Free chattering sliding mode control with adaptive algorithm for ground moving target tracking

2014 ◽  
Author(s):  
Alireza Modirrousta ◽  
Mohsen Sohrab ◽  
Seyed Mohammad Mehdi Dehghan
Keyword(s):  
Sliding Mode Control ◽  
Target Tracking ◽  
Adaptive Algorithm ◽  
Sliding Mode ◽  
Moving Target ◽  
Moving Target Tracking ◽  
Mode Control

A Target Tracking Approach for Nonholonomic Agents Based on Artificial Potentials and Sliding Mode Control

2012 ◽  
Vol 134 (6) ◽  
Author(s):  
Veysel Gazi ◽  
Barış Fidan ◽  
Raúl Ordóñez ◽  
M. İlter Köksal
Keyword(s):  
Sliding Mode Control ◽  
Target Tracking ◽  
Continuous Time ◽  
Sliding Mode ◽  
Control Techniques ◽  
Maneuvering Target ◽  
Mode Control ◽  
Time Control ◽  
Control Scheme ◽  
Simulation Results

In this paper, we consider the task of tracking a maneuvering target both with a single nonholonomic agent and a swarm of nonholonomic agents. In order to achieve the tracking task, a decentralized continuous-time control scheme, which combines artificial potentials and sliding mode control techniques, is developed via constructive analysis. The effectiveness of the proposed control scheme is established analytically and demonstrated via a set of simulation results.

Response Variance Reduction of a Nonlinear Mechanical System via Sliding Mode Control

1998 ◽  
Vol 120 (3) ◽  
pp. 801-805 ◽  
Author(s):  
J. Q. Sun ◽  
Qing Xu
Keyword(s):  
Sliding Mode Control ◽  
Target Tracking ◽  
Mechanical System ◽  
Variance Reduction ◽  
Sliding Mode ◽  
The State ◽  
State Variables ◽  
Mode Control ◽  
Response Variance ◽  
Special Cases

An analysis of a target tracking mechanical system subject to random base excitations is presented in this paper. Sliding mode controls are proposed to minimize the random error of target tracking. Two special cases are studied. In the first case, it is assumed that all the system parameters are known and the state variables are measurable. A sliding mode control is then determined. This highly idealized example reveals the effect of sliding mode control parameters on the reduction of response variance and provides a benchmark for designing a robust controller that deals with systems with unknown parameters. The second case deals with a robust sliding mode control where some parameters of the system are assumed to fall in a known range of values. The proposed controls are proven stable in the mean square sense. The statistical aspects of the controlled system are studied by considering the first and second order moments of the state variables. The equations for these moments are derived and solved by using the method of Gaussian closure in order to investigate the variance reduction performance of the controls.

Robust Region-Tracking for Multi-Agent Systems Using Sliding Mode Control

2010 ◽  
Author(s):  
Mark Bacon ◽  
Nejat Olgac
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Autonomous Agent ◽  
Moving Target ◽  
Multi Agent Systems ◽  
Target Region ◽  
Agent Systems ◽  
Mode Control ◽  
Modeling Uncertainties ◽  
Multi Agent

Control of autonomous agent swarms is studied for targeted flocking exercises. The desired decentralized control also requires robustness against modeling uncertainties and bounded unknown forces. In this analysis, we consider the task of robustly driving multiple agents to a moving ‘target region’, as repulsive interactions help spread out the agents. An unconventional form of sliding mode control is implemented to provide the robust attraction towards the region’s center. For robustness a ‘boundary layer’ is conceived, which corresponds to the desired target region. The attraction is intentionally softened inside this target region, allowing agents to create a final formation utilizing their repulsion forces. Examples are given for moving circular and elliptical regions which illustrate the effectiveness of the proposed strategy.

Swarm Tracking Using Artificial Potentials and Sliding Mode Control

2007 ◽  
Vol 129 (5) ◽  
pp. 749-754 ◽  
Author(s):  
Jingyi Yao ◽  
Raúl Ordóñez ◽  
Veysel Gazi
Keyword(s):  
Sliding Mode Control ◽  
Vehicle Dynamics ◽  
Sliding Mode ◽  
Kinematic Model ◽  
Control Technique ◽  
Moving Target ◽  
Mode Control ◽  
Coordination Framework ◽  
Specific Potential ◽  
Simulation Results

In this paper, we present a stable and decentralized control strategy for multiagent systems (swarms) to capture a moving target in a specific formation. The coordination framework uses artificial potentials to take care of both tracking and formation tasks. First, a basic controller is designed based on a kinematic model. After that, sliding mode control technique is used to force the agents with general vehicle dynamics to obey the required motion. Finally, specific potential functions are discussed and corresponding simulation results are given.

Composite learning adaptive sliding mode control for AUV target tracking

2019 ◽  
Vol 351 ◽  
pp. 180-186 ◽  
Author(s):  
Yuyan Guo ◽  
Hongde Qin ◽  
Bin Xu ◽  
Yi Han ◽  
Quan-Yong Fan ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Target Tracking ◽  
Sliding Mode ◽  
Adaptive Sliding Mode Control ◽  
Adaptive Sliding Mode ◽  
Mode Control
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