Jés Jesus Fiais Cerqueira

Dynamic Modeling with Nonlinear Inputs and Backstepping Control for a Hexarotor Micro-Aerial Vehicle

In this paper the hexarotor dynamic model with nonlinear inputs and full state back stepping technique is presented. Dead zone and saturation nonlinear inputs are considered reflected to the rotors. The goal is to obtain a faithful mathematical representation of the mechanical system for analysis and control design, not only in hover, but also in motion when take-off, land and flight for aerial navigation tasks. The model was implemented in Matlab/Simulink to optimize the design of control system. Simulations of the hexarotor model shows the performance of the control law and stabilizes with good tracking.

Generation of Trajectories Using Predictive Control for Tracking Consensus with Sensing

Abstract This work presents a cooperation strategy for teams of multiple vehicles to solve the rendezvous problem. The approach is based on consensus algorithms, which are basically characterized by information exchange among the team members. The proposal is based on predictive control, in order to compute decentralized control laws, considering constraints and different response requirements. Our work allows considering together vehicles without and with non-holonomic restrictions while optimizing the sensing range, particularly that of fixed frontal cameras, by managing orientation in the way to the rendezvous point. We show the effectiveness of our strategy with simulation results.

Generation of Trajectories Using Predictive Control for Tracking Consensus with Sensing and Connectivity Constraint

This work presents a cooperation strategy for teams of multiple autonomous vehicles to solve the rendezvous problem. The approach is based on consensus algorithms, which are basically characterized by information exchange among the team members. The proposal is based on predictive control in order to compute decentralized control laws, considering constraints and different response requirements according to the application scenario, for example, constraints related to coverage and connectivity of the group. Our work allows considering together vehicles without and with non-holonomic restrictions while optimizing the sensing range, particularly that of fixed frontal cameras, by managing orientation in the way to the rendezvous point. We show the effectiveness of our strategy with simulation results.

Stereotyped gesture recognition: An analysis between HMM and SVM

Stereotypic behaviours are present in both human and nonhuman primates. Usually, these behaviours are a welfare indicator. However, the stereotypic behaviours may be also a symptom of some mental disorder in the humans. A specific case is Autism Spectrum Disorder (ASD). The individuals with ASD may exhibit stereotypic behaviours through some gestures. The classic stereotyped gestures of autism are: (i) Body Rocking; (ii) Hand Flapping; and (iii) Top Spinning. This paper study the performance between two machine learning algorithms to recognition the stereotyped gestures typical of autism: (i) Hidden Markov Model [HMM]; and (ii) Support Vector Machine [SVM]. Sequence of orientations data from some joints obtained through a RGB-D (Red Green Blue - Depth) camera [Kinect®] are used for analysis. The results of these two machine learning algorithms are compared with state-of-the-art. The HMM approach proposed in this paper have shown 98.89% average recognition rate and 98.9% recall. This value is higher compared to the SVM approach and the others of art method presented.

The Berimbot: A Robotic Musical Instrument as an Outreach Tool for the Popularization of Science and Technology

The purpose of this article is to describe an outreach program based on the engineering design of a robotic musical instrument aimed to the segment of the population not served by traditional academic initiatives or outreach programs. It aims to contribute to develop the interest among children and youngsters in pursuing scientific and technology careers and also mitigating science illiteracy among the general public. The program consists in a keynote showing the various phases undertaken, people involved and the knowledge and skills needed to build the robotic musical instrument. The concepts of teamwork, consulting and multidisciplinarity are also examined. The presentation includes a musical performance.

Electric Power System Operation: A Petri Net Approach for Modeling and Control

In this paper the operation of electric power system is treated as a discrete event system and a Petri Net is used as formal tool to achieve it. Each component of power system is modelled as a single Petri Net and the complete model is reached by composition of these single Petri Nets. Properties such as: parallelism, conflict, concurrency and others are used to study the operation of the modelled system. In this study are detected undesired behaviors on the dynamics of system. The theory of supervisory control is used to avoid these undesired behaviors forcing the system to have a controlled behavior. To obtain a controlled system a set of constraint are modelled by linear inequalities and the systems is forced to obey it. A case study application is presented to illustrate the proposed model here.

Trajectory Control of Wheeled Mobile Robots Not Satisfying Ideal Velocity Constraints by Using Slipping and Skidding Variations: A Singular Perturbation Approach

Control of wheeled mobile robots (WMRs) on trajectory tracking problems has given rise to an abundant proposals at recent years. Normally, WMRs are subject to phenomena like sliding, deformability or flexibility, which are strongly associated with violation of velocity constraints. Here, we propose a method to reduce the effects of slipping and skidding in WMRs by using an auxiliary control law whose robustness is based on slipping and skidding variations. It is considered the control law based on state-feedback linearization whose robustness with respect to the deformability of wheel will be based on singular perturbation methods. The tracking problem is studied by using the auxiliary control law proposed in a feedforward loop. The results show that the law proposed is robust to slipping and skidding and that tracking error converges toward zero.

Correspondence: Comments on intelligent optimal control of robotic manipulator using neural networks

This note points out that the proof of Theorem 3 in Kim, Lewis, and Dawson (Automatica 36(9) 1355) has a mistake. Additionally, it is presented as the correction of the theorem.