee robustness to parametric and dynamics uncertainties and also attenuate the effect of immeasurable external disturbances entering the system. Moreover, a quadratic stability approach is used to reduce the conservatism of the conventional robust control approach. It can be guaranteed that all signals in the closed-loop are bounded by employing the proposed robust tracking control. The validity of the proposed control scheme is shown by simulation of a two-link robotic manipulator.

scholarly journals Grey Wolf and Weighted Whale Algorithm Optimized IT2 Fuzzy Sliding Mode Backstepping Control with Fractional-Order Command Filter for a Nonlinear Dynamic System

2021 ◽  
Vol 11 (2) ◽  
pp. 489
Author(s):  
Seongik Han
Keyword(s):  
Fuzzy Logic ◽  
Fractional Order ◽  
Optimization Algorithm ◽  
Sliding Mode ◽  
Fuzzy Logic System ◽  
Backstepping Control ◽  
Whale Optimization Algorithm ◽  
Grey Wolf ◽  
Whale Optimization ◽  
Logic System

In this study, a fractional-order sliding mode backstepping control method was proposed, which involved the use of a fractional-order command filter, an interval type-2 fuzzy logic system approximation method, and a grey wolf and weighted whale optimization algorithm for multi-input multi-output nonlinear dynamic systems. For designing the stabilizing controls of the backstepping control, a novel fractional-order sliding mode surface was suggested. Further, the transformed errors that occurred during the recursive design steps were easily compensated by the controllers constructed using a new fractional-order command filter. Thus, the differentiation issue of the virtual control in the conventional backstepping control design could be bypassed with a simpler controller structure. Subsequently, the unknown plant dynamics were approximated by an interval type-2 fuzzy logic system. The uncertainties, such as the approximation error and the external disturbance, were compensated by the fractional-order sliding mode control that was added in the backstepping controller. Furthermore, the controller parameters and the fuzzy logic system were optimized via a grey wolf and weighted whale optimization algorithm to obtain a faster tuning process and an improved control performance. Simulation results demonstrated that the fractional-order sliding mode backstepping control scheme provides enhanced control performance over the conventional backstepping control system. Thus, in this paper, a fractional-order sliding mode surface and fractional-order backstepping control are studied, which provide more rapid convergence and enhanced robustness. Furthermore, a hybrid grey wolf and weighted whale optimization algorithm are proposed to provide an improved learning performance than those of conventional grey wolf optimization and weighted whale optimization methods.

A New Hardware Architecture for Fuzzy Logic System Acceleration

2016 ◽  
Vol 12 (2) ◽  
pp. 188-197
Author(s):  
A yahoo.com ◽  
Aumalhuda Gani Abood aumalhuda ◽  
A comp ◽  
Dr. Mohammed A. Jodha ◽  
Dr. Majid A. Alwan
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Hardware Architecture ◽  
Logic System

Penerapan Logika Samar dalam Peramalan Data Runtun Waktu

2011 ◽  
Vol 3 (2) ◽  
pp. 11-15
Author(s):  
Seng Hansun
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Time Series Analysis ◽  
Fuzzy Sets ◽  
Fuzzy System ◽  
Time Series Data ◽  
Fuzzy Logic System ◽  
Series Data ◽  
Series Analysis ◽  
Logic System

Recently, there are so many soft computing methods been used in time series analysis. One of these methods is fuzzy logic system. In this paper, we will try to implement fuzzy logic system to predict a non-stationary time series data. The data we use here is Mackey-Glass chaotic time series. We also use MATLAB software to predict the time series data, which have been divided into four groups of input-output pairs. These groups then will be used as the input variables of the fuzzy logic system. There are two scenarios been used in this paper, first is by using seven fuzzy sets, and second is by using fifteen fuzzy sets. The result shows that the fuzzy system with fifteen fuzzy sets give a better forecasting result than the fuzzy system with seven fuzzy sets. Index Terms—forecasting, fuzzy logic, Mackey-Glass chaotic, MATLAB, time series analysis

IMPROVING EIGENSPACE-BASED FUZZY LOGIC SYSTEM USING A LINEAR INTERPOLATION SCHEME FOR SPEECH PATTERN RECOGNITION

2013 ◽  
Vol 37 (3) ◽  
pp. 611-620
Author(s):  
Ing-Jr Ding ◽  
Chih-Ta Yen
Keyword(s):  
Pattern Recognition ◽  
Fuzzy Logic ◽  
Recognition Performance ◽  
Linear Interpolation ◽  
Fuzzy Logic System ◽  
Interpolation Scheme ◽  
Speech Pattern ◽  
Eigen Value ◽  
Target Speaker ◽  
Logic System

The Eigen-FLS approach using an eigenspace-based scheme for fast fuzzy logic system (FLS) establishments has been attempted successfully in speech pattern recognition. However, speech pattern recognition by Eigen-FLS will still encounter a dissatisfactory recognition performance when the collected data for eigen value calculations of the FLS eigenspace is scarce. To tackle this issue, this paper proposes two improved-versioned Eigen-FLS methods, incremental MLED Eigen-FLS and EigenMLLR-like Eigen-FLS, both of which use a linear interpolation scheme for properly adjusting the target speaker’s Eigen-FLS model derived from an FLS eigenspace. Developed incremental MLED Eigen-FLS and EigenMLLR-like Eigen-FLS are superior to conventional Eigen-FLS especially in the situation of insufficient data from the target speaker.

Uniformly ultimately bounded tracking control of sandwich systems with nonsymmetric sandwiched dead-zone nonlinearity and input saturation constraint

2021 ◽  
pp. 107754632098794
Author(s):  
Meysam Azhdari ◽  
Tahereh Binazadeh
Keyword(s):  
Dead Zone ◽  
Input Saturation ◽  
Closed Loop System ◽  
Unknown Parameters ◽  
External Disturbances ◽  
Uniformly Ultimately Bounded ◽  
Output Tracking ◽  
Saturation Constraint ◽  
Two Phases ◽  
Practical Constraints

This article studies the uniformly ultimately bounded output tracking problem of uncertain nonlinear sandwich systems with sandwiched dead-zone nonlinearity in the presence of some practical constraints such as nonsymmetric input saturation, model uncertainties, time-varying external disturbances, and unknown parameters. Due to the existence of both dead-zone and saturation nonlinearities, the design process is more complicated; therefore, to solve the design complexities, the designing process is divided into two phases. The proposed method leads to output tracking with acceptable accuracy. Moreover, all signals in the closed-loop system are ultimately bounded. Simulation results illustrate the applicability and effectiveness of the proposed method by its application on two practical sandwich systems (robotic system and electrohydraulic servo press system).

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