feedback fuzzy-dvs scheduling of control tasks

To consider the energy-aware scheduling problem in computer-controlled systems is necessary to improve the control performance, to use the limited computing resource sufficiently, and to reduce the energy consumption to extend the lifetime of the whole system. In this paper, the scheduling problem of multiple control tasks is discussed based on an adjustable voltage processor. A feedback fuzzy-DVS (dynamic voltage scaling) scheduling architecture is presented by applying technologies of the feedback control and the fuzzy DVS. The simulation results show that, by using the actual utilization as the feedback information to adjust the supply voltage of processor dynamically, the high CPU utilization can be implemented under the precondition of guaranteeing the control performance, whilst the low energy consumption can be achieved as well. The proposed method can be applied to the design in computer-controlled systems based on an adjustable voltage processor.

The role of knowledge facilitators and inhibitors: lessons from airline reservations systems.

Strategic frameworks seeking to explain how an organisation may generate superior performance are numerous. Earlier approaches centred on the competitive position of an organisation within its industry, with subsequent attention focused on an organisation's core competences. More recently, research has concentrated on knowledge and organisational learning. By reference to a study of airline-developed computer reservation systems (CRSs), this article explores the strategic importance of information in creating knowledge to generate superior performance. By examining developments in the use, management and control of information derived from CRSs, evidence is presented to explain how CRS-owning airlines have circumvented regulatory controls and increasingly competition to sustain competitive advantage through the development of their information and knowledge systems. This research demonstrates the need for organisations to develop 'knowledge facilitators' that foster the creation of new knowledge. Equally, managers must develop 'knowledge inhibitors' that help to sustain competitive advantage by limiting the abilities of competitors to create knowledge themselves.

A run-time configurable software architecture for self-managing systems

This paper describes a highly flexible component architecture, primarily designed for automotive control systems, that supports distributed dynamically- configurable context-aware behaviour. The architecture enforces a separation of design-time and run-time concerns, enabling almost all decisions concerning runtime composition and adaptation to be deferred beyond deployment. Dynamic context management contributes to flexibility. The architecture is extensible, and can embed potentially many different self-management decision technologies simultaneously. The mechanism that implements the run-time configuration has been designed to be very robust, automatically and silently handling problems arising from the evaluation of self- management logic and ensuring that in the worst case the dynamic aspects of the system collapse down to static behavior in totally predictable ways.

Temperature, pH, and conductivity control of the nutrient solution of an hydroponic greenhouse

One of the aspects of modern agriculture is characterised by a culture without soil (hydroponic cultures). These culture techniques are identified by possessing automatic control systems to control the nutrient solution. In first hydroponic cultures this control was accomplished by “on- off” analog controllers that applied a single control law implemented in hardware. Therefore, the changes of the control law resulted in the change of all interface electronics. In digital control implemented by micro-controllers the alteration of such control law is easily performed by changing only a computer program, leaving untouched all the interface hardware. In this way, the use and substitution of the control strategy is improved, as well, the use of advanced control strategies.

Completely supervised training algorithms for B-spline neural networks and neuro-fuzzy systems

Complete supervised training algorithms for B-spline neural networks and fuzzy rule-based systems are discussed. By interducing the relationship between B-spline neural networks and certain types of fuzzy models, training algorithms developed initially for neural networks can be adapted by fuzzy systems.

Quantified set inversion with applications to control

This paper describes a new reliable method, based on modal interval analysis (MIA) and set inversion (SI) techniques, for the characterization of solution sets defined by quantified constraints satisfaction problems (QCSP) over continuous domains. The presented methodology, called quantified set inversion (QSI), can be used over a wide range of engineering problems involving uncertain nonlinear models. Finally, an application on parameter identification is presented

Identification and Semiactive Control of Smart Structures Equipped with Magnetorheological Actuators

This paper deals with the problem of identification and semiactive control of smart structures subject to unknown external disturbances such as earthquake, wind, etc. The experimental setup used is a 6-story test structure equipped with shear-mode semiactive magnetorheological actuators being installed in WUSCEEL. The experimental results obtained have verified the effectiveness of the proposed control algorithms

Integration of knowledge-based, qualitative and numeric tools for real time dynamic systems supervision

The proposal presented in this thesis is to provide designers of knowledge based supervisory systems of dynamic systems with a framework to facilitate their tasks avoiding interface problems among tools, data flow and management. The approach is thought to be useful to both control and process engineers in assisting their tasks. The use of AI technologies to diagnose and perform control loops and, of course, assist process supervisory tasks such as fault detection and diagnose, are in the scope of this work. Special effort has been put in integration of tools for assisting expert supervisory systems design. With this aim the experience of Computer Aided Control Systems Design (CACSD) frameworks have been analysed and used to design a Computer Aided Supervisory Systems (CASSD) framework. In this sense, some basic facilities are required to be available in this proposed framework: ·

Integrable Hamiltonian systems defined on the Lie groups SO(3) and SU(2): an application to the attitude control of a spacecraft

This paper considers left-invariant control systems defined on the Lie groups SU(2) and SO(3). Such systems have a number of applications in both classical and quantum control problems. The purpose of this paper is two-fold. Firstly, the optimal control problem for a system varying on these Lie Groups, with cost that is quadratic in control is lifted to their Hamiltonian vector fields through the Maximum principle of optimal control and explicitly solved. Secondly, the control systems are integrated down to the level of the group to give the solutions for the optimal paths corresponding to the optimal controls. In addition it is shown here that integrating these equations on the Lie algebra su(2) gives simpler solutions than when these are integrated on the Lie algebra so(3).

Queue-based agent communication architecture for intelligent human-like computer interfaces

Human-like computer interaction systems requires far more than just simple speech input/output. Such a system should communicate with the user verbally, using a conversational style language. It should be aware of its surroundings and use this context for any decisions it makes. As a synthetic character, it should have a computer generated human-like appearance. This, in turn, should be used to convey emotions, expressions and gestures. Finally, and perhaps most important of all, the system should interact with the user in real time, in a fluent and believable manner.

Fuzzy distributed artificial intelligence systems

In this paper, we introduce a DAI approach called hereinafter Fuzzy Distributed Artificial Intelligence (FDAI). Through the use of fuzzy logic, we have been able to develop mechanisms that we feel may effectively improve current DAI systems, giving much more flexibility and providing the subsidies which a formal theory can bring. The appropriateness of the FDAI approach is explored in an important application, a fuzzy distributed traffic-light control system, where we have been able to aggregate and study several issues concerned with fuzzy and distributed artificial intelligence. We also present a number of current research directions necessary to develop the FDAI approach more fully.

On Nonlinear Dynamics and Control of A Particular Portal Frame Foundation Model, Excited by a Non-Ideal Motor

The nonlinear dynamic response and a nonlinear control method of a particular portal frame foundation for an unbalanced rotating machine with limited power (non-ideal motor) are examined. Numerical simulations are performed for a set of control parameters (depending on the voltage of the motor) related to the static and dynamic characteristics of the motor. The interaction of the structure with the excitation source may lead to the occurrence of interesting phenomena during the forward passage through the several resonance states of the systems. A mathematical model having two degrees of freedom simplifies the non-ideal system. The study of controlling steady-state vibrations of the non-ideal system is based on the saturation phenomenon due to internal resonance.

The LQ control problem for Markovian jumps linear systems with horizon defined by stopping times

This paper deals with a stochastic optimal control problem involving discrete-time jump Markov linear systems. The jumps or changes between the system operation modes evolve according to an underlying Markov chain. In the model studied, the problem horizon is defined by a stopping time τ which represents either, the occurrence of a fix number N of failures or repairs (TN), or the occurrence of a crucial failure event (τΔ), after which the system is brought to a halt for maintenance. In addition, an intermediary mixed case for which T represents the minimum between TN and τΔ is also considered. These stopping times coincide with some of the jump times of the Markov state and the information available allows the reconfiguration of the control action at each jump time, in the form of a linear feedback gain. The solution for the linear quadratic problem with complete Markov state observation is presented. The solution is given in terms of recursions of a set of algebraic Riccati equations (ARE) or a coupled set of algebraic Riccati equation (CARE).

A comparative study between two relaxed LMI-based fuzzy control designs

A comparative study, with theoretical analysis and digital simulations, of two conditions based on LMI for the quadratic stability of nonlinear continuous-time dynamic systems, described by Takagi-Sugeno fuzzy models, are presented. This paper shows that the methods proposed by Teixeira et. al. in 2003 provide better or at least the same results of a recent method presented in the literature. © 2005 IEEE.

Linear quadratic Gaussian control of discrete-time Markov jump linear systems with horizon defined by stopping times

The linear quadratic Gaussian control of discrete-time Markov jump linear systems is addressed in this paper, first for state feedback, and also for dynamic output feedback using state estimation. in the model studied, the problem horizon is defined by a stopping time τ which represents either, the occurrence of a fix number N of failures or repairs (T N), or the occurrence of a crucial failure event (τ δ), after which the system paralyzed. From the constructive method used here a separation principle holds, and the solutions are given in terms of a Kalman filter and a state feedback sequence of controls. The control gains are obtained by recursions from a set of algebraic Riccati equations for the former case or by a coupled set of algebraic Riccati equation for the latter case. Copyright © 2005 IFAC.