BIOMECHANICAL STABILITY ANALYSIS OF THE λ-MODEL CONTROLLING ONE JOINT

2007 ◽  
Vol 17 (03) ◽  
pp. 193-206 ◽  
Author(s):  
L. LAN ◽  
K. Y. ZHU
Keyword(s):  
Equilibrium Point ◽  
Motor System ◽  
Jacobian Matrix ◽  
System Modeling ◽  
Neuromuscular Disorders ◽  
Biomechanical Stability ◽  
Modeling And Control ◽  
Human Motor ◽  
The Stability ◽  
And Control

Computer modeling and control of the human motor system might be helpful for understanding the mechanism of human motor system and for the diagnosis and treatment of neuromuscular disorders. In this paper, a brief view of the equilibrium point hypothesis for human motor system modeling is given, and the λ-model derived from this hypothesis is studied. The stability of the λ-model based on equilibrium and Jacobian matrix is investigated. The results obtained in this paper suggest that the λ-model is stable and has a unique equilibrium point under certain conditions.

scholarly journals MODELING AND SLIDING MODE CONTROL FOR A SINGLE FLEXIBLE MANIPULATOR

2019 ◽  
Vol 57 (5) ◽  
pp. 645
Author(s):  
Nguyen Quang Hoang ◽  
Ha Anh Son
Keyword(s):  
Jacobian Matrix ◽  
Sliding Mode ◽  
Mass Matrix ◽  
Flexible Manipulator ◽  
Sliding Mode Controller ◽  
The Finite Element Method ◽  
Modeling And Control ◽  
Lagrangian Equations ◽  
The Stability ◽  
And Control

This paper concerns with modeling and control of a single flexible manipulator (SFM). The finite element method (FEM) and Lagrangian equations are exploited to establish the dynamic modeling of SFM. Firstly, the Jacobian matrix is built based on kinematic analysis. Then it is used in construction of a mass matrix for each element. The position and vibration of SFM are controlled by sliding mode controller (SMC). Its parameters are chosen by linearized equations to guarantee the stability of the system. The numerical simulation is carried out to show the efficiency of the proposed approach.

Survey on Aerial Manipulator: System, Modeling, and Control

Robotica ◽  
2019 ◽  
Vol 38 (7) ◽  
pp. 1288-1317 ◽  
Author(s):  
Xiangdong Meng ◽  
Yuqing He ◽  
Jianda Han
Keyword(s):  
System Modeling ◽  
Future Research ◽  
Typical Application ◽  
Modeling And Control ◽  
Aerial Manipulator ◽  
Initial Appearance ◽  
Aerial Vehicle ◽  
New Type ◽  
And Control ◽  
Flying Robot

SUMMARYThe aerial manipulator is a special and new type of flying robot composed of a rotorcraft unmanned aerial vehicle (UAV) and a/several manipulator/s. It has gained a lot of attention since its initial appearance in 2010. This is mainly because it enables traditional UAVs to conduct versatile manipulating tasks from air, considerably enriching their applications. In this survey, a complete and systematic review of related research on this topic is conducted. First, various types of structure designs of aerial manipulators are listed out. Subsequently, the modeling and control methods are introduced in detail from the perspective of two types of typical application cases: free-flight and motion-restricted operations. Finally, challenges for future research are presented.

scholarly journals Model Reduction Methods for Complex Network Systems

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
X. Cheng ◽  
J.M.A. Scherpen
Keyword(s):  
Autonomous Systems ◽  
High Dimensional ◽  
Annual Review ◽  
Publication Date ◽  
Network Systems ◽  
Modeling And Control ◽  
Reduced Order ◽  
Reduction Methods ◽  
The Stability ◽  
And Control

Network systems consist of subsystems and their interconnections and provide a powerful framework for the analysis, modeling, and control of complex systems. However, subsystems may have high-dimensional dynamics and a large number of complex interconnections, and it is therefore relevant to study reduction methods for network systems. Here, we provide an overview of reduction methods for both the topological (interconnection) structure of a network and the dynamics of the nodes while preserving structural properties of the network. We first review topological complexity reduction methods based on graph clustering and aggregation, producing a reduced-order network model. Next, we consider reduction of the nodal dynamics using extensions of classical methods while preserving the stability and synchronization properties. Finally, we present a structure-preserving generalized balancing method for simultaneously simplifying the topological structure and the order of the nodal dynamics. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 3, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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