Force control of electro-active polymer actuators using model-free intelligent control

2021 ◽  
pp. 1045389X2098699
Author(s):  
Caner Sancak ◽  
Fatma Yamac ◽  
Mehmet Itik ◽  
Gürsel Alici
Keyword(s):  
Intelligent Control ◽  
Control Method ◽  
Controller Design ◽  
Implementation Process ◽  
Pso Algorithm ◽  
Actuator Dynamics ◽  
Model Free ◽  
Control Framework ◽  
Controller Performance ◽  
Model Free Control

In this paper, a model-free control framework is proposed to control the tip force of a cantilevered trilayer CPA and similar cantilevered smart actuators. The proposed control method eliminates the requirement of modeling the CPAs in controller design for each application, and it is based on the online local estimation of the actuator dynamics. Due to the fact that the controller has few parameters to tune, this control method provides a relatively easy design and implementation process for the CPAs as compared to other model-free controllers. Although it is not vital, in order to optimize the controller performance, a meta-heuristic particle swarm optimization (PSO) algorithm, which utilizes an initial baseline model that approximates the CPAs dynamics, is used. The performance of the optimized controller is investigated in simulation and experimentally. Successful results are obtained with the proposed controller in terms of control performance, robustness, and repeatability as compared with a conventional optimized PI controller.

Intelligent PD controller design for active suspension system based on robust model-free control strategy

2019 ◽  
Vol 233 (14) ◽  
pp. 4863-4880 ◽  
Author(s):  
Maroua Haddar ◽  
Riadh Chaari ◽  
S Caglar Baslamisli ◽  
Fakher Chaari ◽  
Mohamed Haddar
Keyword(s):  
Controller Design ◽  
Design Method ◽  
Active Suspension ◽  
Vehicle Speed ◽  
Pd Controller ◽  
Suspension Systems ◽  
Model Free ◽  
Robust Model ◽  
Road Disturbance ◽  
Model Free Control

A novel active suspension control design method is proposed for attenuating vibrations caused by road disturbance inputs in vehicle suspension systems. For the control algorithm, we propose an intelligent PD controller structure that effectively rejects online estimated disturbances. The main theoretical techniques used in this paper consist of an ultra-local model which replaces the mathematical model of quarter car system and a new algebraic estimator of unknown information. The measurement of only input and output variables of the plant is required for achieving the reference tracking task and the cancellation of unmodeled exogenous and endogenous perturbations such as roughness road variation, unpredictable variation of vehicle speed and load variation. The performance and robustness of the proposed active suspension algorithm are compared with ADRC control and LQR control. Numerical results are provided for showing the improvement of passenger comfort criteria with model-free control.

PSO OPTIMIZATION FOR SOLAR SYSTEM INVERTER CONTROLLER AND COMPARISON BETWEEN TWO CONTROLLER TECHNIQUES

2016 ◽  
Vol 78 (6-2) ◽  
Author(s):  
Maher. G. M. Abdolrasol ◽  
M A Hannan ◽  
Azah Mohamed
Keyword(s):  
Solar System ◽  
Controller Design ◽  
Pso Algorithm ◽  
Pi Controller ◽  
Housing Unit ◽  
Current Waveform ◽  
Phase Voltage ◽  
Swarm Optimization ◽  
Three Phase ◽  
Controller Performance

This paper explains a deep comparison between two controller techniques firstly controller control on modulation index and the second controller use dq method. Both of these controller approaches have control on three phase voltage and use the same system unchanged. The system is a solar system together with a backup battery connected to a single housing unit. Particle Swarm Optimization (PSO) algorithm has been utilized to improve the controller performance by automatically finding its parameters in order to reduce the error in the proportional Integral (PI) controller. Optimization process has been done with a real recording data of housing unit demand in Malaka, Malaysia. System has been simulated and tested in MATLAB/Simulink environment with m-file runs PSO algorithm and simulate the system hundreds of times to get the best results showing in this paper. Comparisons were taking place in controller design and in the simulation results that express the strength and weaken points of each controller starts with THD voltage and current waveform and RMS voltage in each controller.  

scholarly journals Quantized Feedback Control of Active Suspension Systems Based on Event Trigger

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jinwei Sun ◽  
Jingyu Cong ◽  
Weihua Zhao ◽  
Yonghui Zhang
Keyword(s):  
Feedback Control ◽  
Control Method ◽  
Controller Design ◽  
Sliding Mode ◽  
External Disturbance ◽  
Active Suspension ◽  
Trigger Mechanism ◽  
Actuator Dynamics ◽  
Quantized Feedback ◽  
Event Trigger

As the deviation error will accumulate during the data acquisition and transcoding process of an active suspension system, this paper presents a sliding-mode-based quantized feedback control method. The aim of the controller is to improve the vertical performance of vehicles in the presence of external interferences. A 7-DOF suspension model with nonlinear springs and actuator dynamics is built for the control purpose. Firstly, a static quantizer on the uplink channel and a dynamic quantizer on the downlink channel are considered in the sliding mode controller to reduce the cumulative error and suppress the sprung mass motions. Secondly, an event trigger mechanism is introduced in the controller design process to reduce energy consumption and operation frequency of the actuator. The overall stability of the designed controller is proved by the Lyapunov functions. Finally, numerical simulations are carried out to evaluate the efficacy of the proposed controller. Different quantitative and trigger conditions are discussed, and the random road excitation is considered as the external disturbance input. The results of the control method indicate that the designed controller can improve the riding comfort with little loss of handling stability compared with the passive system. In addition, the trigger mechanism can improve the working efficiency of actuators effectively.

scholarly journals Robust Model-Free Control for Robot Manipulator under Actuator Dynamics

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Dorsaf Elleuch ◽  
Tarak Damak
Keyword(s):  
Sliding Mode ◽  
Robot Manipulator ◽  
Lyapunov Theory ◽  
Pd Control ◽  
External Disturbances ◽  
Actuator Dynamics ◽  
Model Free ◽  
Robust Model ◽  
Parameter Variations ◽  
Model Free Control

An intelligent proportional-derivative sliding mode controller (i-PDSMC) is presented to overcome the unmodeled complexity of the robot manipulator under an actuator. i-PDSMC is a free model intelligent control based on the ultralocal, sliding mode, and PD control structure. A stability condition is determined by the Lyapunov theory. A comparative study between a classical PD, an intelligent PD control, and i-PDSMC is done through a robot manipulator under actuators. The simulation results prove that the proposed controller is more robust to trajectory tracking under parameter variations and external disturbances.

The Model-free Adaptive Composite Control Method for Permanent Magnet Linear Motor

2015 ◽  
Vol 7 (2) ◽  
pp. 30-44
Author(s):  
Rongmin Cao ◽  
Su Zhong ◽  
Shizhen Liu
Keyword(s):  
Permanent Magnet ◽  
Control Method ◽  
Controller Design ◽  
Adaptive Controller ◽  
Linear Motor ◽  
Modeling And Control ◽  
Composite Control ◽  
Model Free ◽  
Permanent Magnet Linear Motor ◽  
Force Ripple

A composite control method based on the model-free adaptive control is applied to the position or speed control of the linear motor. The model-free adaptive controller (MFAC) broke through the classical PID controller design of linear framework, is a kind of new controller, it' structure is adaptive and a kind of integration of modeling and control method. The composite control method includes an adaptive feedforward compensator which is designed to eliminate or suppress the effects of inherent force ripple for a permanent magnet linear motor (PMLM). Simulation results show that compared with PID control, the proposed composite control algorithm is more effective for the strong coupling of nonlinear system and difficult to realize stable control. And the response performance of the system is realized.

scholarly journals A model-free control method for estimating the joint angles of the knee exoskeleton

2018 ◽  
Vol 10 (10) ◽  
pp. 168781401880776 ◽  
Author(s):  
Yan Zhang ◽  
Jianzhou Wang ◽  
Wei Li ◽  
Jie Wang ◽  
Peng Yang
Keyword(s):  
Knee Joint ◽  
Joint Angle ◽  
Control Method ◽  
Sliding Mode ◽  
Control Law ◽  
Joint Angles ◽  
Output Data ◽  
Model Free ◽  
Model Free Control ◽  
Discrete Sliding Mode Control

This article describes a model-free adaptive control method for knee joint exoskeleton, which avoids the complexity of human–exoskeleton modeling. An important feature of the proposed controller is that it uses the input and output data of the knee joint angle to control the exoskeleton. Furthermore, discrete sliding mode control law and prior torque are introduced to improve the accuracy and robustness of the system. Prior torque of knee joint is obtained through the walking simulation of human–exoskeleton modeling. Specially, the experiment is carried out by using the co-simulation automatic dynamic analysis of mechanical systems and MATLAB. Data from these assessments indicate that the proposed strategy enables the knee exoskeleton to track the trajectory of angle well and has a good performance on walking assistance.

Model Free Control of the Refrigeration System Based on Minimum Stable Superheat

2013 ◽  
Vol 397-400 ◽  
pp. 1373-1377
Author(s):  
Bao Hua Cheng ◽  
Ai Guo Wu ◽  
Yu Wen You
Keyword(s):  
Pid Control ◽  
Control Method ◽  
Coupling Effect ◽  
Dynamic Performance ◽  
Variable Load ◽  
Refrigeration System ◽  
Applied Model ◽  
Model Free ◽  
Model Free Control ◽  
Steady State Performance

This paper applied model free control method to the refrigeration system evaporator minimum stable superheat control. Compared with conventional PID control, model free control method has fast convergence, anti-interference ability. Meanwhile, model free control can reduce the coupling effect between evaporator superheat and evaporating temperature and be well adapted to the variable load control requirements of the refrigeration system, which has good steady state performance and dynamic performance.

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