IMPLEMENTING ACTIVE FORCE CONTROL TO REDUCE VIBRATION OF A SHORT LENGTH DRIVE SHAFT

2016 ◽  
Vol 78 (10) ◽  
Author(s):  
Mustafa Mohebbi ◽  
Mahdi Hashemi ◽  
Musa Mailah
Keyword(s):  
Force Control ◽  
Pid Controller ◽  
Physical Phenomenon ◽  
Low Frequency ◽  
Short Length ◽  
Drive Shaft ◽  
Active Force ◽  
Active Force Control ◽  
In Series ◽  
Three Degree Of Freedom

Vibration is a physical phenomenon involving repeated oscillatory movements or fluctuations at certain frequency and typically undesirable in many applications since it may cause undue failure or damage to the system. In this paper, the vibration of a three degree-of-freedom (DOF) model representing a short length drive shaft has been effectively and robustly suppressed through the implementation of a novel Active Force Control (AFC) used in conjunction with a classic proportional-integral-derivative (PID) controller. The shaft vibration caused by its support and constraint during its operation was simulated using MATLAB and Simulink considering a number of operating and loading conditions. The results proved that when a pure PID controller was implemented, the vibration is indeed reduced but at the expense of longer execution time and producing noticeable frequency oscillation with slight offset. On the other hand, when the AFC loop was engaged by adding it directly in series with the PID controller (PID+AFC) to produce a 2 DOF controller without any need to further tune the PID controller gains, the vibration is significantly reduced with the amplitude hovering a zero datum without any offset and yielding an extremely low frequency trending. 

scholarly journals Stability Analysis of a Linear Friction-Induced Vibration Model and Its Prevention Using Active Force Control

2014 ◽  
Vol 6 ◽  
pp. 251594 ◽  
Author(s):  
S. M. Hashemi-Dehkordi ◽  
A. R. Abu-Bakar ◽  
M. Mailah
Keyword(s):  
Force Control ◽  
Pid Controller ◽  
Active Force ◽  
Active Force Control ◽  
Vibration Model ◽  
Control Scheme ◽  
Linear Friction ◽  
Critical Slope ◽  
Negative Damping ◽  
Friction Induced Vibration

This paper presents friction-induced vibration (FIV) caused by combined mode-coupling and negative damping effects in a simple FIV model. In doing so, a new four-degree-of-freedom linear model which consists of a slider and a block is proposed and then simulated using MATLAB/Simulink. Stability or instability of the FIV model is defined by the convergence or divergence of time domain responses of the slider and the block. Having found critical slope of friction-velocity characteristics that generate instabilities in the model, a conventional closed loop proportional-integral-derivative (PID) controller is first introduced into the main model in order to attenuate the vibration level and subsequently to suppress it. Later, the model is integrated with the active force control (AFC) element to effectively reject the disturbance and reduce the vibrations. It is found that the integrated PID-AFC scheme is effective in reducing vibration compared to the pure PID controller alone. Thus, the proposed control scheme can be one of the potential solutions to suppress vibration in a friction-induced vibration system.

Active Force Control Applied to Spray Boom Structure

2013 ◽  
Vol 315 ◽  
pp. 616-620 ◽  
Author(s):  
Mona Tahmasebi ◽  
Roslan Abdul Rahman ◽  
Musa Mailah ◽  
Mohammad Gohari
Keyword(s):  
Pid Control ◽  
Force Control ◽  
High Frequency ◽  
Pid Controller ◽  
Active Force ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Active Force Control ◽  
Simulation Results ◽  
Vertical Vibrations

Distribution pattern of spray boom in fields is affected by several parameters which one of the important reasons is horizontal and vertical vibrations because of unevenness surfaces. Spray boom movements lead to decrease of spread efficiency and crop yield. Generally, active suspension is employed to control and attenuate the vibration of sprayer booms because these suspensions reduce the high frequency vibration of spray booms thanks to irregularities soil. In this research, a proportional-integral-derivative controller with active force control is used to remove undesired rolling of spray boom. Simulation results depict that the proposed scheme is more effective and accurate than PID control only scheme. The AFC based scheme shows the robustness and accuracy compared to the PID controller.

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

2011 ◽  
Vol 110-116 ◽  
pp. 4932-4940 ◽  
Author(s):  
Amin Noshadi ◽  
Ali Zolfagharian ◽  
Gang Wang
Keyword(s):  
Force Control ◽  
Parallel Manipulator ◽  
Active Force ◽  
Active Force Control ◽  
Novel Approach ◽  
Planar Parallel Manipulator ◽  
Unknown Disturbances ◽  
In Series ◽  
Trajectory Tracking Controller ◽  
Computed Torque

This paper presents a novel approach to control a 3-RRR (revolute-revolute-revolute) planar parallel manipulator applying an active force control (AFC) strategy. A PID-based computed torque controller (CTC) was first designed and developed to demonstrate the basic and stable response of the manipulator in order to follow a prescribed trajectory. Then, the AFC part was incorporated into the control scheme in series with the CTC (AFC-CTC) in a cascade form. Performance of the system was demonstrated by the computer simulation results. By using the AFC method, the design of trajectory tracking controller can be conducted based on a precise model of the system. The overall tracking performance was improved with using AFC scheme in presence of known or unknown disturbances. Results clearly illustrate the robustness and effectiveness of the proposed AFC-based scheme as a robust disturbance rejecter compared to the conventional CT controller.

scholarly journals Knowledge-Based Trajectory Error Pattern Method Applied to an Active Force Control Scheme

1970 ◽  
Vol 3 (1) ◽  
Author(s):  
Endra Pitowarno, Musa Mailah, Hishamuddin Jamaluddin
Keyword(s):  
Force Control ◽  
Error Pattern ◽  
Robot Arm ◽  
Active Force ◽  
Trajectory Error ◽  
Track Error ◽  
Knowledge Based ◽  
Inertia Matrix ◽  
Active Force Control ◽  
Control Scheme

The active force control (AFC) method is known as a robust control scheme that dramatically enhances the performance of a robot arm particularly in compensating the disturbance effects. The main task of the AFC method is to estimate the inertia matrix in the feedback loop to provide the correct (motor) torque required to cancel out these disturbances. Several intelligent control schemes have already been introduced to enhance the estimation methods of acquiring the inertia matrix such as those using neural network, iterative learning and fuzzy logic. In this paper, we propose an alternative scheme called Knowledge-Based Trajectory Error Pattern Method (KBTEPM) to suppress the trajectory track error of the AFC scheme. The knowledge is developed from the trajectory track error characteristic based on the previous experimental results of the crude approximation method. It produces a unique, new and desirable error pattern when a trajectory command is forced. An experimental study was performed using simulation work on the AFC scheme with KBTEPM applied to a two-planar manipulator in which a set of rule-based algorithm is derived. A number of previous AFC schemes are also reviewed as benchmark. The simulation results show that the AFC-KBTEPM scheme successfully reduces the trajectory track error significantly even in the presence of the introduced disturbances.Key Words:  Active force control, estimated inertia matrix, robot arm, trajectory error pattern, knowledge-based.

Intelligent Adaptive Active Force Control of a Robotic Arm with Embedded Iterative Learning Algorithms

2012 ◽  
Author(s):  
Musa Mailah ◽  
Miaw Yong Ong
Keyword(s):  
Force Control ◽  
Learning Algorithms ◽  
Iterative Learning ◽  
Operating Conditions ◽  
Robotic Arm ◽  
Active Force ◽  
Inertia Matrix ◽  
Active Force Control ◽  
Controller Gain ◽  
On Line

Kawalan jitu dan lasak bagi satu sistem lengan robot atau pengolah adalah amat penting terutama sekali jika sistem mengalami pelbagai bentuk bebanan dan keadaan pengendalian. Kertas kerja ini memaparkan satu kaedah baru dan lasak untuk mengawal lengan robot menggunakan teknik pembelajaran secara berlelaran yang dimuatkan dalam strategi kawalan daya aktif. Sebanyak dua algoritma pembelajaran utama digunakan dalam kajian – yang pertama digunakan untuk menala gandaan pengawal secara automatik manakala yang satu lagi pula untuk menganggarkan matriks inersia pengolah. Kedua-dua parameter ini dihasilkan secara adaptif dan dalam talian ketika robot sedang menjalankan tugas menjejak trajektori dalam persekitaran tindakan daya gangguan. Dalam kajian ini, pengetahuan awal tentang kedua–dua nilai gandaan pengawal dan anggaran matriks inersia tidak wujud. Dengan demikian, suatu skema kawalan yang jitu dan lasak terhasil. Keberkesanan kaedah yang dicadangkan dapat ditentusahkan melalui hasil kajian yang diperoleh dan dibentangkan dalam kertas kerja ini. Kata kunci: Adaptif; kawalan daya aktif; pembelajaran berlelaran; matriks inersia; gandaan pengawal The robust and accurate control of a robotic arm or manipulator are of prime importance especially if the system is subjected to varying forms of loading and operating conditions. The paper highlights a novel and robust method to control a robotic arm using an iterative learning technique embedded in an active force control strategy. Two main iterative learning algorithms are utilized in the study – the first is used to automatically tune the controller gains while the second to estimate the inertia matrix of the manipulator. These parameters are adaptively computed on-line while the robot is executing a trajectory tracking task and subject to some forms of external disturbances. No priori knowledge of both the controller gains and the estimated inertia matrix are ever assumed in the study. In this way, an adaptive and robust control scheme is derived. The effectiveness of the method is verified and can be seen from the results of the work presented in this paper. Keywords: Adaptive; active force control; iterative learning; inertia matrix; controller gain

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