The dc motor is one of the most fundamental electromechanical devices of mechatronic systems, which plays an important role in maintaining the accuracy in the execution of tasks. One of the main issues in the accuracy and robustness of dc motor control system is how to optimally tune its parameters. In this paper, a multi-objective online tuning optimization approach is proposed to adaptively tune up the velocity control parameters of the permanent magnet dc motor. This approach simultaneously considers the modeled error and the corresponding sensitivity to choose the best compromise solution in the Pareto dominance-based selection process of solutions to deal the changing optimum solutions in the dynamic environment of the tuning approach based on online optimization method and moreover, the modified differential evolution with induced initial population based on non-dominated solution through a memory is proposed to guide the search into the feasible region, and to promote the exploitation of solutions found in the previous time interval. Simulation results verify that proposed modifications provide higher robustness and better quality in the velocity regulation control of the dc motor under parametric uncertainties, and also under discontinuous dynamic load, than multi-objective differential evolution, particle swarm optimization, and non-dominated sorting genetic algorithm-II.

Deaths due to heart diseases are a leading cause of death in Mexico. Cardiovascular diseases are considered a public health problem because they produce cardiorespiratory arrests. During an arrest, cardiac and/or respiratory activity stops. A cardiorespiratory arrest is rapidly fatal without a quick and efficient intervention. As a response to this problem, the Virtual${}^{CPR}$ system was designed in the present work. Virtual${}^{CPR}$ is a mobile virtual reality application to support learning and practicing of basic techniques of cardiopulmonary resuscitation (CPR) for experts or non-experts in CPR. Virtual${}^{CPR}$ implements an interactive virtual scenario with the user, which is visible by means of employment of virtual reality lenses. User’s interactions, with our proposal, are by a portable force sensor for integration with training mannequins, whose development is based on an application for the Android platform. Furthermore, this proposal integrates medical knowledge in first aid, related to the basic CPR for adults using only the hands, as well as technological knowledge, related to development of simulations on a mobile virtual reality platform by three main processes: (i) force measurement and conversion, (ii) data transmission and (iii) simulation of a virtual scenario. An experiment by means of a multifactorial analysis of variance was designed considering four factors for a CPR session: (i) previous training in CPR, (ii) frequency of compressions, (iii) presence of auditory suggestions and (iv) presence of color indicator. Our findings point out that the more previous training in CPR a user of the Virtual${}^{CPR}$ system has, the greater the percentage of correct compressions obtained from a virtual CPR session. Setting the rate to 100 or 150 compressions per minute, turning on or off the auditory suggestions and turning the color indicator on or off during the session have no significant effect on the results obtained by the user.

We introduce a new kind of aerial manipulator based on multirotors. This device exploits the rarely used yaw movement which characterizes these aircrafts in order to generate and transmit forces and displacements trough a serial-chain of rigid links and other drones, as if the whole system was a flying robot arm with UAVS as rotational joints. Also we provide comparisons with the existing technologies and a condensed review concerning them. Finally, this paper proposes many open problems in order to develop the final system. Due to the scientific and social impact of this new approach, we provide some application examples.

In this work, a new version of the Harmony Search algorithm for solving multi-objective optimization problems is proposed, MOHSg, with pitch adjustment using genotype. The main contribution consists of adjusting the pitch using the crowding distance by genotype; that is, the distancing in the search space. This adjustment automatically regulates the exploration–exploitation balance of the algorithm, based on the distribution of the harmonies in the search space during the formation of Pareto fronts. Therefore, MOHSg only requires the presetting of the harmony memory accepting rate and pitch adjustment rate for its operation, avoiding the use of a static bandwidth or dynamic parameters. MOHSg was tested through the execution of diverse test functions, and it was able to produce results similar or better than those generated by algorithms that constitute search variants of harmonies, representative of the state-of-the-art in multi-objective optimization with HS.

With the help of platforms with haptic devices, rehabilitation areas for cerebrovascular accident patients can be attended with practices such as upper and lower extremity training. The application of training and/or rehabilitation protocols generates in disabled people the capacity for motor learning (movements executed quickly and accurately through practice). In this research article, we present the integration of a rehabilitation platform for upper limb, which is used by a pilot sample of users, who perform the evaluation of the user’s workload during human-robot interaction using the NASA-TLX protocol, which is based on the assessment of load and mental fatigue. To generate the rehabilitation tasks from trajectory planning in the workspace of the haptic device and guarantee position convergence, a wavenet control (Multiresolution PID control based on wavelet transform and second generation neural networks as identification scheme) was implemented. The proposed adaptive control is evaluated on a 6-degree-of-freedom haptic device with high technological performance (Cyberforce) designed to position an exoskeleton CyberGrasp with the human operator in the loop.