Modelling and control of a piezo actuated micro robot with active force control capability for in-pipe application

2011 ◽  
Vol 13 (4) ◽  
pp. 301 ◽  
Author(s):  
Yaser Sabzehmeidani ◽  
Musa Mailah ◽  
Mohamed Hussein
Keyword(s):  
Force Control ◽  
Active Force ◽  
Active Force Control ◽  
Micro Robot ◽  
Control Capability ◽  
And Control

A hybrid active force control of a lower limb exoskeleton for gait rehabilitation

2018 ◽  
Vol 63 (4) ◽  
pp. 491-500 ◽  
Author(s):  
Zahari Taha ◽  
Anwar P.P. Abdul Majeed ◽  
Amar Faiz Zainal Abidin ◽  
Mohammed A. Hashem Ali ◽  
Ismail Mohd Khairuddin ◽  
...  
Keyword(s):  
Force Control ◽  
Lower Limb ◽  
Sagittal Plane ◽  
Joint Space ◽  
Gait Rehabilitation ◽  
Active Force ◽  
Lower Limb Exoskeleton ◽  
Active Force Control ◽  
Increasing Demand ◽  
And Control

Abstract Owing to the increasing demand for rehabilitation services, robotics have been engaged in addressing the drawbacks of conventional rehabilitation therapy. This paper focuses on the modelling and control of a three-link lower limb exoskeleton for gait rehabilitation that is restricted to the sagittal plane. The exoskeleton that is modelled together with a human lower limb model is subjected to a number of excitations at its joints while performing a joint space trajectory tracking, to investigate the effectiveness of the proposed controller in compensating disturbances. A particle swarm optimised active force control strategy is proposed to facilitate disturbance rejection of a conventional proportional-derivative (PD) control algorithm. The simulation study provides considerable insight into the robustness of the proposed method in attenuating the disturbance effect as compared to the conventional PD counterpart without compromising its tracking performance. The findings from the study further suggest its potential employment on a lower limb exoskeleton.

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

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.

scholarly journals Robust Motion Control for Mobile Manipulator Using Resolved Acceleration and Proportional-Integral Active Force Control

10.5772/5794 ◽  
2005 ◽  
Vol 2 (2) ◽  
pp. 14 ◽  
Author(s):  
Musa Mailah ◽  
Endra Pitowarno ◽  
Hishamuddin Jamaluddin
Keyword(s):  
Motion Control ◽  
Force Control ◽  
Dynamic Control ◽  
Mobile Manipulator ◽  
Active Force ◽  
Proportional Integral ◽  
Active Force Control ◽  
Resolved Acceleration Control ◽  
Unknown Disturbances ◽  
Robust Motion Control

A resolved acceleration control (RAC) and proportional-integral active force control (PIAFC) is proposed as an approach for the robust motion control of a mobile manipulator (MM) comprising a differentially driven wheeled mobile platform with a two-link planar arm mounted on top of the platform. The study emphasizes on the integrated kinematic and dynamic control strategy in which the RAC is used to manipulate the kinematic component while the PIAFC is implemented to compensate the dynamic effects including the bounded known/unknown disturbances and uncertainties. The effectivenss and robustness of the proposed scheme are investigated through a rigorous simulation study and later complemented with experimental results obtained through a number of experiments performed on a fully developed working prototype in a laboratory environment. A number of disturbances in the form of vibratory and impact forces are deliberately introduced into the system to evaluate the system performances. The investigation clearly demonstrates the extreme robustness feature of the proposed control scheme compared to other systems considered in the study.

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