A Unified Adaptive Control Law Design for Rigid Body Robots via a Hamiltonian Property

1992 ◽  
Author(s):  
Shuzhi S. Ge ◽  
J.C Allwright ◽  
C.B. Besant
Keyword(s):  
Adaptive Control ◽  
Rigid Body ◽  
Control Law ◽  
Hamiltonian Property ◽  
Adaptive Control Law

Leader-Following Adaptive Consensus of Multiple Uncertain Rigid Body Systems over Jointly Connected Networks

2019 ◽  
Vol 08 (02) ◽  
pp. 85-93
Author(s):  
Tianqi Wang ◽  
Jie Huang
Keyword(s):  
Adaptive Control ◽  
Rigid Body ◽  
Switching Network ◽  
Control Law ◽  
Consensus Problem ◽  
System Matrix ◽  
Switching Networks ◽  
Distributed Adaptive Control ◽  
Leader Following ◽  
Adaptive Control Law

The leader-following consensus problem of a group of uncertain multiple rigid body systems subject to static networks has been solved by a distributed adaptive control law utilizing the distributed observer for the leader system. In this paper, we extend this result to jointly connected switching networks. This extension needs to overcome the discontinuity of some variables caused by the switching network. Additionally, we remove the assumption that every follower knows the system matrix of the leader system by employing an adaptive distributed observer for the leader system.

A road-adaptive control law for semi-active suspensions

1999 ◽  
Vol 13 (10) ◽  
pp. 667-676 ◽  
Author(s):  
Youngjoo Cho ◽  
Byung Suk Song ◽  
Kyongsu Yi
Keyword(s):  
Adaptive Control ◽  
Control Law ◽  
Active Suspensions ◽  
Adaptive Control Law

Function Projective Dual Synchronization with Uncertain Parameters of Hyperchaotic Systems

2017 ◽  
Vol 6 (4) ◽  
pp. 1-16 ◽  
Author(s):  
A. Almatroud Othman ◽  
M.S.M. Noorani ◽  
M. Mossa Al-sawalha
Keyword(s):  
Adaptive Control ◽  
Lyapunov Stability Theory ◽  
Control Law ◽  
Uncertain Parameters ◽  
Unknown Parameters ◽  
Chen System ◽  
Response Systems ◽  
Hyperchaotic Lu System ◽  
Hyperchaotic Systems ◽  
Adaptive Control Law

Function projective dual synchronization between two pairs of hyperchaotic systems with fully unknown parameters for drive and response systems is investigated. On the basis of the Lyapunov stability theory, a suitable and effective adaptive control law and parameters update rule for unknown parameters are designed, such that function projective dual synchronization between the hyperchaotic Chen system and the hyperchaotic Lü system with unknown parameters is achieved. Theoretical analysis and numerical simulations are presented to demonstrate the validity and feasibility of the proposed method.

Dynamic Modeling and Adaptive Control of a Single Degree-of-Freedom Flexible Cable-Driven Parallel Robot

2019 ◽  
Vol 141 (10) ◽  
Author(s):  
Harsh Atul Godbole ◽  
Ryan James Caverly ◽  
James Richard Forbes
Keyword(s):  
Adaptive Control ◽  
Numerical Simulations ◽  
Dynamic Modeling ◽  
Parallel Robot ◽  
Control Law ◽  
Single Degree Of Freedom ◽  
Flexible Cable ◽  
Single Degree ◽  
Cable Properties ◽  
Adaptive Control Law

This paper investigates the dynamic modeling and adaptive control of a single degree-of-freedom flexible cable-driven parallel robot (CDPR). A Rayleigh–Ritz cable model is developed that takes into account the changes in cable mass and stiffness due to its winding and unwinding around the actuating winch, with the changes distributed throughout the cables. The model uses a set of state-dependent basis functions for discretizing cables of varying length. A novel energy-based model simplification is proposed to further facilitate reduction in the computational load when performing numerical simulations involving the Rayleigh–Ritz model. For control purposes, the massive payload assumption is used to decouple the rigid and elastic dynamics of the system, and a modified input torque and modified output payload rate are used to develop a passive input–output map for the naturally noncollocated system. A passivity-based adaptive control law is derived to dynamically adapt to changes in cable properties and payload inertia, and different forms of the adaptive control law regressor are proposed. It is shown through numerical simulations that the adaptive controller is robust to changes in payload mass and cable properties, and the selection of the regressor form has a significant impact on the performance of the controller.

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