Minimum Energy Control of Quadrotor UAV: Synthesis and Performance Analysis of Control System with Neurobiologically Inspired Intelligent Controller (BELBIC)

Giernacki, Wojciech

doi:10.3390/en15207566

Cited by 8 publications

(11 citation statements)

References 56 publications

(66 reference statements)

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“…An approach to modeling the full translational dynamics of a quadrotor UAV by a feedforward neural network was proposed by [32], which was adopted as the prediction model in a model predictive controller (MPC) for precise position control. Finally, the aim of [33] was to shed light on the problem of shaping control signals in terms of energy-optimal flights. The synthesis of a UAV autonomous control system with a brain-emotional-learning-based intelligent controller (BELBIC) is presented.…”

Section: Relevant and Related Workmentioning

confidence: 99%

Quadrotor Trajectory Control Based on Energy-Optimal Reference Generator

Bianchi,

Borri,

Cappuzzo

et al. 2024

Drones

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Inspired by the limited battery life of multi-rotor unmanned aerial vehicles (UAVs), this research investigated hierarchical real-time control of UAVs with the generation of energy-optimal reference trajectories. The goal was to design a reference generator and controller based on optimal-control theory that would guarantee energy consumption close to optimal with lower computational cost. First, a least-squares-estimation-(LSE) algorithm identified the parameters of the UAV mathematical model. Then, by considering a precise electrical model for the brushless DC motors and rest-to-rest maneuvers, the extraction of clear rules to compute the optimal mission time and generate ’energetic trajectories’ was performed. These rules emerged from analyzing the optimal-control strategy results that minimized the consumption over many simulations. Afterward, a hierarchical controller tracked those desired energetic trajectories identified as sub-optimal. Numerical experiments compared the results regarding trajectory tracking, energy performance index, and battery state of charge (SOC). A co-simulation framework consisting of commercial software tools, Simcenter Amesim for the physical modeling of the UAV, and Matlab-Simulink executed numerical simulations of the implemented controller.

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Section: Relevant and Related Workmentioning

confidence: 99%

Quadrotor Trajectory Control Based on Energy-Optimal Reference Generator

Bianchi,

Borri,

Cappuzzo

et al. 2024

Drones

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“…The issues of drive sources of UAVs are presented in a number of articles [96][97][98][99][100][101][102][103][104]. Due to the environment's need to overcome the force of gravity, these robots have special power requirements [105][106][107][108][109][110][111].…”

Section: Limitations Of Previous Studiesmentioning

confidence: 99%

Energy Sources of Mobile Robot Power Systems: A Systematic Review and Comparison of Efficiency

et al. 2023

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Mobile robots can perform tasks on the move, including exploring terrain, discovering landmark features, or moving a load from one place to another. This group of robots is characterized by a certain level of intelligence, allowing the making of decisions and responding to stimuli received from the environment. As part of Industry 5.0, such mobile robots and humans are expected to co-exist and work together in a shared environment to make human work less tiring, quicker, and safer. This can only be realized when clean, dense, and economical energy sources are available. The aim of the study is to analyze the state of the art and to identify the most important directions for future developments in energy sources of robotic power systems based mainly on batteries. The efficiency and performance of the battery depends on the design using different materials. Work environments and performance requirements are considered in this systematic review to classify solutions that help developers choose the best-suited power system for specific application. Indirectly, the aim of the work is to generate discussion within the scientific and engineering community. A narrative review of publications from six major bibliographic databases according to preset inclusion criteria is combined with a critical analysis of current and future technologies. The main findings of the review allow answering the question of what is the role of modern power source technologies, artificial intelligence, and ground-breaking research work in global policies related to energy saving, green policies, and sustainable development. The main opportunities and threats are discussed, and a brief feasibility analysis is carried out. The novelty of the article relates not only to the analysis of technologies, but also to approaches and their use under conditions of limited resource availability, when resource usage must be minimized. The article provides an overview of batteries, their specifications, classifications, and their advantages and disadvantages. In addition, we propose (1) an algorithm for selecting the main energy source for robot application, and (2) an algorithm for selecting an electrical system power supply. Current mobile robot batteries are, in most cases, the robot’s biggest limitation. Progress in battery development is currently too slow to catch up with the demand for robot autonomy and range requirements, limiting the development of mobile robots. Further intensive research and implementation work is needed to avoid years of delay in this area.

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“…There are also mobile robots that also move in other environments in the air -UAVs (Unmanned Aerial Vehicles) or in the water environment AUV Autonomous Underwater Vehicles). The issues of drive sources of UAV are presented in a number of articles [96][97][98][99][100][101][102][103][104]. Due to the environment's need to overcome the force of gravity, these robots have special power requirements.…”

Section: Limitatons Of Previous Studiesmentioning

confidence: 99%

Materials for Batteries of Mobile Robot Power Systems: A Systematic Review and Comparison of Efficiency

Mikołajczyk¹,

Mikołajewski²,

Kłodowski³

et al. 2023

Preprint

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Mobile robots can perform tasks on the move, including exploring terrain, discovering landmark features or moving a load from one place to another. This group of robots is characterized by a certain level of intelligence allowing making decisions and responding to stimuli received from the environment. As part of Industry 5.0, such mobile robots and humans are expected to co-exist and work together in a shared environment to make human work less tiring, quicker, and safer. This can only be realized when clean, dense, and economical energy sources are available. The aim of the study is to analyze the state of the art and to identify the most important directions for future developments in robotic power systems based mainly on batteries. The efficiency and performance of the battery depends on the design using different materials. Work environments and performance requirements are considered in this systematic review to classify solutions that help developers choose the best suited power system for specific application. Indirectly, the aim of the work is to generate discussion within the scientific and engineering community. A narrative review of publications from six major bibliographic databases according to preset inclusion criteria was combined with a critical analysis of current and future technologies. The main findings of the review allow answering question what is the role of modern power source technologies, artificial intelligence and ground-breaking research work in global policies related to energy saving, green policies, and sustainable development. The main opportunities and threats are discussed, and a brief feasibility analysis is carried out. Novelty of the article relates not only to the analysis of technologies, but also to approaches and their use under conditions of limited resource availability, when resource usage must be minimized. The article provides an overview of batteries, their specifications, classifications, and their advantages and disadvantages. In addition, we propose: (1) an algorithm for selecting main energy source for robot application, and (2) an algorithm for selecting electrical system power supply. Current mobile robot batteries are, in most cases, their biggest limitation. Progress in batteries development is too slow to catch up with the demand for robot autonomy and range requirements, limiting the development of mobile robots. Further intensive research and implementation work is needed to avoid years of delay in this area.

show abstract

Minimum Energy Control of Quadrotor UAV: Synthesis and Performance Analysis of Control System with Neurobiologically Inspired Intelligent Controller (BELBIC)

Cited by 8 publications

References 56 publications

Quadrotor Trajectory Control Based on Energy-Optimal Reference Generator

Quadrotor Trajectory Control Based on Energy-Optimal Reference Generator

Energy Sources of Mobile Robot Power Systems: A Systematic Review and Comparison of Efficiency

Materials for Batteries of Mobile Robot Power Systems: A Systematic Review and Comparison of Efficiency

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