Model-based event-triggered adaptive formation control for underactuated surface vehicles via the minimal learning parameter technique

2021 ◽  
pp. 095965182110402
Author(s):  
Guoqing Zhang ◽  
Wei Yu ◽  
Jiqiang Li ◽  
Weidong Zhang
Keyword(s):  
Formation Control ◽  
Lyapunov Theory ◽  
Polar Coordinate System ◽  
State Variables ◽  
Model Based ◽  
Minimal Learning Parameter ◽  
Polar Coordinate ◽  
Learning Parameter ◽  
And Control ◽  
Event Triggered

This article presents an adaptive neural formation control algorithm for underactuated surface vehicles by the model-based event-triggered method. In the algorithm, the leader–follower structure is employed to construct the formation model. Meanwhile, two new coordinate variables are introduced to avoid the possible singularity problem that exists in the polar coordinate system. Furthermore, the event-triggered mechanism is developed by constructing the adaptive model in a concise form. Related state variables and control parameters are required to be updated only at the event-triggered instants. Thus, the communication load between the controller and the actuator could be effectively reduced. Besides, for merits of the radial basis function neural network and the minimal learning parameter techniques, only two adaptive parameters are employed to compensate for the effects of the model uncertainties and the external disturbances. With the Lyapunov theory, all signals in the closed-loop system are proved to be semi-global uniformly ultimately bounded. Finally, numerical simulations are conducted to illustrate the effectiveness and feasibility of the proposed algorithm.

scholarly journals In-Flight Self-Alignment Method Aided by Geomagnetism for Moving Basement of Guided Munitions

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Shuang-biao Zhang ◽  
Xing-cheng Li ◽  
Zhong Su
Keyword(s):  
Measurement Errors ◽  
Rolling Speed ◽  
Magnetic Sensors ◽  
Alignment Method ◽  
State Variables ◽  
Model Based ◽  
Alignment Model ◽  
Spinning Projectile ◽  
Initial Attitude ◽  
And Control

Due to power-after-launch mode of guided munitions of high rolling speed, initial attitude of munitions cannot be determined accurately, and this makes it difficult for navigation and control system to work effectively and validly. An in-flight self-alignment method aided by geomagnetism that includes a fast in-flight coarse alignment method and an in-flight alignment model based on Kalman theory is proposed in this paper. Firstly a fast in-flight coarse alignment method is developed by using gyros, magnetic sensors, and trajectory angles. Then, an in-flight alignment model is derived by investigation of the measurement errors and attitude errors, which regards attitude errors as state variables and geomagnetic components in navigation frame as observed variables. Finally, fight data of a spinning projectile is used to verify the performance of the in-flight self-alignment method. The satisfying results show that (1) the precision of coarse alignment can attain below 5°; (2) the attitude errors by in-flight alignment model converge to 24′ at early of the latter half of the flight; (3) the in-flight alignment model based on Kalman theory has better adaptability, and show satisfying performance.

scholarly journals Model-Based Monitoring of Biotechnological Processes—A Review

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 908
Author(s):  
Velislava Lyubenova ◽  
Georgi Kostov ◽  
Rositsa Denkova-Kostova
Keyword(s):  
Sliding Mode ◽  
High Gain ◽  
State Variables ◽  
Applied Model ◽  
Model Based ◽  
Software Sensors ◽  
On Line ◽  
Biotechnological Processes ◽  
Sliding Mode Observers ◽  
And Control

The monitoring of the main variables and parameters of biotechnological processes is of key importance for the research and control of the processes, especially in industrial installations, where there is a limited number of measurements. For this reason, many researchers are focusing their efforts on developing appropriate algorithms (software sensors (SS)) to provide reliable information on unmeasurable variables and parameters, based on the available on-line information. In the literature, a large number of developments related to this topic that concern data-based and model-based sensors are presented. Up-to-date reviews of data-driven SS for biotechnological processes have already been presented in the scientific literature. Hybrid software sensors as a combination between the abovementioned ones are under development. This gives a reason for the article to be focused on a review of model-based software sensors for biotechnological processes. The most applied model-based methods for monitoring the kinetics and state variables of these processes are analyzed and compared. The following software sensors are considered: Kalman filters, methods based on estimators and observers of a deterministic type, probability observers, high-gain observers, sliding mode observers, adaptive observers, etc. The comparison is made in terms of their stability and number of tuning parameters. Particular attention is paid to the approach of the general dynamic model. The main characteristics of the classic variant proposed by D. Dochain are summarized. Results related to the development of this approach are analyzed. A key point is the presentation of new formalizations of kinetics and the design of new algorithms for its estimation in cases of uncertainty. The efficiency and applicability of the considered software sensors are discussed.

scholarly journals Formation Control with Event-Triggered Strategy for Multi-Agent Systems

2014 ◽  
Vol 18 (1) ◽  
pp. 71-77 ◽  
Author(s):  
Feng Zhou ◽  
◽  
Zhiwu Huang ◽  
Weirong Liu ◽  
Liran Li
Keyword(s):  
Formation Control ◽  
Control Input ◽  
Multi Agent Systems ◽  
Control Laws ◽  
Agent Systems ◽  
Event Trigger ◽  
Multi Agent ◽  
Event Based ◽  
And Control ◽  
Event Triggered

This paper considers cooperative formation control on networked multi-agent systems, in which the mobile agents have limited resources. Two event-based strategies are introduced to reduce resource utilization and control actuation in formation control. In one strategy, the event trigger function is designed to use system state, whereas in the other, it is designed to use control input. Theoretical and experimental analyses of the pros and cons of the two strategies are given. In addition, the stabilities of the two event-triggered formation control laws are discussed. The results of simulations conducted confirm the feasibility and effectiveness of the proposed methods.

Model-based programming tools for integrated monitoring, simulation, diagnosis and control

1993 ◽  
Author(s):  
Gabor Karsai ◽  
Samir Padalkar ◽  
Hubertus Franke ◽  
Janos Sztipanovits
Keyword(s):  
Integrated Monitoring ◽  
Model Based ◽  
Programming Tools ◽  
And Control

Model-based Management and Control of the Bioreactions in a Collection System

2018 ◽  
Vol 2018 (13) ◽  
pp. 2700-2708 ◽  
Author(s):  
Lisha Guo ◽  
John Walton ◽  
Sovanna Tik ◽  
Zachary Scott ◽  
Keshab Raj Sharma ◽  
...  
Keyword(s):  
Collection System ◽  
Model Based ◽  
And Control

scholarly journals Model-Based Slippage Estimation to Enhance Planetary Rover Localization with Wheel Odometry

2021 ◽  
Vol 11 (12) ◽  
pp. 5490
Author(s):  
Anna Maria Gargiulo ◽  
Ivan di Stefano ◽  
Antonio Genova
Keyword(s):  
Inertial Measurement Unit ◽  
Correction Method ◽  
Harsh Environments ◽  
Measurement Unit ◽  
Planetary Rovers ◽  
Model Based ◽  
Accurate Knowledge ◽  
And Control ◽  
Wheeled Vehicles ◽  
Rover Localization

The exploration of planetary surfaces with unmanned wheeled vehicles will require sophisticated software for guidance, navigation and control. Future missions will be designed to study harsh environments that are characterized by rough terrains and extreme conditions. An accurate knowledge of the trajectory of planetary rovers is fundamental to accomplish the scientific goals of these missions. This paper presents a method to improve rover localization through the processing of wheel odometry (WO) and inertial measurement unit (IMU) data only. By accurately defining the dynamic model of both a rover’s wheels and the terrain, we provide a model-based estimate of the wheel slippage to correct the WO measurements. Numerical simulations are carried out to better understand the evolution of the rover’s trajectory across different terrain types and to determine the benefits of the proposed WO correction method.

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