1,555 research outputs found
Body Travel Performance Improvement of Space Vehicle Electromagnetic Suspension System using LQG and LQI Control Methods
Electromagnetic suspension system (EMS) is mostly used in the field of high-speed vehicle. In this paper, a space exploring vehicle quarter electromagnetic suspension system is modelled, designed and simulated using linear quadratic optimal control problem. Linear quadratic Gaussian and linear quadratic integral controllers are designed to improve the body travel of the vehicle using bump road profile. Comparison between the proposed controllers is done and a promising simulation result have been analyzed
Robust Control Theory Based Performance Investigation of an Inverted Pendulum System using Simulink
In this paper, the performance of inverted pendulum have been Investigated using robust control theory. The robust controllers
used in this paper are H∞ Loop Shaping Design Using Glover McFarlane Method and mixed H∞ Loop Shaping Controllers.
The mathematical model of Inverted Pendulum, a DC motor, Cart and Cart driving mechanism have been done successfully.
Comparison of an inverted pendulum with H∞ Loop Shaping Design Using Glover McFarlane Method and H∞ Loop Shaping
Controllers for a control target deviation of an angle from vertical of the inverted pendulum using two input signals (step and
impulse). The simulation result shows that the inverted pendulum with mixed H∞ Loop Shaping Controller to have a small rise
time, settling time and percentage overshoot in the step response and having a good response in the impulse response too.
Finally the inverted pendulum with mixed H∞ Loop Shaping Controller shows the best performance in the overall simulation
result
Comparison of neural network NARMA-L2 model reference and predictive controllers for nonlinear quarter car active suspension system
Recently, active suspension system will become important to the vehicle industries because of its advantages in
improving road managing and ride comfort. This paper offers the development of mathematical modelling and
design of a neural network control approach. The paper will begin with a mathematical model designing primarily
based at the parameters of the active suspension system. A nonlinear three by four-way valve-piston hydraulic
actuator became advanced which will make the suspension system under the active condition. Then, the model can
be analyzed thru MATLAB/Simulink software program. Finally, the NARMA-L2, model reference and predictive
controllers are designed for the active suspension system. The results are acquired after designing the simulation of
the quarter-car nonlinear active suspension system. From the simulation end result using MATLAB/Simulink, the
response of the system might be as compared between the nonlinear active suspension system with NARMA-L2,
model reference and predictive controllers. Besides that, the evaluation has been made between the proposed
controllers thru the characteristics of the manage objectives suspension deflection, body acceleration and body travel
of the active suspension system. . As a conclusion, designing a nonlinear active suspension system with a nonlinear
hydraulic actuator for quarter car model has improved the car performance by using a NARMA-L2 controller. The
improvements in performance will improve road handling and ride comfort performance of the active suspension
system
H ∞ and μ-synthesis Design of Quarter Car Active Suspension System
To improve the street managing and passenger comfort of a vehicle, a suspension system is furnished. An
active suspension device is considered to be better than the passive suspension device. In this paper, 2
degree of freedom of an active suspension system of a linear vehicle are designed, that's challenge to oneof-a-kind disturbances on the road. Since the parametric uncertainty inside the spring, the shock absorber,
the mass and the actuator has been taken into consideration, robust control is used. In this paper, H∞ and
µ-synthesis controllers are used to enhance using consolation and the capability to force the car on the
road. For the analysis of the time domain, a MATLAB script software become used and a check with 4
road disturbance inputs (bump, random, sinusoidal and harmonic) became carried out for suspension
deflection, body acceleration and travel of the body for the energetic suspension with the H∞ controller
and the active suspension with the µ-synthesis controller and the comparative simulation and the reference
consequences display the effectiveness of the active suspension system with the µ-synthesis controller
Nonlinear autoregressive moving average-L2 model based adaptive control of nonlinear arm nerve simulator system
This paper considers the trouble of the usage of approximate strategies for realizing the neural controllers for nonlinear SISO systems. In this paper, we introduce the nonlinear autoregressive moving average (NARMA-L2) model which might be approximations to the NARMA model. The nonlinear autoregressive moving average (NARMA-L2) model is an precise illustration of the input–output behavior of finite-dimensional nonlinear discrete time dynamical systems in a neighborhood of the equilibrium state. However, it isn't always handy for purposes of neural networks due to its nonlinear dependence on the manipulate input. In this paper, nerves system based arm position sensor device is used to degree the precise arm function for nerve patients the use of the proposed systems. In this paper, neural network controller is designed with NARMA-L2 model, neural network controller is designed with NARMA-L2 model system identification based predictive controller and neural network controller is designed with NARMA-L2 model based model reference adaptive control system. Hence, quite regularly, approximate techniques are used for figuring out the neural controllers to conquer computational complexity. Comparison were made among the neural network controller with NARMA-L2 model, neural network controller with NARMA-L2 model system identification based predictive controller and neural network controller with NARMA-L2 model reference based adaptive control for the preferred input arm function (step, sine wave and random signals). The comparative simulation result shows the effectiveness of the system with a neural network controller with NARMA-L2 model based model reference adaptive control system. Index Terms--- Nonlinear autoregressive moving average, neural network, Model reference adaptive control, Predictive controller DOI: 10.7176/JIEA/10-3-03 Publication date: April 30th 202
Comparison of H∞ and μ-synthesis Control Design for Quarter Car Active Suspension System using Simulink
To improve road dealing with and passenger consolation of a vehicle, a suspension system is supplied. An
active suspension system is taken into consideration better than the passive suspension system. In this
paper, an active suspension system of a linear quarter vehicle is designed, that's issue to exclusive
disturbances on the road. Since the parametric uncertainty within the spring, the shock absorber and the
actuator has been taken into consideration, robust control is used. H∞ and µ-Synthesis controllers of are
used to improve using consolation and road dealing with potential of the vehicle, in addition to confirm the
sturdy stability and overall performance of the system. In the H∞ design, we designed a driving force for
passenger consolation and to preserve the deflection of the suspension small and to reduce the disturbance
of the road to the deflection of the suspension. For the µ synthesis system, we designed a controller with
hydraulic actuator and uncertainty model. We designed a MATLAB / SIMULINK model for the active
suspension system with the H∞ and µ-synthesis controllers we tested the use of 4 road disturbance inputs
(bump, random, sinusoidal pavement and slope) for deflection of the suspension, body acceleration and
body travel for passive, active suspension with controller and active suspension without controller. Finally,
we evaluate the H∞ and µ-synthesis controllers with a Simulink model for suspension deflection, body
acceleration and body travel simulation, and the result suggests that both designs offer correct overall
performance, however the H∞ controller has superior overall performance as compared to the µ-synthesis
controller
Quarter car active suspension system design using optimal and robust control method
This paper offers with the theoretical and computational evaluation of optimal& robust controlproblems, with the
goal of providing answers to them with MATLAB simulation.For the robust control, -synthesis controller and for
the optimal control, LQR controller are designed for a quarter car active suspension system to maximize the ride
comfort and road handling criteria’s of the vehicle. The proposed controllers are designed using Matlab script
program using time domain analysis for the four road disturbances (bump, random sine pavement and white noise)
for the control targets suspension deflection, body acceleration and body travel. Finally the simulation result proves
the effectiveness of the active suspension system with -synthesis controller
Comparison of Mixed H 2 H∞ with Regional Pole Placement Control and H 2 Optimal Control for the Design of Steam Condenser
This paper investigates the comparison between mixed H 2 /H∞ with regional pole placement control and H 2
optimal control for the design of steam condenser. The comparison have been made for a step change in the steam
condenser pressure set point for a step change of 10 & 23 seconds using MATLAB/Simulink environment for the
steam condenser with mixed H 2 /H∞ with regional pole placement controller, steam condenser with H 2 optimal
controller and steam condenser without controller. The steam condenser with mixed H 2 /H∞ with regional pole
placement controller presented excellent and superior dynamic performance in response to the two step changes
and an improvement in settling time. The overall simulation results demonstrated that the steam condenser with
mixed H 2 /H∞ with regional pole placement controller can be an efficient alternative to the steam condenser with
H 2 optimal controller for the steam condenser
Comparison of DC motor speed control performance using fuzzy logic and model predictive control method
The main target of this paper is to control the speed of DC motor by comparing the actual and the desired speed set
point. The DC motor is designed using Fuzzy logic and MPC controllers. The comparison is made between the
proposed controllers for the control target speed of the DC motor using square and white noise desired input signals
with the help of Matlab/Simulink software. It has been realized that the design based on the fuzzy logic controller track
the set pointwith the best steady state and transient system behavior than the design with MPC controller. Finally, the
comparative simulation result prove the effectiveness of the DC motor with fuzzy logic controller
DC motor speed control with the presence of input disturbance using neural network based model reference and predictive controllers
In this paper we describe a technical system for DC motor speed control. The speed of DC motor is controlled using
Neural Network Based Model Reference and Predictive controllers with the use of Matlab/Simulink. The analysis of
the DC motor is done with and without input side Torque disturbance input and the simulation results obtained by
comparing the desired and actual speed of the DC motor using random reference and sinusoidal speed inputs for the
DC motor with Model Reference and Predictive controllers. The DC motor with Model Reference controller shows
almost the actual speed is the same as the desired speed with a good performance than the DC motor with Predictive
controller for the system with and without input side disturbance. Finally the comparative simulation result prove the
effectiveness of the DC motor with Model Reference controller
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