Intelligent Sliding Mode Controller for Active Suspension System Using Particle Swarm Optimization

2014 ◽  
Vol 69 (1) ◽  
Author(s):  
Mahmood Ali Moqbel Obaid ◽  
Abdul Rashid Husain ◽  
Ali Abdo Mohammed Al-kubati
Keyword(s):  
Particle Swarm Optimization ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Pso Algorithm ◽  
Suspension System ◽  
Sliding Mode Controller ◽  
Swarm Optimization ◽  
Passive Suspension ◽  
Passive Suspension System ◽  
Mismatched Uncertainty

This paper considers the control of an active suspension system (ASS) for a quarter car model based on the fusion of robust control and computational intelligence techniques. The objective of designing a controller for the car suspension system is to improve the ride comfort while maintaining the constraints on to the suspension travel and tire deformation subjected to different road profile. However, due to the mismatched uncertainty in the mathematical model of the ASS, sliding mode control (SMC) cannot be applied directly to control the system. Thus, the purpose of this work is to adapt the SMC technique for the control of ASS, where particle swarm optimization (PSO) algorithm is utilized to design the sliding surface such that the effect of the mismatched uncertainty can be minimized. The performance of the proposed sliding mode controller based on the PSO algorithm is compared with the linear quadratic optimal control (LQR) and the existing passive suspension system. In comparison with the other control methods, the simulation results demonstrate the superiority of the proposed controller, where it significantly improved the ride comfort 67% and 25% more than the passive suspension system and the LQR controller, respectively. 

scholarly journals Super-twisting sliding mode controllers based on D-PSO optimization for temperature control of an induction cooking system

2020 ◽  
Vol 11 (2) ◽  
pp. 1055
Author(s):  
Abdeldjalil Abdelkader Mekki ◽  
Abdelkader Kansab ◽  
Mohamed Matallah ◽  
Zinelaabidine Boudjema ◽  
Mouloud Feliachi
Keyword(s):  
Particle Swarm Optimization ◽  
Sliding Mode ◽  
Pso Algorithm ◽  
Sliding Mode Controller ◽  
Swarm Optimization ◽  
Fem Method ◽  
Cooking Temperature ◽  
Sliding Mode Controllers ◽  
Simulation Results ◽  
Induction Cooking

<p class="Default">In this study, we perform the control of the temperature evolution versus time of induction cooking system using a super twisting sliding mode control (STSMC) based on Dynamic Particle Swarm Optimization (D-PSO). First, we will determine the evolution of the temperature in the middle of the pan bottom using the FEM method. The found temperature exceeds the limit of the desired cooking temperature (150-200°C). Second, to limit temperature increase, a (ST-SMC) method combined with a (D-PSO) algorithm is used to get the desired temperature. Particles Swarm Optimization (D-PSO) method is used to optimize the parameters of the gain of (ST-SMC) and improve its performance. The simulation results show that the use of the optimized super twisting sliding mode controller helps to achieve a desired value of cooking.</p>

scholarly journals Design Stable Controller for PUMA 560 Robot with PID and Sliding Mode Controller Based on PSO Algorithm

2020 ◽  
Vol 13 (6) ◽  
pp. 487-499
Author(s):  
Hanan Akkar ◽  
◽  
Suhad Haddad ◽  
Keyword(s):  
Particle Swarm Optimization ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Step Response ◽  
Sliding Mode Controller ◽  
Nonlinear Controller ◽  
Swarm Optimization ◽  
Integral Sliding Mode

The most significant challenge facing the researcher in the field of robotics is to control the robot manipulator with appropriate overall performance. This paper focuses mainly on the novel Intelligent Particle Swarm Optimization (PSO) algorithm that was used for optimizing and tuning the gain of conventional Proportional Integral Derivative (PID), and improve the parameters of dynamic design in Sliding Mode Control (SMC), which is considered a strong nonlinear controller for controlling highly nonlinear systems, particularly for multi-degree serial link robot manipulator. Additional modified Integral Sliding Mode Controller (ISMC) was implemented to the design of dynamic system with high control theory of sliding mode controller. Intelligent Particle Swarm Optimization (PSO) algorithm was introduced for developing the nonlinear controller. The algorithm demonstrates superior performance in determining the appropriate gains and parameters value in harmony with robot scheme dynamic layout in order to achieve suitable and stable nonlinear controller, besides reduce the chattering phenomenon. PUMA robot manipulator that was used as study case in this work, shows perfect result in step response, with acceptable steady state, and overshoot, besides, eliminating the disadvantage of chattering in conventional SMC. Matlab / Simulink presents to increase the speed of matrix calculation in forward, inverse kinematics and dynamic model of manipulator. Comparison was made between the proposed method with existing methods. Result shows that integral sliding mode with PSO (ISMC/PSO) gave best result for stable step response, minimum mean square error with best objective function, and stable torque.

Ride comfort analysis of driver seat using super twisting sliding mode controlled magnetorheological suspension system

2021 ◽  
pp. 095440702110087
Author(s):  
Arockia Suthan Soosairaj ◽  
Arunachalam Kandavel
Keyword(s):  
Time Domain ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Mr Damper ◽  
Time Domain Analysis ◽  
Suspension System ◽  
Sliding Mode Controller ◽  
Passive Suspension ◽  
Voltage Variation ◽  
Continuous State

In order to improve the ride comfort of the driver, a higher-order Sliding Mode Controller was proposed in this study for a semiactive magnetorheological (MR) suspension system. The work is mainly focused on improving the ride comfort of the driver with simultaneous improvement in road holding capability of the vehicle and to study the effects of using Super Twisting Sliding Mode Controller (STSMC) in a quarter car with driver seat model. The modified Bouc-Wen model was simulated using MATLAB/Simulink software and the STSMC was adopted to control the voltage variation in MR damper using Continuous State Control (CSC) algorithm. The controller and the suspension system parameters were analysed in time domain with random road inputs. Fast Fourier Transform (FFT) analysis was also carried out to show the effectiveness of the controller towards improving the driver seat comfort. The STSMC-controlled MR damper was used as a primary suspension and the effectiveness of its controllability was compared with passive suspension system. The uncontrolled MR suspension system was also analysed in order to verify the fail-proof advantage of the MR damper. From the results, it was found that the ride comfort was extremely improved when STSMC controller was used than when the uncontrolled MR and passive suspension systems were employed. The uncertainty of the STSMC was verified for different passenger masses and it achieved a robust control over load variation. The selected STSMC was validated with the first-order Sliding Mode Controller and the results were discussed in terms of time-domain analysis.

A Novel Control Scheme for PWM Boost Converter based on Sliding Mode Control using Particle Swarm Optimization

2020 ◽  
Vol 14 ◽  
Author(s):  
Gang Liu ◽  
Dong Qiu ◽  
Xiuru Wang ◽  
Ke Zhang ◽  
Huafeng Huang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Steady State ◽  
Sliding Mode ◽  
Particle Swarm ◽  
Mathematic Model ◽  
Absolute Error ◽  
Boost Converter ◽  
Sliding Mode Controller ◽  
Swarm Optimization ◽  
Steady State Performance

Background: The PWM Boost converter is a strongly nonlinear discrete system, especially when the input voltage or load varies widely, therefore, tuning the control parameters of which is a challenge work. Objective: In order to overcome the issues, particle swarm optimization (PSO) is employed for tuning the parameters of a sliding mode controller of a boost converter. Methods: Based on the analysis of the Boost converter model and its non-linear characteristics, a mathematic model of a boost converter with a sliding mode controller is built firstly. Then, the parameters of the Boost controller are adjusted based on the integrated time and absolute error (ITAE), integral square error (ISE) and integrated absolute error (IAE) indexes by PSO. Results: Simulation verification was performed, and the results show that the controllers tuned by the three indexes all have excellent robust stability. Conclusion: The controllers tuned by ITAE and ISE indexes have excellent steady-state performance, but the overshoot is large during the startup. The controller tuned by IAE index has better startup performance and slightly worse steady-state performance.

Performance analysis of MR damper based semi-active suspension system using optimally tuned controllers

2021 ◽  
pp. 095440702110044
Author(s):  
Gurubasavaraju Tharehalli mata ◽  
Vijay Mokenapalli ◽  
Hemanth Krishna
Keyword(s):  
Pid Controller ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Dynamic Performance ◽  
Parametric Method ◽  
Mr Damper ◽  
Active Suspension ◽  
Suspension System ◽  
Sliding Mode Controller ◽  
Road Excitation

This study assesses the dynamic performance of the semi-active quarter car vehicle under random road conditions through a new approach. The monotube MR damper is modelled using non-parametric method based on the dynamic characteristics obtained from the experiments. This model is used as the variable damper in a semi-active suspension. In order to control the vibration caused under random road excitation, an optimal sliding mode controller (SMC) is utilised. Particle swarm optimisation (PSO) is coupled to identify the parameters of the SMC. Three optimal criteria are used for determining the best sliding mode controller parameters which are later used in estimating the ride comfort and road handling of a semi-active suspension system. A comparison between the SMC, Skyhook, Ground hook and PID controller suggests that the optimal parameters with SMC have better controllability than the PID controller. SMC has also provided better controllability than the PID controller at higher road roughness.

A new control system design for a small hydro-power plant based on particle swarm optimization-fuzzy sliding mode controller with Kalman estimator

2011 ◽  
Vol 34 (4) ◽  
pp. 388-400 ◽  
Author(s):  
A Zargari ◽  
R Hooshmand ◽  
M Ataei
Keyword(s):  
Particle Swarm Optimization ◽  
Control System ◽  
Sliding Mode ◽  
Particle Swarm ◽  
Local Network ◽  
Sliding Mode Controller ◽  
Swarm Optimization ◽  
Hydro Power ◽  
Fuzzy Sliding Mode ◽  
System Variables

One of the main problems in small hydro-power plants that are locally used is their frequency control system. In this paper, a suggested control system based on the fuzzy sliding mode controller is presented for controlling the network frequency. Also, the proposed control strategy is compared with a PI controller and conventional sliding mode controller. In order to regulate the membership functions of fuzzy system more accurately, the particle swarm optimization algorithm is also applied. Moreover, because of unavailability of the control system variables, an estimator is suggested for estimating and identifying the system variables. This estimator will reduce the costs of implementing the control method. The simulation results show the ability of controller system in controlling the local network frequency in the presence of load and parameter’s variations.

Active Vehicle Suspension Control Using Full State-Feedback Controller

2015 ◽  
Vol 1115 ◽  
pp. 440-445 ◽  
Author(s):  
Musa Mohammed Bello ◽  
Amir Akramin Shafie ◽  
Raisuddin Khan
Keyword(s):  
State Feedback ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suspension System ◽  
Feedback Controller ◽  
Vehicle Suspension ◽  
Passive Suspension ◽  
Full State ◽  
Full State Feedback ◽  
Passive Suspension System

The main purpose of vehicle suspension system is to isolate the vehicle main body from any road geometrical irregularity in order to improve the passengers ride comfort and to maintain good handling stability. The present work aim at designing a control system for an active suspension system to be applied in today’s automotive industries. The design implementation involves construction of a state space model for quarter car with two degree of freedom and a development of full state-feedback controller. The performance of the active suspension system was assessed by comparing it response with that of the passive suspension system. Simulation using Matlab/Simulink environment shows that, even at resonant frequency the active suspension system produces a good dynamic response and a better ride comfort when compared to the passive suspension system.

scholarly journals Sliding Mode Control of Laterally Interconnected Air Suspensions

2020 ◽  
Vol 10 (12) ◽  
pp. 4320 ◽  
Author(s):  
Dou Guowei ◽  
Yu Wenhao ◽  
Li Zhongxing ◽  
Amir Khajepour ◽  
Tan Senqi
Keyword(s):  
Ride Comfort ◽  
Control Method ◽  
Sliding Mode ◽  
Suspension System ◽  
Lateral Acceleration ◽  
Sliding Mode Controller ◽  
The Road ◽  
Air Suspension ◽  
Simulation Based ◽  
Different Levels

This paper presents a control method based the lateral interconnected air suspension system, in order to improve the road handling of vehicles. A seven-DOF (Degree of freedom) full-vehicle model has been developed, which considers the features of the interconnected air suspension system, for example, the modeling of the interconnected pipelines and valves by considering the throttling and hysteresis effects. On the basis of the well-developed model, a sliding mode controller has been designed, with a focus on constraining and minimizing the roll motion of the sprung mass caused by the road excitations or lateral acceleration of the vehicle. Moreover, reasonable road excitations have been generated for the simulation based on the coherence of right and left parts of the road. Afterwards, different simulations have been done by applying both bumpy and random road excitations with different levels of roughness and varying vehicle lateral accelerations. The simulation results indicate that the interconnected air suspension without control can improve the ride comfort, but worsen the road handling performance in many cases. However, by applying the proposed sliding mode controller, the road handling of the sprung mass can be improved by 20% to 85% compared with the interconnected or non-interconnected mode at a little cost of comfort.

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