2009 (Volume 19)
CLP approach to optimal instruction scheduling for VLIW processors
(Motorola Polska Electronics Sp. z o.o.)
Along with modern processor architectures where multiple functional units can execute instructions in parallel and numerous resources have to be managed, there is a need for efficient tools facilitating code generation and enhancing development. The aim is to achieve maximal instruction throughput. This is a place where automatic
optimization techniques should be employed due to high complexity of the real life problems.
This article presents an approach to optimal instruction scheduling for very long instruction word (VLIW) processors using a constraint logic programming (CLP) solver with particular emphasis on the modulo scheduling technique. Modulo scheduling is an optimization technique used to achieve greater instruction level parallelism than one achievable by just optimally scheduling code basic blocks.
keywords: VLIW, processor, modulo scheduling, constraint logic programming
Hybrid adaptive control for speed regulation of an induction motor drive
(Power Electronics Laboratory, Nuclear Research Center of Brine, Algeria)
|D. Boukhetala, F. Boudjema|
(Department of Electric Eng, Laboratoire de Commande des Processus, ENSP, Algeria)
Model Reference Adaptive Control (MRAC) techniques may be used in high performance applications of nduction-motor (IM) drives to minimize adverse effects from changes in the load conditions and/or system parameters. Although the MRAC technique accounts for uncertainties and/or inaccuracies of the motor and load parameters in the design stage, its implementation on an nteger-based Digital Signal Processor (DSP) has several difficulties associated with the large dynamic range of the covariance matrix and the finite length of the DSP word. This paper investigates new form of a hybrid model reference adaptive speed control (HMRAC) to adapt the closed loop system including the plant with variation parameter to match with the reference model. The adaptive analog controller consists of a set of analog gain controller and a switching controller. The switching controller selects a controller from the set of analog controllers and connects it into the closed loop controlled system suitably. The duty rate of each analog controller will adapt the closed loop controlled system to be coincided with a reference model in reasonable sense. The importance of the hybrid controller is demonstrated by intensive experimental results. It is shown that the presented HMRAC for IM drive has fast tracking capability, smaller steady state error and is robust to load disturbance.
keywords: induction motor, field oriented control, hybrid control, MRAC
Positivity and stabilization of fractional 2D Roesser model by state-feedbacks, LMI approach
(Białystok Technical University, Faculty of Electrical Engineering, Poland)
LMI approach is applied to compute a gain matrix of state-feedbacks such that the closed-loop system is positive and asymptotically stable. Necessary and suffiecient conditions for the solvability of the problem are established. The proposed method is illustrated by two numerical examples.
keywords: fractional 2D Roesser model, positive, stabilization, state-feedbacks, LMI
On hybrid observability and sliding mode observer in three cells converter
|A. Mezhoud, S. Maradi, M. Tadjine|
(LCP, ENP, Algeria)
|K. Benmansour, M. Djemai|
((ECS), ENSEA, Cedex, France)
Power converters by their nature present hybrid behavior since they contains switched circuits. Such circuits can be described by a set of discrete states with associated continuous dynamics. In this paper a new hybrid model for a 3-cells power converter is proposed. This hybrid model incorporates both the continuous and discrete states allowing better understanding of the system operating modes and properties. Of particular interests the new concept of hybrid Z(T_N) observability is used to deal with the observability of the capacitors voltages and a discussion on the achievable observation dynamics is given. A sliding mode observer strategy is derived to estimate the flying voltages of the converter. Furthermore, it is derived that under some specific control sequence, the observation errors are asymptotically stable. Finally, experimental results are presented in order to illustrate the performance of the proposed approach.
keywords: 3-cells converter, hybrid switched systems, observability, sliding mode observer, real time evaluation
Stabilization methods for nonlinear second-order systems
(Akademia Górniczo-Hutnicza, Department of Automatics, Kraków, Poland)
The goal of this paper is to study stabilization techniques for a system described by nonlinear second-order differential equations. The problem is to determine the feedback control as a function of the state variables. It is shown that the following controllers can asymptotically stabilize the system: linear position feedback, linear velocity feedback and a group of nonlinear feedbacks. The asymptotic stability of the closed-loop system has been proved by LaSalle's invariance principle. The results of numerical computations are included to verify theoretical analysis and mathematical formulation.
keywords: nonlinear system, stabilization, asymptotic stability, linear feedback, nonlinear feedback
Intelligent nonlinear optimal controller of a biotechnological process
(Department of Electronics, University of Jijel, Algeria)
(Department of Electrotechnics, University of Skikda, Algeria)
(Department of Electronics, University of Ferhat Abbas-Setif, Algeria)
Designing an effective criterion and learning algorithm for finding the best structure is a major problem in the control design process. In this paper, the fuzzy Proportional Parallel Distributed Compensation with Reduced Rule Base approach (PPDC_RRB) is proposed. The design problem considered is essentially nonlinear optimal and robust control problem due to the nonlinear nature of the Takagi-Sugeno fuzzy system. The control signal thus obtained will minimize performance index, which is a function of the tracking/regulating errors, the quantity of the energy of the control signal applied to the system, and the number of fuzzy rules. The genetic learning is proposed for constructing the PPDC_RRB controller. The chromosome genes are arranged into two parts, the binary-coded part contains the control genes and the real-coded part contains the genes parameters representing the fuzzy knowledge base. The effectiveness of this chromosome formulation enables the fuzzy sets and rules to be optimally reduced. The chaotic mutation is introduced for maintaining the population diversity during the evolution process of the genetic algorithm. The performances of the PPDC_RRB are compared with those found by the traditional PD controller with Genetic Optimization (PD_GO). Simulations demonstrate that the proposed PPDC_RRB and PD_GO has successfully met the design specifications.
keywords: nonlinear optimal controller, genetic learning, PDC, reduced rule base