UAVs-UGV Leader Follower Formation Using Adaptive Non-Singular Terminal Super Twisting Sliding Mode Control

Ullah, Nasim; Mehmood, Yasir; Aslam, Jawad; Ali, Amjad; Iqbal, Jamshed

doi:10.1109/access.2021.3081483

Cited by 10 publications

(7 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Same applies to the control methodologies used across UAV platforms. The interested reader may refer to [ 24 – 28 ] for an insight into UAV control methodologies.…”

Section: Uav Firefightingmentioning

confidence: 99%

Efficient optimization techniques for resource allocation in UAVs mission framework

et al. 2023

Self Cite

View full text Add to dashboard Cite

This paper considers the generic problem of a central authority selecting an appropriate subset of operators in order to perform a process (i.e. mission or task) in an optimized manner. The subset is selected from a given and usually large set of ‘n’ candidate operators, with each operator having a certain resource availability and capability. This general mission performance optimization problem is considered in terms of Unmanned Aerial Vehicles (UAVs) acting as firefighting operators in a fire extinguishing mission and from a deterministic and a stochastic algorithmic point of view. Thus the applicability and performance of certain computationally efficient stochastic multistage optimization schemes is examined and compared to that produced by corresponding deterministic schemes. The simulation results show acceptable accuracy as well as useful computational efficiency of the proposed schemes when applied to the time critical resource allocation optimization problem. Distinguishing features of this work include development of a comprehensive UAV firefighting mission framework, development of deterministic as well as stochastic resource allocation optimization techniques for the mission and development of time-efficient search schemes. The work presented here is also useful for other UAV applications such as health care, surveillance and security operations as well as for other areas involving resource allocation such as wireless communications and smart grid.

show abstract

“…Same applies to the control methodologies used across UAV platforms. The interested reader may refer to [ 24 – 28 ] for an insight into UAV control methodologies.…”

Section: Uav Firefightingmentioning

confidence: 99%

Efficient optimization techniques for resource allocation in UAVs mission framework

et al. 2023

Self Cite

View full text Add to dashboard Cite

show abstract

“…for any τ ≥ 0, where the positive parameter µ max denotes upper and lower control signal limitation. Substituting control signal (5) to the above inequality one gets…”

Section: A Control Signal Limitationmentioning

confidence: 99%

“…This makes it hard to evaluate, how the solution would perform in the real world. In [5] an adaptive non-singular terminal supertwisting sliding mode controller was used for the related problem of UAV formation control. Formations of UAVs can be useful for e.g.…”

Section: Introductionmentioning

confidence: 99%

“…The main difference is that in [6] it is assumed that not all UAVs have direct communication with the leader, and the formation must be held using only local distance information. Moreover, [6] utilizes a collision avoidance mechanism based on artificial potential field, which was not considered in [5]. The performance of the proposed approach is validated both in theory and in computer simulations.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

IAE Minimization in Sliding Mode Control With Input and Velocity Constraints

Pietrala¹,

Leśniewski²,

Bartoszewicz³

2022

IEEE Access

View full text Add to dashboard Cite

In this work an optimal sliding mode controller for second order, nonlinear systems is proposed. First, the sliding surface is selected to obtain finite time convergence to the desired state. Moreover, to ensure robustness with respect to unknown external disturbances and model uncertainties, the surface is time-varying and at the start of the control process it intersects the point, whose coordinates are defined by the initial state. Thus, the existence of the sliding mode is ensured for the whole control process. Next, admissible values of the hyperplane parameters, that ensure satisfaction of velocity and/or control signal constraints are determined. Lastly, optimal values of these parameters, in terms of integral absolute error (IAE) are calculated. The main motivation of this paper was to obtain the good dynamical performance of the system and robustness by eliminating the reaching phase, overcoming the external, unknown disturbances and obtaining a finite-time convergence of the representative point to the desired state. The other main issue was to include some key limitations such as control signal and velocity constraints in order to facilitate the practical application of this strategy.

show abstract

“…However, they are mathematically complex and computationally time consuming [ 27 , 28 , 29 ]. Recently, the improved sliding mode reaching law (ISMRL) has provided a terminable system state convergence time to reject the steady-state error (i.e., the terminable time for the system trajectory to reach the sliding mode region in the presence of uncertainty) [ 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. However, it should be noted that even if ISMRL makes the solar power generation system achieve the expected control effect, it is easy for the solar array to become partially shielded by buildings, trees, dust, etc.…”

Section: Introductionmentioning

confidence: 99%

Study and Implementation of a High-Quality True Sine Wave DC-to-AC Inverter for Solar Power Generation Systems

Chang

et al. 2022

Micromachines

View full text Add to dashboard Cite

True sine wave DC-to-AC inverters are becoming more and more important in solar power generation in order to raise the system’s efficiency. A high-quality true sine wave DC-to-AC inverter can be built with a robust intelligent control method. This robust intelligent control method is comprised of improved sliding mode reaching law (ISMRL) and particle swarm optimization (PSO)—catfish effect (CE). The sliding mode reaching law is robust and insensitive to parameter variations and external disturbances. However, it has infinite system-state convergence times and steady-state errors. In addition, solar panels are often affected by partial shading, causing the output power–voltage characteristic curve to be multi-peaked. Such a situation causes misjudgment of the maximum power point tracking with conventional algorithms, which can neither obtain the global extremes nor establish high conversion efficiency. Therefore, this paper proposes an ISMRL based on PSO-CE applied to the tracking of maximum power in the case of partial shading of a solar power generation system. The ISMRL guarantees quick terminable time convergence, making it well-suited for digital implementation. In this paper, PSO-CE is used to find the global best solution of ISMRL, rejecting steady-state errors, slow convergence, and premature trapping in local optimums. Simulation and experimental results are verified using digital implementation based on a Texas Instruments digital signal processor to produce more accurate and better tracking control of true sine wave DC-to-AC inverter-based solar power generation systems.

show abstract

UAVs-UGV Leader Follower Formation Using Adaptive Non-Singular Terminal Super Twisting Sliding Mode Control

Cited by 10 publications

References 48 publications

Efficient optimization techniques for resource allocation in UAVs mission framework

Efficient optimization techniques for resource allocation in UAVs mission framework

IAE Minimization in Sliding Mode Control With Input and Velocity Constraints

Study and Implementation of a High-Quality True Sine Wave DC-to-AC Inverter for Solar Power Generation Systems

Contact Info

Product

Resources

About