Robust IDA-PBC for under-actuated systems with inertia matrix dependent of the unactuated coordinates: application to a UAV carrying a load

2021 ◽  
Author(s):  
M. E. Guerrero-Sánchez ◽  
O. Hernández-González ◽  
G. Valencia-Palomo ◽  
D. A. Mercado-Ravell ◽  
F. R. López-Estrada ◽  
...  
Keyword(s):  
Inertia Matrix

Alternate Formulations for the Manipulator Inertia Matrix

1991 ◽  
Vol 10 (1) ◽  
pp. 64-74 ◽  
Author(s):  
Kathryn W. Lilly ◽  
David E. Orin
Keyword(s):  
Inertia Matrix

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.

Propagation of Nonlinearities in the Inertia Matrix of Tracked Vehicles

1994 ◽  
Author(s):  
J. H. Choi ◽  
A. A. Shabana ◽  
Roger A. Wehage
Keyword(s):  
Numerical Solution ◽  
Vehicle Dynamics ◽  
Equations Of Motion ◽  
Coefficient Matrix ◽  
Influence Coefficient ◽  
Dynamic Force ◽  
Tracked Vehicles ◽  
Revolute Joints ◽  
Inertia Matrix ◽  
Force Coupling

Abstract In this investigation, a procedure is presented for the numerical solution of tracked vehicle dynamics equations of motion. Tracked vehicles can be represented as two kinematically decoupled subsystems. The first is the chassis subsystem which consists of chassis, rollers, idlers, and sprockets. The second is the track subsystem which consists of track links interconnected by revolute joints. While there is dynamic force coupling between these two subsystems, there is no inertia coupling since the kinematic equations of the two subsystems are not coupled. The objective of the procedure developed in this investigation is to take advantage of the fact that in many applications, the shape of the track does not significantly change even though the track links undergo significant configurations changes. In such cases the nonlinearities propagate along the diagonals of a velocity influence coefficient matrix. This matrix is the only source of nonlinearities in the generalized inertia matrix. A permutation matrix is introduced to minimize the number of generalized inertia matrix LU factor evaluations for the track.

A Study on the Simulation of Flexible Link Mechanics Based on FEM

1997 ◽  
Author(s):  
Koichi Honke ◽  
Yoshio Inoue ◽  
Eiko Hirooka ◽  
Naoki Sugano
Keyword(s):  
Stiffness Matrix ◽  
Large Displacement ◽  
Dynamics Analysis ◽  
Flexible Link ◽  
Finite Rotation ◽  
Fem Model ◽  
Elastic Vibrations ◽  
Link Structure ◽  
Geometric Stiffness ◽  
Inertia Matrix

Abstract The dynamics analysis of link structure, including elastic vibrations, is presented. The two nodes element including large displacement is developed. This element is based on the theory of finite rotation, and includes geometric stiffness. The stiffness matrix and the inertia matrix are obtained from the FEM model by the theory of Guyan’s reduction including large displacement motion. In this paper, we explain the theory of this element and show some examples of analysis.

scholarly journals Satellite Inertia Parameters Estimation Based on Extended Kalman Filter

2019 ◽  
Author(s):  
Abdellatif Bellar ◽  
Mohammed Arezki Si Mohammed
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Critical Role ◽  
Low Earth Orbit ◽  
Parameters Estimation ◽  
Moment Of Inertia ◽  
Satellite Mission ◽  
Inertia Matrix ◽  
Inertia Parameters ◽  
The Moment

The moment of inertia parameters play a critical role in assuring the spacecraft mission throughout its lifetime. However, determination of the moment of inertia is a key challenge in operating satellites. During satellite mission, those parameters can change in orbit for many reasons such as sloshing, fuel consumption, etc. Therefore, the inertia matrix should be estimated in orbit to enhance the attitude estimation and control accuracy. This paper investigates the use of gyroscope to estimate the attitude rate and inertia matrix for low earth orbit satellite via extended Kalman filter. Simulation results show the effectiveness and advantages of the proposed algorithm in estimating these parameters without knowing the nominal inertia. The robustness of the proposed algorithm has been validated using the Monte-Carlo method. The obtained results demonstrate that the accuracy of the estimated inertia and angular velocity parameters is satisfactory for satellite with coarse accuracy mission requirements. The proposed method can be used for different types of satellites.

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

91.28 The inertia matrix of a uniform solid

2007 ◽  
Vol 91 (520) ◽  
pp. 148-152
Author(s):  
M. A. Grant
Keyword(s):  
Inertia Matrix
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