An approach for characterizing the operating modes in dynamic hybrid control architectures

Nowadays, manufacturing control system faces the challenge of featuring optimal and reactive mechanisms to respond to volatile environments. In automation domain, hybrid control architectures solve these requirements as it allows coupling predictive/proactive and reactive techniques in manufacturing operations. However, to include dynamic coupling features, it is necessary to characterize the possible new operating modes and visualize its potential when a switching is needed. This paper presents an approach to characterize the operating modes of dynamic hybrid control architectures to support the dynamic switching process. The results, obtained through a simulation in a multi agent platform of flexible manufacturing systems, showed the interest of our approach in terms of including the characterization of operating modes as decisional criteria towards a system switching.info:eu-repo/semantics/publishedVersio

A switching mechanism framework for optimal coupling of predictive scheduling and reactive control in manufacturing hybrid control architectures

Nowadays, manufacturing systems are seeking control architectures that offer efficient production performance and reactivity to disruptive events. Dynamic hybrid control architectures are a promising approach as they are not only able to switch dynamically between hierarchical, heterarchical and semi-heterarchical structures, they can also switch the level of coupling between predictive scheduling and reactive control techniques. However, few approaches address an efficient switching process in terms of structure and coupling. This paper presents a switching mechanism framework in dynamic hybrid control architectures, which exploits the advantages of hierarchical manufacturing scheduling systems and heterarchical manufacturing execution systems, and also mitigates the respective reactivity and optimality drawbacks. The main feature in this framework is that it monitors the system dynamics online and shifts between different operating modes to attain the most suitable production control strategy. The experiments were carried out in an emulation of a real manufacturing system to illustrate the benefits of including a switching mechanism in simulated scenarios. The results show that the switching mechanism improves response to disruptions in a global performance indicator as it permits to select the best alternative from several operating modes.This article was supported by COLCIENCIAS Departamento Administrativo de Ciencia, Tecnología e Innovación 10.13039/100007637 [Grant Number Convocatoria 568 Doctorados en el exterior]; Pontificia Universidad Javeriana [Grant Number Programa de Formacion de posgrados].info:eu-repo/semantics/publishedVersio

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness, and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission Planning and Scheduling (MPS) frameworks are then presented as a key component to implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics and the notions of tasks, resources, and constraints. This paper concludes by proposing future strands of work devoted to study the trade-offs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.Postprint (author's final draft

Determining structural performance

An overview of the methods and concepts developed to enhance and predict structural dynamic characteristics of advanced aeropropulsion systems is presented. Aeroelasticity, vibration control, dynamic systems, and computational structural methods are four disciplines that make up the structural dynamic effort at LeRC. The aeroelasticity program develops analytical and experimental methods for minimizing flutter and forced vibration of aerospace propulsion systems. Both frequency domain and time domain methods were developed for applications on the turbofan, turbopump, and advanced turboprop. In order to improve life and performance, the vibration control program conceives, analyzes, develops, and demonstrates new methods for controlling vibrations in aerospace systems. Active and passive vibration control is accomplished with electromagnetic dampers, magnetic bearings, and piezoelectric crystals to control rotor vibrations. The dynamic systems program analyzes and verifies the dynamics of interacting systems, as well as develops concepts and methods for high-temperature dynamic seals. Work in this field involves the analysis and parametric identification of large, nonlinear, damped, stochastic systems. The computational structural methods program exploits modern computer science as an aid to the solutions of structural problems

Topology Considerations in Hybrid Electric Vehicle Powertrain Architecture Design.

Optimal system architecture (topology or configuration) design has been a challenging design problem because of its combinatorial nature. Parametric optimization studies make design decisions assuming a given architecture but there has been no general methodology that addresses design decisions on the system architecture itself. Hybrid Electric Vehicle (HEV) powertrains allow various architecture alternatives created by connecting the engine, motor/generators and the output shaft in different ways through planetary gear systems. Addition of clutches to HEV powertrains allows changing the connection arrangement (configuration) among the powertrain components during the vehicle operation. Architectures with this capability are referred to as multi-mode architectures while architectures with fixed configurations are referred to as single-mode architectures. HEV architecture optimization requires designing the powertrain’s configuration and its sizing simultaneously. Additionally, evaluation of an HEV architecture design depends on a power management (control) strategy that distributes the power demand to the engine and motor/generators. Including this control problem increases the complexity of the HEV architecture design problem. This dissertation focuses on a general methodology to make design decisions on HEV powertrain architecture and component sizes. The representation of the architecture design problem is critical to solving this problem. A new general representation capable of describing all architecture alternatives is introduced. Using the representation, all feasible configurations are generated where these feasible configurations are used to create single- and multi-mode HEV architectures. Single-mode and multi-mode architecture design problems considering fuel economy, vehicle performance and architecture complexity are formulated separately and solution strategies are developed. The high complexity of the resulting optimization problem does not allow us to claim true optimality rigorously; therefore, the terms ``promising" or ``near-optimal" are more accurate in characterizing our results. The results show that different architectures must be designed for different applications. The case studies designing architectures for some available vehicles from the market find the architectures already implemented in these vehicles under some design constraints. Alternative architectures that improve these designs under different design constraints are also demonstrated. Architectures for a new application that is not available in the market are also designed.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111412/1/bayrak_1.pd