REAL-TIME IMPLEMENTATION OF FEED RATE ACTIVE FORCE CONTROL OF A SYRINGE FLUID DISPENSER

2017 ◽  
Vol 79 (5) ◽  
Author(s):  
Siti Khadijah Badar Sharif ◽  
Musa Mailah

For precise application, it is imperative to provide accurate and stable performance. The feed flow rate of a syringe fluid dispensing system is regulated through a Proportional- Integral-Derivative (PID) and Active Force Control (AFC) control scheme that was actuated using a DC servo motor considering a real-time implementation. The focus of this study is to control the speed of a DC motor by implementing an AFC strategy in rejecting the disturbance in the system. The AFC is implemented by cascading its control loop with the outer PID controller loop to form a two degree-of-freedom (DOF) controller. The performance of the proposed PID with AFC control scheme was investigated considering both the theoretical simulation and experimental works. The simulation was performed in MATLAB/Simulink computing platform while the real-time experimentation was done by utilising the Arduino MEGA 2560 microcontroller with MATLAB/Simulink driver for the data acquisition, interface and control implementation. The results implies the robustness of the AFC-based system in controlling the feed flow rate of the fluid in the dispenser. The best performance is obtained for 100% AFC with the disturbance due to vibration almost completely compensated via the proposed scheme in comparison to the PID counterpart.

1970 ◽  
Vol 3 (1) ◽  
Author(s):  
Endra Pitowarno, Musa Mailah, Hishamuddin Jamaluddin

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.


2014 ◽  
Vol 6 ◽  
pp. 251594 ◽  
Author(s):  
S. M. Hashemi-Dehkordi ◽  
A. R. Abu-Bakar ◽  
M. Mailah

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.


Author(s):  
Giovanni Jacazio ◽  
Gualtiero Balossini

This paper describes an electronically controlled active force control system that was recently developed to provide real time loading for the tests of a landing gear. As the landing gear moves during the test, a force is generated on the landing gear in order to ensure that its dynamics is identical to that that would occur during its operation in an actual flight. Since landing gear deployment and retraction can occur at different environmental and flight conditions, the load profile that must be developed by the force control system depends on the simulated flight condition and is determined by an appropriate landing gear model. To attain accurate force control, a system was setup comprised of a servovalve controlled hydraulic actuator, force and position sensors, and a high rate digital controller implementing a complex adaptive control law. An excellent accuracy of the load control was eventually achieved for all load profiles occurring on the landing gear.


2012 ◽  
Author(s):  
Musa Mailah ◽  
Wun Shiung Jonathan Chong

Prestasi lasak bagi skema kawalan robot sangat perlu untuk memastikan robot dapat bekerja dengan berkesan seperti yang dikehendaki dalam persekitaran terbatas melibatkan gangguan, perubahan parameter, ketidaktentuan dan kepelbagaian keadaan operasi. Kajian yang dibuat adalah berkaitan dengan satu skema kawalan daya aktif dan algoritma pembelajaran berlelaran (AFCAIL) yang melibatkan satu ciri pembaikan dalam bentuk penggunaan kriteria memberhenti yang sesuai dimuatkan dalam strategi kawalan. Skema tersebut digunapakai terhadap sistem pengolah robotik planar berlengan–dua yang beroperasi secara mendatar. Kriteria memberhenti yang dicadangkan adalah reka bentuk untuk memberhentikan proses pembelajaran berlelaran apabila syarat atau keadaan berkaitan dengan kejituan ketika melakukan tugas serta perolehan matriks inersia anggaran pengolah yang dikehendaki dapat dipenuhi. Dengan cara demikian, robot dikatakan dapat beroperasi dengan baik sebagaimana yang diarahkan. Keberkesanan skema juga dikaji dengan mengambil kira beberapa keadaan bebanan dan operasi. Kata kunci: Robot; kawalan daya aktif; algoritma pembelajaran berlelaran; kriterion memberhenti The robust performance of a robot control scheme is vital to ensure that the robot accomplishes its tasks desirably in a constraint environment involving disturbances, parametric changes, uncertainties and varied operating conditions. The study introduces the Active Force Control and Iterative Learning Algorithm (AFCAIL) scheme with an improved feature in the form of a suitably designed stopping criterion incorporated in the control strategy. The scheme is applied to the control of a horiziontally operated robotic two–link planar manipulator. The proposed stopping criterion is specifically designed to halt the iterative learning process when the conditions related to the accuracy of the performed tasks and the acquisition of appropriate estimated inertia matrix of the robot arm are favourably met. In this way, the robot is said to perform desirably and excellently. The effectiveness of the scheme is also investigated by considering a number different loading and operating conditions. Key words: Robot; active force control; iterative learning algorithm; stopping criterion


Author(s):  
Musa Mailah ◽  
Miaw Yong Ong

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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