scholarly journals A Range-Based Algorithm for Autonomous Navigation of an Aerial Drone to Approach and Follow a Herd of Cattle

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7218
Author(s):  
Manaram Gnanasekera ◽  
Jay Katupitiya ◽  
Andrey V. Savkin ◽  
A.H.T. Eranga De De Silva
Keyword(s):  
Sliding Mode Control ◽  
Mathematical Analysis ◽  
Autonomous Navigation ◽  
Sliding Mode ◽  
Rate Of Change ◽  
Measurement Noise ◽  
Experimental Results ◽  
Primary Motivation ◽  
Range Measurements ◽  
Robust Sensing

This paper proposes an algorithm that will allow an autonomous aerial drone to approach and follow a steady or moving herd of cattle using only range measurements. The algorithm is also insensitive to the complexity of the herd’s movement and the measurement noise. Once arrived at the herd of cattle, the aerial drone can follow it to a desired destination. The primary motivation for the development of this algorithm is to use simple, inexpensive and robust sensing hence range sensors. The algorithm does not depend on the accuracy of the range measurements, rather the rate of change of range measurements. The proposed method is based on sliding mode control which provides robustness. A mathematical analysis, simulations and experimental results with a real aerial drone are presented to demonstrate the effectiveness of the proposed method.

scholarly journals Reaching Law Based Sliding Mode Control of Sampled Time Systems

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1882
Author(s):  
Piotr Leśniewski ◽  
Andrzej Bartoszewicz
Keyword(s):  
Sliding Mode Control ◽  
Discrete Time ◽  
Sliding Mode ◽  
Rate Of Change ◽  
Reaching Law ◽  
Mode Control ◽  
Sliding Motion ◽  
Control Precision ◽  
Continuous Time Systems ◽  
Time Systems

In this paper, discrete time reaching law-based sliding mode control of continuous time systems is considered. In sliding mode control methods, usually the assumption of bounded absolute values of disturbances is used. However in many cases, the rate of change of the disturbance is also bounded. In the presented approach, this knowledge is used to improve the control precision and reduce the undesirable chattering. Another advantage of the proposed method is that the disturbance does not have to satisfy the matching conditions. In the paper two new reaching laws are analyzed, one of them ensures the switching quasi-sliding motion and the other the non-switching motion. For both of them, the robustness is assessed by calculating the quasi-sliding mode band width, as well as the greatest possible state error values. Specifically, the state errors are not considered only at the sampling instants, as is usual for discrete time systems, but the bounds on the continuous values “between” the sampling instants are also derived. Then, the proposed approaches are compared and analyzed with respect to energy expenditure of the control signal.

Sliding Mode Control for Wheeled Inverted Pendulum

2014 ◽  
Vol 971-973 ◽  
pp. 714-717 ◽  
Author(s):  
Xiang Shi ◽  
Zhe Xu ◽  
Qing Yi He ◽  
Ka Tian
Keyword(s):  
Control System ◽  
Sliding Mode Control ◽  
High Performance ◽  
Inverted Pendulum ◽  
Sliding Mode ◽  
Experimental Results ◽  
Control Law ◽  
Collaborative Simulation ◽  
Mode Control ◽  
Wheeled Inverted Pendulum

To control wheeled inverted pendulum is a good way to test all kinds of theories of control. The control law is designed, and it based on the collaborative simulation of MATLAB and ADAMS is used to control wheeled inverted pendulum. Then, with own design of hardware and software of control system, sliding mode control is used to wheeled inverted pendulum, and the experimental results of it indicate short adjusting time, the small overshoot and high performance.

scholarly journals A Composite Guidance Law for Suppressing Measurement Noise of LOS Angular Rate

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Feng Chen ◽  
Guangjun He ◽  
Qifang He
Keyword(s):  
Sliding Mode Control ◽  
Finite Time ◽  
Disturbance Observer ◽  
Sliding Mode ◽  
Angular Rate ◽  
Measurement Noise ◽  
Terminal Sliding Mode ◽  
Guidance Law ◽  
Fast Terminal Sliding Mode ◽  
Low Altitude

To effectively intercept a low-altitude target in clutter background, a nonsingular fast terminal sliding mode guidance law is designed. The designed guidance law can fully exploit the fast convergence characteristics of linear sliding mode control and the finite-time-convergent characteristics of terminal sliding mode control to ensure that the line-of-sight (LOS) angle converges to a desired angle in a limited time at a faster rate. Utilizing the smooth switching characteristics of the hyperbolic tangent function similar to the saturation function, a finite-time-convergent differentiator is designed. Meanwhile, a new finite-time-convergent disturbance observer designed on the tracking differentiator can effectively track the ideal LOS angular rate, suppress the measurement noise, and make a smooth estimation of the target maneuvering acceleration in clutter background. Combining the estimated value of the disturbance observer, the sign function with switch coefficient is introduced to design a composite nonsingular fast terminal sliding mode guidance law. The simulation results show that the composite guidance law can not only effectively suppress the measurement noise of the LOS angular rate and improve the accuracy of low-altitude target intercepting, but also greatly reduce the energy consumption in the interception process.

scholarly journals Quasi-Sliding Networked Control of Systems Subject to Unbounded Disturbance with Limited Rate of Change

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Andrzej Bartoszewicz ◽  
Paweł Latosiński
Keyword(s):  
Sliding Mode Control ◽  
Control Strategy ◽  
Sliding Mode ◽  
Rate Of Change ◽  
Networked Control ◽  
Sliding Mode Controller ◽  
System State ◽  
The Past ◽  
State Measurement ◽  
Measurement Delay

This paper concerns network based sliding mode control of linear plants with state measurement delay. The considered plants are subject to unbounded disturbance, but it is assumed that the change of disturbance value between each two subsequent sampling instants is limited. In order to combat the unpredictable disturbance in the environment with state measurement delay, a novel sliding mode controller has been introduced. It utilizes two nominal models of the plant to drive the system state along a desired trajectory and counteract the predicted effect of the past disturbance on the system. It has been proven that applying the new control strategy to the plant confines the system state to a defined band around the sliding hyperplane.

scholarly journals Sliding Mode Control of Magnetic Bearings: Comparison of Sensed and Self Sensing Performance

1999 ◽  
Author(s):  
S. Ueno ◽  
J. H. Lee ◽  
P. E. Allaire ◽  
Y. Okada
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Angular Displacement ◽  
State Space Model ◽  
Experimental Results ◽  
Magnetic Bearings ◽  
Small Scale ◽  
Linear Component ◽  
Mode Control ◽  
Physical Sensors

A sliding mode control algorithm has been designed for control of a balance beam on two symmetric magnetic bearings. A state space model of the system is developed and the controller is separated into a linear and non-linear component. A reaching condition to bring the system to the sliding surface is developed and a continuous function boundary layer approach is evaluated to avoid chattering. Previous works have discussed theoretical and experimental sliding mode control with physical sensors. This paper represents the first use of a simple envelope filter for sliding mode self sensing. The system simulation demonstrates arrival at the hyperplane surface within 0.003 sec and converges to the zero angular displacement value within 0.008 sec. Experimental results produced system convergence to zero angular displacement within approximately 0.35 sec both for the case when an eddy current position sensor was used and the case when system self sensing was employed. Some small scale chatter was observed in the experimental results with a peak to peak magnitude of approximately 3 times larger in the self-sensing case as compared to the case with a physical sensor.

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