Relaxed and Hybridized Backstepping

International audienceIn the present work, we consider nonlinear control systems for which there exist structural obstacles to the design of classical continuous backstepping feedback laws. We conceive feedback laws such that the origin of the closed-loop system is not globally asymptotically stable but a suitable attractor (strictly containing the origin) is practically asymptotically stable. A design method is suggested to build a hybrid feedback law combining a backstepping controller with a locally stabilizing controller. A constructive approach is also suggested employing a differential inclusion representation of the nonlinear dynamics. The results are illustrated for a nonlinear system which, due to its structure, does not have a priori any globally stabilizing backstepping controller

Compare and contrast the reaction coordinate diagrams for chemical reactions and cytoskeletal force generators.

Reaction coordinate diagrams are used to relate the free energy changes that occur during the progress of chemical processes to the rate and equilibrium constants of the process. Here I briefly review the application of these diagrams to the thermodynamics and kinetics of the generation of force and motion by cytoskeletal motors and polymer ratchets as they mediate intracellular transport, organelle dynamics, cell locomotion, and cell division. To provide a familiar biochemical context for discussing these subcellular force generators, I first review the application of reaction coordinate diagrams to the mechanisms of simple chemical and enzyme-catalyzed reactions. My description of reaction coordinate diagrams of motors and polymer ratchets is simplified relative to the rigorous biophysical treatment found in many of the references that I use and cite, but I hope that the essay provides a valuable qualitative representation of the physical chemical parameters that underlie the generation of force and motility at molecular scales. In any case, I have found that this approach represents a useful interdisciplinary framework for understanding, researching, and teaching the basic molecular mechanisms by which motors contribute to fundamental cell biological processes

Control and Optimization of Fuel Cell Based Powertrain for Automotive Applications

Fuel cell powered electric vehicles, with fast-refueling time, high energy density, and zero CO2 emissions, are becoming a promising solution for future fossil-free transportation. However, the relatively slow dynamic response and the inability of recovering the regenerative energy make vehicles solely powered by fuel cells not an immediately attractive solution. Instead, hybrid vehicles powered by fuel cells combined with energy buffers such as batteries and supercapacitors could be of more interest. Due to the unique characteristics of each energy buffer, the vehicle performance may vary with the hybrid energy storage system configuration. This thesis performs a comprehensive study on various energy storage configurations for applications in fuel cell hybrid electric vehicles. This thesis first examines the fuel cell/supercapacitor passive hybrid configuration where the fuel cell and supercapacitor share the same DC-link voltage. The power distribution between them is inherently determined by their internal resistances. Therefore, the DC-link voltage varies and depends on the vehicle power demand. In this work, a fuel cell/supercapacitor passive hybrid powertrain is first modeled and evaluated. Simulation results show that the energy efficiency is 53%–71% during propulsion and 84%–94% during braking, respectively. Moreover, a 3 kW lab-scale fuel cell/supercapacitor passive hybrid system is designed and investigated. Experimental results show that the fuel cell takes time to respond to a load change, while the supercapacitor provides the transient power, which makes it possible to downsize the fuel cell.Since the passive configuration loses the active controllability, this thesis further considers a fully-active fuel cell/supercapacitor system to improve the controllability of the power distribution. This configuration requires a boost converter for the fuel cell and a buck-boost converter for the supercapacitor. In this work, an adaptive power split method is used to smooth the fuel cell current and prevent the supercapacitor from exceeding its lower and upper charge limits. The cut-off frequency of the low-pass filter is adaptively controlled by the spectrum area ratio. Experimental results show that the supercapacitor state-of-charge is effectively controlled within the desired range. Moreover, a load disturbance compensator is proposed and demonstrated to improve the control performance such that the DC-link voltage fluctuation caused by the load current variation is significantly reduced.This thesis also investigates the cost-effectiveness of different energy buffers hybridized with fuel cells in various trucking applications. First, a chance-constraint co-design optimization problem is formulated. Convex modeling steps are presented to show that the problem can be decomposed and solved using convex programming. Results show that the power rating of the electric machine can be dramatically reduced when the delivered power is satisfied in a probabilistic sense. Moreover, the hybridization of fuel cells with lithium-ion batteries results in the lowest cost while the vehicle using lithium-ion capacitors as the energy buffer can carry the heaviest payload. This work also develops a robust co-design optimization framework considering the uncertainties in parameters (e.g., vehicle movement) and design decision variables (e.g., scaling factors of fuel cells and batteries). Results show that these uncertainties might propagate to uncertainties in state variables (e.g., battery energy) and optimization variables (e.g., battery power), leading to a larger battery capacity and therefore a higher total cost in robust optimal solutions. In summary, this thesis performs a comprehensive study on control and optimization of fuel cell based powertrains for automotive applications. This will provide a guidance on component selection and sizing, as well as powertrain system configuration and optimization for design of fuel cell powered electric vehicles

Nonlinear Systems

Open Mathematics is a challenging notion for theoretical modeling, technical analysis, and numerical simulation in physics and mathematics, as well as in many other fields, as highly correlated nonlinear phenomena, evolving over a large range of time scales and length scales, control the underlying systems and processes in their spatiotemporal evolution. Indeed, available data, be they physical, biological, or financial, and technologically complex systems and stochastic systems, such as mechanical or electronic devices, can be managed from the same conceptual approach, both analytically and through computer simulation, using effective nonlinear dynamics methods. The aim of this Special Issue is to highlight papers that show the dynamics, control, optimization and applications of nonlinear systems. This has recently become an increasingly popular subject, with impressive growth concerning applications in engineering, economics, biology, and medicine, and can be considered a veritable contribution to the literature. Original papers relating to the objective presented above are especially welcome subjects. Potential topics include, but are not limited to: Stability analysis of discrete and continuous dynamical systems; Nonlinear dynamics in biological complex systems; Stability and stabilization of stochastic systems; Mathematical models in statistics and probability; Synchronization of oscillators and chaotic systems; Optimization methods of complex systems; Reliability modeling and system optimization; Computation and control over networked systems

Development And Human Performance Evaluation Of Control Modes Of An Exo-Skeletal Assistive Robotic Arm (esara)

This research was conducted to assist with functional tasks for a targeted group of individuals with spinal cord injury (SCI); with C5 to C7 level of injury relating to upper extremity movement. The specific population was selected as the existing technology was either too expensive, too bulky or was unable to address their needs in regards to upper extremity mobility. In addition, no platforms allowed multimodal control options for customization or provided a methodology for this crucial evaluation. The motivation of this research was to provide a methodology for selecting the appropriate control of an assistive device based on the range of basic human movements that were possible by the population under consideration (button pushing, lever sliding, and speech). The main idea was to create an evaluation methodology based on a user platform with multiple modes of control. The controls were developed such that they would allow operation of the device with respect to the capabilities of SCI participants. Engineering advancements have taken assistive robotics to new dimensions. Technologies such as wheelchair robotics and myo-electronically controlled systems have opened up a wide range of new applications to assist people with physical disabilities. Similarly exo-skeletal limbs and body suits have provided new foundations from which technologies can aid function. Unfortunately, these devices have issues of usability, weight, and discomfort with donning. The Smart Assistive Reacher Arm (SARA) system, developed in this research, is a voice-activated, lightweight, mobile device that can be used when needed. SARA was built to help overcome daily reach challenges faced by individuals with limited arm and hand movement capability, such as people with cervical level 5-6 (C5-6) SCI. The functional reacher arm with voice control can be beneficial for this population. Comparison study with healthy participants and an SCI participant shows that, when using SARA, a person with SCI can perform simple reach and grasp tasks independently, without someone else\u27s help. This suggests that the interface is intuitive and can be easily used to a high-level of proficiency by a SCI individual. Using SARA, an Exo-Skeletal Assistive Robotic Arm (eSARA) was designed and built. eSARA platform had multiple modes of control namely, voice (ballistic mode with no extremity movement), button (ballistic mode with minor extremity movement) and slider (continuous mode with major extremity movement). eSARA was able to extend a total of 7 inches from its original position. The platform also provided lift assist for users that can potentially enable them to lift up to 20lbs.The purpose of eSARA was to build a platform that could help design a methodology to select the modality for a specific level of SCI injury or capability. The eSARA platform\u27s Human Machine Interface (HMI) was based on two experiments `Fine movement experiment\u27 and `Gross movement experiment\u27. These experiments tested the reaching, grasping and lifting ability of the platform. Two groups of healthy young adults were selected to perform the experiment. The first group, 12 healthy participants, had no movement restrictions. The second group, 6 Occupational Therapy students, that could mimic restrictions similar to those of a level 5-6 SCI individual. The experiment was also conducted by an SCI individual. The results of the 2 groups from both the experiments were compared with the results of the SCI participant. It was found that the SCI participant\u27s time performance to finish the tasks was comparable to the average of the healthy participants. It was concluded that the developed methodology and platforms could be used to evaluate the control modes needed in order to customize the system to the capabilities of SCI individual. . These platforms can be tested for a broader range of participants including participants with arthritis, recovering from paralysis and seniors with movement issues

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019