Javascript must be enabled to continue!
Quarter car model optimization of active suspension system using fuzzy PID and linear quadratic regulator controllers
View through CrossRef
The primary objective of this paper is to improve the performance of a car's active suspension system and control the vibrations that occurred in the car's using two well-known control technologies, namely the Linear Quadratic Regulator (LQR) and fuzzy PID control. When the car suspension is designed, a quarter car model with two degrees of freedom is used. A complete control system is needed to provide the desired suspension performance and characteristics such as passenger comfort, road handling, and suspension deflection, this control system performed using the MATLAB/SIMULINK and includes three parts: input signals (actuator force and road profile), Controller part, and the suspension system model. The simulation results from the implemented Simulink models show a comparison between the uncontrolled suspension system and the suspension system with a fuzzy PID controller and the active suspension system of the car based on the linear-quadratic regulator, and it is explained thoroughly.
Title: Quarter car model optimization of active suspension system using fuzzy PID and linear quadratic regulator controllers
Description:
The primary objective of this paper is to improve the performance of a car's active suspension system and control the vibrations that occurred in the car's using two well-known control technologies, namely the Linear Quadratic Regulator (LQR) and fuzzy PID control.
When the car suspension is designed, a quarter car model with two degrees of freedom is used.
A complete control system is needed to provide the desired suspension performance and characteristics such as passenger comfort, road handling, and suspension deflection, this control system performed using the MATLAB/SIMULINK and includes three parts: input signals (actuator force and road profile), Controller part, and the suspension system model.
The simulation results from the implemented Simulink models show a comparison between the uncontrolled suspension system and the suspension system with a fuzzy PID controller and the active suspension system of the car based on the linear-quadratic regulator, and it is explained thoroughly.
Related Results
High-fidelity modeling of redundant EMA and small angle displacement analysis under different controllers
High-fidelity modeling of redundant EMA and small angle displacement analysis under different controllers
An increasing number of applications of the electromechanical actuator (EMA) in the flight vehicle control system have required accurate dynamic models and control strategies. This...
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Abstract. Fuzzy Inference System requires several stages to get the output, 1) formation of fuzzy sets, 2) formation of rules, 3) application of implication functions, 4) compositi...
Functional Diversification and Dynamics of CAR-T Cells in B-ALL Patients
Functional Diversification and Dynamics of CAR-T Cells in B-ALL Patients
Chimeric antigen receptor-engineered (CAR)-T cell therapy represents one of the most promising strategies of cancer treatment, and the function and persistence of CAR-T cells in vi...
Generated Fuzzy Quasi-ideals in Ternary Semigroups
Generated Fuzzy Quasi-ideals in Ternary Semigroups
Here in this paper, we provide characterizations of fuzzy quasi-ideal in terms of level and strong level subsets. Along with it, we provide expression for the generated fuzzy quasi...
A Feedback‐Assisted Inverse Neural Network Controller for Cart‐Mounted Inverted Pendulum
A Feedback‐Assisted Inverse Neural Network Controller for Cart‐Mounted Inverted Pendulum
A vast variety of neural network (NN)–based controllers use indirect adaptive control structures for their implementation, which primarily aims at estimating the nonlinear dynamics...
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
Background Several scholars defined the concepts of fuzzy soft set theory and their application on decision-making problem. Based on this concept, researchers defined the generalis...
Robust Nonlinear Non-Referenced Inertial Frame Multi-Stage PID Controller for Symmetrical Structured UAV
Robust Nonlinear Non-Referenced Inertial Frame Multi-Stage PID Controller for Symmetrical Structured UAV
The design and implementation of a multi-stage PID (MS-PID) controller for non-inertial referenced UAVs are highly complex. Symmetrical multirotor UAVs are unstable systems, and it...
Stochastic continuous-time cash flows: A coupled linear-quadratic model
Stochastic continuous-time cash flows: A coupled linear-quadratic model
<p>The focal point of this dissertation is stochastic continuous-time cash flow models. These models, as underpinned by the results of this study, prove to be useful to descr...

