On approximation properties of smooth fuzzy models

This Paper Addresses The Approximation Properties Of The Smooth Fuzzy Models. It Is Widely Recognized That The Fuzzy Models Can Approximate A Nonlinear Function To Any Degree Of Accuracy In A Convex Compact Region. However, In Many Applications, It Is Desirable To Go Beyond That And Acquire A Model To Approximate The Nonlinear Function On A Smooth Surface To Gain Better Performance And Stability Properties. Especially In The Region Around The Steady States, When Both Error And Change In Error Are Approaching Zero, It Is Much Desired To Avoid Abrupt Changes And Discontinuity In The Approximation Of The Input-Output Mapping. This Problem Has Been Remedied In Our Approach By Application Of The Smooth Compositions In The Fuzzy Modeling Scheme. In The Fuzzy Decomposition Stage Of Fuzzy Modeling, We Have Discretized The Parameters And Then Calculated The Result Through Partitioning Them Into A Dense Grid. This Could Enable Us To Present The Formulations By Convolution And Fourier Transformation Of The Parameters And Then Obtain The Approximation Properties By Studying The Structural Properties Of The Fourier Transformation And Convolution Of The Parameters. We Could Show That, Irrespective To The Shape Of The Membership Function, One Can Approximate The Dynamics And Derivative Of The Continuous Systems Together, Using The Smooth Fuzzy Structure. The Results Of The Paper Have Been Tested And Evaluated On A Discrete Event System In The Hybrid And Switched Systems Framework

Direct yaw-moment control of an in-wheel-motored electric vehicle based on body slip angle fuzzy observer

A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based body slip angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental settin

Development of a semi-active car suspension control system using magneto-rheological damper model

In this paper, the development of a semi- active suspension control of quarter car model using fuzzy-based controller has been done. The quarter car model to be used here can be described as a nonlinear two degrees of freedom system which is subject to excitation from different road profile. The semi-active control is designed as the fuzzy control inferred by using two single input rule fuzzy modules, and the road model is used as the control force is released by actuating an electromagnetic shaker. To implement semi-active suspension system experimentally, the MR damper is used here as the adjustable damper. The MR damper is a control device that consists of a hydraulic cylinder filled with magnetically polarizable particles suspended in a liquid. MR dampers dissipate vibration by absorbing energy. Magnetorheological (MR) fluids dampers are very effective to control vibration, which use MR fluids to produce controllable damping force and provide both the reliability of passive systems and the facility of active control systems with small power supply. Due to their mechanical simplicity, high dynamic range, low power requirements, large force capacity, and robustness, offer an attractive means of vibration protection. The objectives of this are modeling of semi-active suspension system, developing controller and understanding the characteristics of the MR damper to provide effective damping for the purpose of suspension isolation or suppression car model. In this work pid, fuzzy logic and fuzzy-hybrid controller are used to control semi-active car suspension system

Extruder for food product (otak–otak) with heater and roll cutter

Food extrusion is a form of extrusion used in food industries. It is a process by which a set of mixed ingredients are forced through an opening in a perforated plate or die with a design specific to the food, and is then cut to a specified size by blades [1]. Summary of the invention principal objects of the present invention are to provide a machine capable of continuously producing food products having an’ extruded filler material of meat or similarity and an extruded outer covering of a moldable food product, such as otak-otak, that completely envelopes the filler material

Investigations of Using an Intelligent ANFIS Modeling Approach for a Li-Ion Battery in MATLAB Implementation: Case Study

This research paper will propose an incentive topic to investigate the accuracy of an adaptive neuro-fuzzy modeling approach of lithium-ion (Li-ion) batteries used in hybrid electric vehicles and electric vehicles. Based on this adaptive neuro-fuzzy inference system (ANFIS) modeling approach, we will show its effectiveness and suitability for modeling the nonlinear dynamics of any process or control system. This new ANFIS modeling approach improves the original nonlinear battery model and an alternative linear autoregressive exogenous input (ARX) polynomial model. The alternative ARX is generated using the least square errors estimation method and is preferred for its simplicity and faster implementation since it uses typical functions from the MATLAB system identification toolbox. The ARX and ANFIS models’ effectiveness is proved by many simulations conducted on attractive MATLAB R2021b and Simulink environments. The simulation results reveal a high model accuracy in battery state of charge (SOC) and terminal voltage. An accurate battery model has a crucial impact on building a very precise adaptive extended Kalman filter (AEKF) SOC estimator. It is considered an appropriate case study of a third-order resistor-capacitor equivalent circuit model (3RC ECM) SAFT-type 6 Ah 11 V nominal voltage of Li-ion battery for simulation purposes