scholarly journals Hardware in the Loop Testing of Adaptive Inertia Weight PSO-Tuned LQR Applied to Vehicle Suspension Control

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Joshua Sunder David Reddipogu ◽  
Vinodh Kumar Elumalai
Keyword(s):  
Optimization Problem ◽  
Ride Comfort ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Vehicle Body ◽  
Linear Quadratic ◽  
Body Acceleration ◽  
Inertia Weight ◽  
Optimal Weights ◽  
Road Profile

This paper presents an adaptive inertia weight particle swarm optimization (AIWPSO) employed for solving the multiobjective weight optimization problem of LQR applied for the vehicle active suspension system (ASS). To meet the competing control objectives of ASS including the ride comfort, road handling, and suspension travel, the state feedback controller design for ASS is formulated as an optimization problem and an improved PSO is employed for finding the optimal weights of the linear-quadratic regulator (LQR). Specifically, for solving the premature convergence of the particles and imbalance between exploration and exploitation capabilities of PSO, an adaptive inertia weight that updates the velocity of the particles based on the success rate is used. The efficacy of the AIWPSO-tuned LQR is experimentally tested on a quarter-car ASS plant using the hardware in loop (HIL) testing for an uneven road surface. Experimental results highlight that, compared to conventional PSO-tuned LQR, the proposed scheme can significantly minimize the vehicle body acceleration due to irregular road profile while guaranteeing the minimum tire friction for passenger safety. The ISO 2361-1 standards adopted to evaluate the ride and health criteria substantiate that the proposed scheme reduces the vibration dose value by 25.34% for a bumpy road profile. Moreover, the cumulative power spectral density (CPSD) of vehicle body acceleration assessed in both low- and high-frequency regions manifests the significant improvement in the ride comfort.

scholarly journals FULL CAR ACTIVE DAMPING SYSTEM FOR VIBRATION CONTROL

2020 ◽  
Vol 6 (4) ◽  
pp. 1-17
Author(s):  
G. Yakubu ◽  
G. Sani ◽  
S. B. Abdulkadir ◽  
A. A.Jimoh ◽  
M. Francis
Keyword(s):  
Mathematical Model ◽  
Linear Quadratic Regulator ◽  
Active Damping ◽  
Settling Time ◽  
Linear Quadratic ◽  
Body Acceleration ◽  
The Road ◽  
Road Profile ◽  
Lqr Controller ◽  
Mass Displacement

Full car passive and active damping system mathematical model was developed. Computer simulation using MATLAB was performed and analyzed. Two different road profile were used to check the performance of the passive and active damping using Linear Quadratic Regulator controller (LQR)Road profile 1 has three bumps with amplitude of 0.05m, 0.025 m and 0.05 m. Road profile 2 has a bump with amplitude of 0.05 m and a hole of -0.025 m. For all the road profiles, there were 100% amplitude reduction in Wheel displacement, Wheel deflection, Suspension travel and body displacement, and 97.5% amplitude reduction in body acceleration for active damping with LQR controller as compared to the road profile and 54.0% amplitude reduction in body acceleration as compared to the passive damping system. For the two road profiles, the settling time for all the observed parameters was less than two (2) seconds. The present work gave faster settling time for mass displacement, body acceleration and wheel displacement.

LQG Control Design for Vehicle Active Anti-Roll Bar System

2014 ◽  
Vol 663 ◽  
pp. 146-151 ◽  
Author(s):  
Noraishikin Zulkarnain ◽  
Hairi Zamzuri ◽  
Saiful Amri Mazlan
Keyword(s):  
Ride Comfort ◽  
Simulation Analysis ◽  
Control Strategies ◽  
Dynamic Modelling ◽  
Linear Quadratic Regulator ◽  
Vehicle Body ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Roll Rate ◽  
External Forces

The objective of this paper is to design a linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controllers for an active anti-roll bar system. The use of an active anti-roll bar will be analysed from two different perspectives in vehicle ride comfort and handling performances. This paper proposed the basic vehicle dynamic modelling with four degree of freedom (DOF) on half car model and are described that show, why and how it is possible to control the handling and ride comfort of the car, with the external forces also control strategies on the front anti-roll bar. By simulation analysis, the design model is validity and the performance under control of linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controller are achieved. Both two controllers are modeled in MATLAB/SIMULINK environment. It has to be determined which control strategy delivers better performance with respect to roll angle and the roll rate of half vehicle body. The result shows, however, that LQG produced better response compared to a LQR strategy.

scholarly journals Semi-Active Control of Vehicle Seat Suspension System with Magnetorheological Damper

2011 ◽  
Vol 2-3 ◽  
pp. 1067-1070
Author(s):  
Hai Jun Xing ◽  
Shao Pu Yang ◽  
Yong Jun Shen
Keyword(s):  
Active Control ◽  
Ride Comfort ◽  
Linear Quadratic Regulator ◽  
Suspension System ◽  
Magnetorheological Damper ◽  
Vehicle Body ◽  
Control Force ◽  
Linear Quadratic ◽  
Seat Suspension ◽  
Vehicle Seat

This research aims at the vibration control of vehicle seat suspension system. A three degree of freedom quarter vehicle model is used for semi-active control system in which a magnetorheological damper (MRD) is installed at the position between the vehicle body and the seat. A fully active linear quadratic regulator (LQR) control strategy is used to determine the optimized control force which is then matched by MRD to compute the semi-active control result. Computation result proves that semi-active control with MRD can alleviate the vehicle seat acceleration to improve ride comfort.

scholarly journals Signature PSO: A novel inertia weight adjustment using fuzzy signature for LQR tuning

2021 ◽  
Vol 10 (1) ◽  
pp. 308-318
Author(s):  
Achmad Komarudin ◽  
Novendra Setyawan ◽  
Leonardo Kamajaya ◽  
Mas Nurul Achmadiah ◽  
Zulfatman Zulfatman
Keyword(s):  
Linear Quadratic Regulator ◽  
Absolute Error ◽  
Control Parameters ◽  
Optimum Control ◽  
Exploration And Exploitation ◽  
Linear Quadratic ◽  
Lqr Control ◽  
Inertia Weight ◽  
Adjustment Strategy ◽  
Complete Optimization

Particle swarm optimization (PSO) is an optimization algorithm that is simple and reliable to complete optimization. The balance between exploration and exploitation of PSO searching characteristics is maintained by inertia weight. Since this parameter has been introduced, there have been several different strategies to determine the inertia weight during a train of the run. This paper describes the method of adjusting the inertia weights using fuzzy signatures called signature PSO. Some parameters were used as a fuzzy signature variable to represent the particle situation in a run. The implementation to solve the tuning problem of linear quadratic regulator (LQR) control parameters is also presented in this paper. Another weight adjustment strategy is also used as a comparison in performance evaluation using an integral time absolute error (ITAE). Experimental results show that signature PSO was able to give a good approximation to the optimum control parameters of LQR in this case.

scholarly journals Simulation of a Steam Injected Gas Turbine Plant Control System

1997 ◽  
Author(s):  
Shusheng Zang ◽  
Jaqiang Pan
Keyword(s):  
Gas Turbine ◽  
Flow Rate ◽  
Controller Design ◽  
Dynamic Performance ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Turbine Plant ◽  
Fuel Flow ◽  
Lqr Controller ◽  
Gas Turbine Plant

The design of a modern Linear Quadratic Regulator (LQR) is described for a test steam injected gas turbine (STIG) unit. The LQR controller is obtained by using the fuel flow rate and the injected steam flow rate as the output parameters. To meet the goal of the shaft speed control, a classical Proportional Differential (PD) controller is compared to the LQR controller design. The control performance of the dynamic response of the STIG plant in the case of rejection of load is evaluated. The results of the computer simulation show a remarkable improvement on the dynamic performance of the STIG unit.

Improvement on Ride Comfort of Quarter-Car Active Suspension System Using Linear Quadratic Regulator

2018 ◽  
pp. 431-441
Author(s):  
Sharifah Munawwarah Syed Mohd Putra ◽  
Fitri Yakub ◽  
Mohamed Sukri Mat Ali ◽  
Noor Fawazi Mohd Noor Rudin ◽  
Zainudin A. Rasid ◽  
...  
Keyword(s):  
Ride Comfort ◽  
Linear Quadratic Regulator ◽  
Active Suspension ◽  
Suspension System ◽  
Linear Quadratic ◽  
Quarter Car

scholarly journals Online Reinforcement Learning-Based Control of an Active Suspension System Using the Actor Critic Approach

2020 ◽  
Vol 10 (22) ◽  
pp. 8060
Author(s):  
Ahmad Fares ◽  
Ahmad Bani Younes
Keyword(s):  
Reinforcement Learning ◽  
Least Squares Method ◽  
Linear Quadratic Regulator ◽  
Active Suspension ◽  
Suspension System ◽  
Recursive Least Squares ◽  
Linear Quadratic ◽  
Reward Function ◽  
Road Profile ◽  
The One

In this paper, a controller learns to adaptively control an active suspension system using reinforcement learning without prior knowledge of the environment. The Temporal Difference (TD) advantage actor critic algorithm is used with the appropriate reward function. The actor produces the actions, and the critic criticizes the actions taken based on the new state of the system. During the training process, a simple and uniform road profile is used while maintaining constant system parameters. The controller is tested using two road profiles: the first one is similar to the one used during the training, while the other one is bumpy with an extended range. The performance of the controller is compared with the Linear Quadratic Regulator (LQR) and optimum Proportional-Integral-Derivative (PID), and the adaptiveness is tested by estimating some of the system’s parameters using the Recursive Least Squares method (RLS). The results show that the controller outperforms the LQR in terms of the lower overshoot and the PID in terms of reducing the acceleration.

scholarly journals Cross Regulation Reduced Optimal Multivariable Controller Design for Single Inductor DC-DC Converters

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 477 ◽  
Author(s):  
S. Augusti Lindiya ◽  
N. Subashini ◽  
K. Vijayarekha
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Multiple Input Multiple Output ◽  
Linear Quadratic Regulator ◽  
Prototype Model ◽  
Linear Quadratic ◽  
Load Current ◽  
Practical Applications ◽  
Input Multiple Output ◽  
Single Input

Single Inductor (SI) converters with the advantage of using one inductor for any number of inputs/outputs find wide applications in portable electronic gadgets and electrical vehicles. SI converters can be used in Single Input Multiple Output (SIMO) and Multiple Input Multiple Output (MIMO) configurations but they need controllers to achieve good transient and steady state responses, to improve the stability against load and line disturbances and to reduce cross regulation. Cross regulation is the change in an output voltage due to change in the load current at another output and it is an added constraint in SI converters. In this paper, Single Input Dual Output (SIDO) and Dual Input Dual Output (DIDO) converters with applications capable of handling high load current working in Continuous Conduction Mode (CCM) of operation are taken under study. Conventional multivariable PID and optimal Linear Quadratic Regulator (LQR) controllers are developed and their performances are compared for the above configurations to meet the desired objectives. Generalized mathematical models for SIMO and MIMO are developed and a Genetic Algorithm (GA) is used to find the parameters of a multivariable PID controller and the weighting matrices of optimal LQR where the objective function includes cross regulation as a constraint. The simulated responses reveal that LQR controller performs well for both the systems over multivariable PID controller and they are validated by hardware prototype model with the help of DT9834® Data Acquisition Module (DAQ). The methodologies used here generate a fresh dimension for the case of such converters in practical applications.

Analytical and Experimental Evaluation of Various Active Suspension Alternatives for Superior Ride Comfort and Utilization of Autonomous Vehicles

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Ivan Cvok ◽  
Mario Hrgetić ◽  
Matija Hoić ◽  
Joško Deur ◽  
Davor Hrovat ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
High Performance ◽  
Ride Comfort ◽  
Simulation Analysis ◽  
Linear Quadratic Regulator ◽  
Active Suspension ◽  
Vertical Acceleration ◽  
Linear Quadratic ◽  
Seat Suspension ◽  
Road Disturbance

Abstract Autonomous vehicles (AVs) give the driver opportunity to engage in productive or pleasure-related activities, which will increase AV’s utility and value. It is anticipated that many AVs will be equipped with active suspension extended with road disturbance preview capability to provide the necessary superior ride comfort resulting in almost steady work or play platform. This article deals with assessing the benefits of introducing various active suspensions and related linear quadratic regulator (LQR) controls in terms of improving the work/leisure ability. The study relies on high-performance shaker rig-based tests of a group of 44 drivers involved in reading/writing, drawing, and subjective ride comfort rating tasks. The test results indicate that there is a threshold of root-mean-square vertical acceleration, below which the task execution performance is similar to that corresponding to standstill conditions. For the given, relatively harsh road disturbance profile, only the fully active suspension with road preview control can suppress the vertical acceleration below the above critical superior comfort threshold. However, when adding an active seat suspension, the range of chassis suspension types for superior ride comfort is substantially extended and can include semi-active suspension and even passive suspension in some extreme cases that can, however, lead to excessive relative motion between the seat and the vehicle floor. The design requirements gained through simulation analysis, and extended with cost and packaging requirements related to passenger car applications, have guided design of two active seat suspension concepts applicable to the shaker rig and production vehicles.

Optimization control for dynamic vibration absorbers and active suspensions of in-wheel-motor-driven electric vehicles

2020 ◽  
Vol 234 (9) ◽  
pp. 2377-2392
Author(s):  
Mingchun Liu ◽  
Yuanzhi Zhang ◽  
Juhua Huang ◽  
Caizhi Zhang
Keyword(s):  
Electric Vehicles ◽  
Ride Comfort ◽  
Linear Quadratic Regulator ◽  
Vibration Absorber ◽  
Linear Quadratic ◽  
Dynamic Vibration Absorber ◽  
Dynamic Vibration ◽  
Optimization Control ◽  
Motor Vibration ◽  
Suspension Performance

This study addresses the challenges of ride comfort improvement and in-wheel-motor vibration suppression in in-wheel-motor-driven electric vehicles. First, a mathematical model of a quarter vehicle equipped with a dynamic vibration absorber and an active suspension is developed. Then, a two-stage optimization control method is proposed to improve the coupled dynamic vibration absorber–suspension performance. In the first stage, a linear quadratic regulator controller based on particle swarm optimization is designed for the dynamic vibration absorber to suppress the in-wheel-motor vibration, in which the dynamic vibration absorber parameters and linear quadratic regulator controller weighting factors are optimally matched by using the particle swarm optimization algorithm. In the second stage, a finite-frequency H∞ controller is designed in the framework of linear matrix inequality optimization for the active suspension to improve vehicle ride comfort. Suspension performance factors, including suspension working space and road-holding ability, are taken as constraints in both stages. The proposed method simultaneously improves vehicle ride comfort and suppresses in-wheel-motor vibration. Finally, the effectiveness and superiority of the proposed method are illustrated through comparison simulations.

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