Performance Analysis of the Computed Torque Based Active Force Control for a Planar Parallel Manipulator

Noshadi, Amin; Zolfagharian, Ali; Mailah, Musa

doi:10.4028/www.scientific.net/amm.110-116.4932

Cited by 3 publications

(2 citation statements)

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“…The Golubev method [21] is used to estimate an appropriate model for control of the actuator [22,23,24,25]. Using the Golubev method for the input signal, the uncertain transfer function relating the applied voltage to the bending angle of the actuator is estimated as:G(s)=eβsa1s3+a2s2+a3s+a4b1s4+b2s3+b3s2+b4s+b5,…”

Section: Modelling and Experimental Resultsmentioning

confidence: 99%

Control-Oriented Modelling of a 3D-Printed Soft Actuator

et al. 2018

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A new type of soft actuator was developed by using hydrogel materials and three-dimensional (3D) printing technology, attracting the attention of researchers in the soft robotics field. Due to parametric uncertainties of such actuators, which originate in both a custom design nature of 3D printing as well as time and voltage variant characteristics of polyelectrolyte actuators, a sophisticated model to estimate their behaviour is required. This paper presents a practical modeling approach for the deflection of a 3D printed soft actuator. The suggested model is composed of electrical and mechanical dynamic models while the earlier version describes the actuator as a resistive-capacitive (RC) circuit. The latter model relates the ionic charges to the bending of an actuator. The experimental results were acquired to estimate the transfer function parameters of the developed model incorporating Takagi-Sugeno (T-S) fuzzy sets. The proposed model was successful in estimating the end-point trajectory of the actuator, especially in response to a broad range of input voltage variation. With some modifications in the electromechanical aspects of the model, the proposed modelling method can be used with other 3D printed soft actuators.

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Section: Modelling and Experimental Resultsmentioning

confidence: 99%

Control-Oriented Modelling of a 3D-Printed Soft Actuator

et al. 2018

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“…Hence, actuating force can be measured simply by force transducers, and accelerometer can provide the value of a′. The estimated mass may be given by assuming a perfect model, crude approximation [25,34,35], or intelligent method [29]. In other words, if all parameters have been obtained successfully, the resulting estimated force from equation (5) would result in a stable and robust performance of the proposed control system [28].…”

Section: Active Force Controlmentioning

confidence: 99%

Active Off-Road Seat Suspension System Using Intelligent Active Force Control

Gohari

Tahmasebi

2015

Journal of Low Frequency Noise, Vibration and Active Control

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Transmitted vibration from vehicles to driver body generates some problems in the long term. Passive and active seat suspensions are used in heavy duty vehicles to reduce unwanted vibration and prevent health problems due to oscillation. Seat suspension must minimize the driver's body displacement and acceleration to increase riding convenience. Active force control (AFC) method is a new technique which is used in active controllers and makes them more accurate. Therefore, this work represents the possibility of applying AFC strategy for an active seat suspension control to increase its robustness. An AFC-based scheme is designed and simulated in MATLAB software. In addition, artificial neural network (ANN) is integrated into the AFC loop to approximate estimated mass of the seat and human body for the proposed controller. The training of ANN with multi-layer feedforward structure is carried out using Levenberg-Marquardt learning algorithm. To evaluate the neuro-AFC control system robustness, the seat is subjected to various types of disturbances. The results of the present study illustrate that the neuro-AFC technique is computationally simple and efficient compared to the classic proportional-integral-derivative (PID) controller in suppressing undesired vibration of heavy duty vehicles' seat. The neuro-AFC scheme is found to demonstrate superior performance for various road profiles compared to pure PID controller, and it can be successfully utilized in heavy duty vehicles such as industrial and agricultural tractors.

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