In this paper, a robust backstepping integral sliding mode control (RBISMC) technique is designed for the flight control of a quadcopter, which is an under-actuated nonlinear system. First, the mathematical model of this highly coupled and under-actuated system is described in the presence of dissipative drag forces. Second, a robust control algorithm is designed for the derived model to accurately track the desired outputs while ensuring the stability of attitude, altitude and position of the quadcopter. A step by step mathematical analysis, based on the Lyapunov stability theory, is performed that endorses the stability of both the fully-actuated and under-actuated subsystems of the aforementioned model. The comparison of proposed RBISMC control algorithm, with fraction order integral sliding mode control (FOISMC), affirms the enhanced performance in terms of faster states convergence, improved chattering free tracking and more robustness against uncertainties in the system.

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Robust Integral Sliding Mode Control Design for Stability Enhancement of Under-actuated Quadcopter

This paper provides a comprehensive review of the robotic potential that is foreseen by researchers in designing future food manufacturing plant. The present day food handling and packaging setup is limited in capacity and output due to manual processing. An optimized protocol to fetch various ingredients and shape them in a final product by passing through various stages in an automated processing plant while simultaneously ensuring high quality and hygienic environment is merely possible by using robotized processing. The review also highlights the possibilities and limitations of introducing these high technology robots in the food sector. A comparison of several robots from different classes is listed with major technical parameters. However, as predicted, a food cyber-physical production system (CPPS) visualizes a closed loop system for the desired output keeping in view various constraints and risks. Human machine interface (HMI) for these machines complies with the industrial safety standards to provide a fail safe production cycle. Various new horizons in research and development of food robots are also highlighted in the upcoming industrial paradigm.

/pdf/towards-realizing-robotic-potential-in-future-intelligent-uzco3ezksu.pdf

Towards realizing robotic potential in future intelligent food manufacturing systems

Advanced sliding mode control techniques for Inverted Pendulum: Modelling and simulation

There is a high demand for developing effective controllers to perform fast and accurate operations for either flexible link manipulators (FLMs) or rigid link manipulators (RLMs). Thus, this paper is beneficial for such vast field, and it is also advantageous and indispensable for researchers who are interested in robotics to have sufficient knowledge about various controllers of FLMs and RLMs as the controllers’ concepts are elaborated in detail. The paper concentrates in critically reviewing classical controllers, intelligent controllers, robust controllers, and hybrid controllers for both FLMs and RLMs. The advantages and disadvantages of the aforementioned control methods are summarized in this paper; it also has a detailed comparison for the controllers in terms of the design difficulty, performance, and the suitability for controlling FLMs or RLMs.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/77234C86571FA246BCFD0B8331BE37DC/S0263574720000223a.pdf/div-class-title-a-critical-review-of-control-techniques-for-flexible-and-rigid-link-manipulators-div.pdf

A Critical Review of Control Techniques for Flexible and Rigid Link Manipulators

An improved optimal integral sliding mode control for uncertain robotic manipulators with reduced tracking error, chattering, and energy consumption

Robots have become an integral part of industrial automation. Their ultimate role and contribution in this sector is essentially a function of the associated control strategy to ensure precision, r...

Optimal and Robust Control of Multi DOF Robotic Manipulator: Design and Hardware Realization

In real-time embedded systems, scheduling policy is considered one of the main factors that affect their performance. It helps to choose which task should be selected first from ready queue to run. Round Robin (RR) scheduling algorithm is widely used and its performance highly depends on a Quantum size Qt, which is a predefined amount of time assigned by CPU to every task to be executed. However, the performance degrades with respect to an average waiting time (AWT), an average Turn-Around time (ATT) and a number of Context Switches (NCS). This paper presents a new improved dynamic Round Robin scheduling algorithm to reduce the average waiting time, turn-around time and the number of context switches in order to improve the system overall performance. It also presents a comparative analysis between several existing Round Robin algorithms based on the average time for waiting and turn-around and number of context switches.

An improved dynamic Round Robin scheduling algorithm based on a variant quantum time

Automatic logo recognition is gaining importance due to the increasing number of its applications. Unlike other object recognition tasks, logo recognition is more challenging because of the limited amount of the available original data. In this paper, the transfer leaning technique was applied to a Deep Convolutional Neural Network model to guarantee logo recognition using a small computational overhead. The proposed method was based on the Densely Connected Convolutional Networks (DenseNet). The experimental results show that for the FlickrLogos-32 logo recognition dataset, our proposed method performs comparably with state-of-the-art methods while using fewer parameters.

/pdf/logo-recognition-with-the-use-of-deep-convolutional-neural-20cmzon1sg.pdf

Logo Recognition with the Use of Deep Convolutional Neural Networks

Real-time embedded systems have become widely used in many fields such as control, monitoring and aviation. They perform several tasks under strict time constraints. In such systems, deadline miss may lead to catastrophic results so that all jobs need to be scheduled appropriately to ensure that they meet their deadline times. This paper presents an efficient dynamic scheduling algorithm during run-time to schedule periodic tasks in multiprocessor environments and uniprocessor as well using a dynamic average estimation. Dynamic average estimation refers to changing in different probability distributions when a task is added or removed from them. It is not always available a value of Worst-Case Execution Time (WCET) in many real-time applications such as multimedia where data has a great variation. The proposed approach selects which task or a set of tasks must be picked up for execution. A simulation system was developed to show validation of the proposed approach.

An efficient dynamic scheduling algorithm for periodic tasks in real-time systems using dynamic average estimation

Embedded systems have become very important in our life; they pervade all fields in today's advanced technology. With the increasing importance of these systems, designers need to estimate the performance metrics such as Delay which includes processing and communication and Power consumption. This procedure is very critical and even crucial at an early stage of design and implementation. Using GPUs and parallelization schemes together shows a promising sight to enhance the delay in a system under investigation with trade-off in power consumption and code size. In this paper, we will analyze that system using Hierarchical Performance Modeling (HPM) to estimate the improvement in the delay by using GPUs and parallelization methods on different hardware architectures and software platforms. The experimental results showed an improvement in the delay each time we used more threads and maximum reduction obtained when GPU was invoked to perform all graphical tasks.

Ahmed Alsheikhy

Papers

Optimal and Robust Control of Multi DOF Robotic Manipulator: Design and Hardware Realization

An improved dynamic Round Robin scheduling algorithm based on a variant quantum time

Logo Recognition with the Use of Deep Convolutional Neural Networks

An efficient dynamic scheduling algorithm for periodic tasks in real-time systems using dynamic average estimation

Delay and power consumption estimation in embedded systems using hierarchical performance modeling