Neuroadaptive Control for Complicated Underactuated Systems With Simultaneous Output and Velocity Constraints Exerted on Both Actuated and Unactuated States

SUMMARY Many different control schemes have been proposed in the technical literature to control the special class of underactuated systems, the- so-called brachiation robots. However, most of these schemes are limited with regard to the method by which the robot executes the brachiation movement. Moreover, many of these control strategies do not take into account the energy of the system as a decision variable. To observe the behavior of the system’s, energy is very important for a better understanding of the robot dynamics while performing the motion. This paper discusses a variety of energy-based strategies to better understand how the system’s energy may influence the type of motion (under-swing or overhand) the robot should perform.

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Coordination of a Class of Underactuated Systems via Sampled-Data-Based Event-Triggered Schemes

IEEE Transactions on Systems Man and Cybernetics Systems ◽

10.1109/tsmc.2020.3048201 ◽

2021 ◽

pp. 1-11

Author(s):

Xiang-Yu Yao ◽

Ju H. Park ◽

Hua-Feng Ding ◽

Ming-Feng Ge

Keyword(s):

Underactuated Systems ◽

Sampled Data ◽

Event Triggered

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Embedded model control for underactuated systems: An application to Furuta pendulum

Control Engineering Practice ◽

10.1016/j.conengprac.2021.104854 ◽

2021 ◽

Vol 113 ◽

pp. 104854

Author(s):

Wilber Acuña-Bravo ◽

Andrés Guillermo Molano-Jiménez ◽

Enrico Canuto

Keyword(s):

Underactuated Systems ◽

Model Control ◽

Embedded Model

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H/sup ∞/-optimal tracking control techniques for nonlinear underactuated systems

Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187) ◽

10.1109/cdc.2000.914100 ◽

2002 ◽

Cited By ~ 32

Author(s):

G.J. Toussaint ◽

T. Basar ◽

F. Bullo

Keyword(s):

Tracking Control ◽

Underactuated Systems ◽

Optimal Tracking ◽

Control Techniques ◽

Optimal Tracking Control

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Robust sliding mode control for a class of underactuated systems with mismatched uncertainties

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1243/09596518jsce734 ◽

2009 ◽

Vol 223 (6) ◽

pp. 785-795 ◽

Cited By ~ 16

Author(s):

D W Qian ◽

X J Liu ◽

J Q Yi

Keyword(s):

Robust Control ◽

Sliding Mode Control ◽

Control Method ◽

Sliding Mode ◽

Underactuated Systems ◽

Sliding Surface ◽

Nominal System ◽

Sliding Surfaces ◽

Mode Control ◽

Mismatched Uncertainties

Based on the sliding mode control methodology, this paper presents a robust control strategy for underactuated systems with mismatched uncertainties. The system consists of a nominal system and the mismatched uncertainties. Since the nominal system can be considered to be made up of several subsystems, a hierarchical structure for the sliding surfaces is designed. This is achieved by taking the sliding surface of one of the subsystems as the first-layer sliding surface and using this sliding surface and the sliding surface of another subsystem to construct the second-layer sliding surface. This process continues till the sliding surfaces of all the subsystems are included. A lumped sliding mode compensator is designed at the last-layer sliding surface. The asymptotic stability of all of the layer sliding surfaces and the sliding surface of each subsystem is proven. Simulation results show the validity of this robust control method through stabilization control of a system consisting of two inverted pendulums and mismatched uncertainties.

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Motion Planning of a Nonholonomic Multibody System Using Genetic Algorithm

Design Engineering, Volumes 1 and 2 ◽

10.1115/imece2003-42674 ◽

2003 ◽

Cited By ~ 1

Author(s):

Xin-Sheng Ge ◽

Li-Qun Chen

Keyword(s):

Genetic Algorithm ◽

Motion Planning ◽

Nonholonomic System ◽

Multibody System ◽

Planning Problem ◽

Control Approach ◽

Velocity Constraints ◽

Nonholonomic Motion Planning ◽

Optimal Control Approach ◽

Motion Planning Problem

The motion planning problem of a nonholonomic multibody system is investigated. Nonholonomicity arises in many mechanical systems subject to nonintegrable velocity constraints or nonintegrable conservation laws. When the total angular momentum is zero, the control problem of system can be converted to the motion planning problem for a driftless control system. In this paper, we propose an optimal control approach for nonholonomic motion planning. The genetic algorithm is used to optimize the performance of motion planning to connect the initial and final configurations and to generate a feasible trajectory for a nonholonomic system. The feasible trajectory and its control inputs are searched through a genetic algorithm. The effectiveness of the genetic algorithm is demonstrated by numerical simulation.

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