Unified Design Framework Research Articles

A Unified Framework for Design and Analysis of Networked and Quantized Control Systems

We generalize and unify a range of recent results in quantized control systems (QCS) and networked control systems (NCS) literature and provide a unified framework for controller design for control systems with quantization and time scheduling via an emulation-like approach. A crucial step in our proofs is finding an appropriate Lyapunov function for the quantization/time-scheduling protocol which verifies its uniform global exponential stability (UGES). We construct Lyapunov functions for several representative protocols that are commonly found in the literature, as well as some new protocols not considered previously. Our approach is flexible and amenable to further extensions which are briefly discussed.

COMPUTATIONAL DESIGN FOR MULTIFUNCTIONAL MICROSTRUCTURAL COMPOSITES

As an important class of natural and engineered materials, periodic microstructural composites have drawn substantial attention from the material research community for their excellent flexibility in tailoring various desirable physical behaviors. To develop periodic cellular composites for multifunctional applications, this paper presents a unified design framework for combining stiffness and a range of physical properties governed by quasi-harmonic partial differential equations. A multiphase microstructural configuration is sought within a periodic base-cell design domain using topology optimization. To deal with conflicting properties, e.g. conductivity/permeability versus bulk modulus, the optimum is sought in a Pareto sense. Illustrative examples demonstrate the capability of the presented procedure for the design of multiphysical composites and tissue scaffolds.

A Unified Design Framework for Single-Channel Dispersion-Managed Terrestrial Systems

This paper provides a unified framework to the design, performance optimization, and accurate numerical simulation of periodic, dispersion-managed (DM) single-channel long-haul optical transmission systems for nonsoliton on-off keying (OOK) modulation. The focus is on DM terrestrial systems, with identical spans composed of a long transmission fiber compensated at the span end by a linear dispersion compensating module, with pre- and postcompensation fibers at the beginning and end of the link. The framework is based on the dispersion-managed nonlinear Schrodinger equation (DM-NLSE). First, expressions of the DM-NLSE kernel are provided both in the frequency and the time domain, and a novel map strength parameter, appropriate for terrestrial systems, is introduced. It is then shown that the DM-NLSE contains all the basic information needed for system design, as summarized by three parameters: i) nonlinear phase, ii) in-line dispersion, and iii) map strength. Through a large-signal perturbative analysis of the DM-NLSE, the well-known linear relationship between the in-line dispersion and the optimal precompensation is derived, along with the large-signal step response of the DM link, from which the ghost pulses energy growth and a first estimation of the link memory are derived. The DM-NLSE is then linearized around the average signal field to get the amplitude/phase small-signal system matrix of the overall DM link, including pre- and postcompensation. By a singular-value decomposition of the small-signal DM link matrix, a novel expression of the memory of the optimized DM link is finally provided. Knowledge of such a memory is mandatory to run accurate numerical simulations and laboratory measurements with a sufficiently long pseudorandom bit sequence to avoid patterning effects.

A neural network approach to FIR filter design using frequency-response masking technique

This paper presents a new optimization method for the design of various frequency-response-masking (FRM)-based linear-phase finite-impulse response (FIR) digital filters. The method is based on a batch back-propagation neural network algorithm (NNA), which is taken as a variable learning rate mode. In order to reduce the complexity, the following two-step optimization technique is proposed. At the first step, an initial FRM filter is designed by alternately optimizing the sub-filters. This solution is then used as a start-up solution for further optimization. At the second step, the coefficients of overall sub-filters are optimized simultaneously by the NNA. Algorithm details for the design of basic and multistage FRM filters are presented to show that the proposed approach offers a unified design framework for a variety of FRM filters. Some examples taken from the literatures are included and the results show that the proposed algorithm can design better FRM filters than several existing methods.

Impulsive and Hybrid Dynamcial Systems: Stability, Dissipativity and Control (W.M. Haddad et al.; 2008) [Bookshelf

The stated objective of this book is to "develop a unified analysis and control design framework for impulsive and hybrid dynamical systems using a Lyapunov and dissipative systems approach." The book is organized into 13 chapters and includes an appendix section. Some of the topics covered include: stability theory for time-variant and time-varying impulsive systems; extending the notion of dissipative dynamical systems to impulsive dissipative dynamical systems; vector dissipativity for large-scale nonlinear impulsive dynamical systems; the stability of feedback interconnections of dissipative impulsive dynamical systems; qualitative analyses of special classes of impulsive hybrid feedback control systems; disturbance rejection control and robust control for nonlinear impulsive dynamical systems with bounded exogenous disturbances; and Poincare's theorem adapted to left-continuous dynamical systems. This book fills a void in the area of systems research and is a welcome addition to the literature on hybrid and impulsive systems. The book is well-organized, well written, and rigorous in the development of the subject on hand. It would be of great use to many researchers within the control systems community and could be used as the basis for a graduate course om control systems.

A framework for designing mimo systems with decision feedback equalization or tomlinson-harashima precoding

We consider joint transceiver design for point-to-point Multiple-Input Multiple-Output communication systems that implement interference (pre-)subtraction; i.e., Decision Feedback Equalization (DFE) or Tomlinson-Harashima precoding (THP). We develop a unified framework for joint transceiver design of these two dual systems by considering design criteria that are expressed as functions of the (logarithm of the) Mean Square Error (MSE) of the individual data streams. By deriving two inequalities that involve the logarithms of the individual MSEs, we obtain optimal designs for two broad classes of communication objectives, namely those that are Schur-convex and Schur-concave functions of these logarithms. These two classes embrace several design criteria for which the optimal transceiver design has remained an open problem. For Schur-convex objectives, the optimal design results in data streams with equal MSEs. In addition to other desirable properties, this design simultaneously minimizes the total MSE and the average bit error rate, and maximizes the Gaussian mutual information; a property that is not achieved by a linear transceiver. Moreover, we show that the optimal design yields objective values that are superior to the corresponding optimal objective value for a linear transceiver. For Schur-concave objectives, the optimal DFE design results in linear equalization and the optimal THP design results in linear precoding. The proposed design framework can be regarded as a counterpart of the existing framework for linear transceiver design.

Observer-based output feedback controller for a class of nonlinear systems

The design of an observer based output feedback controller for a class of uniformly observable nonlinear systems with an admissible tracking capability, is proposed. Two fundamental features of the proposed control scheme are worth to be mentioned. The first one consists in the high gain nature of the underlying state feedback control and observer designs. More specifically, a unified high gain control design framework is proposed thanks to the duality between control and observation. The second feature consists in incorporating a filtered integral action into the control design. The filtering is mainly motivated by measurement noise sensitivity reduction while the integral action allows to achieve a robust offset free performance in the presence of step like disturbances. The features of the proposed approach are illustrated using the induction motor model and simulation are performed in order to highlight the performance of the underlying observer based output feedback controller.

A Unified Adaptive Iterative Learning Control Framework for Uncertain Nonlinear Systems

In this note, we propose a unified framework for adaptive iterative learning control design for uncertain nonlinear systems. It is shown that if a Lyapunov based adaptive control law is available for the system under consideration and the Lyapunov function satisfies certain conditions, it is straightforward to extend the adaptive controller to handle repetitive systems operating over a finite time interval. According to the value of a certain parameter γ, the parametric adaptation law can be a pure time-domain adaptation, a pure iteration-domain adaptation or a combination of both.A pure iteration-domain adaptation is described by a difference equation, a pure time-domain adaptation is described by a differential equation, and a combination of both is described by a differential-difference equation. The advantages and disadvantages of the three possible adaptation types are discussed and some illustrative examples are given.

Comparison of p-cycles and p-trees in a unified mathematical framework

As high-speed networks grow in capacity, network protection becomes increasingly important. Recently, following interest in p-cycle protection, the related concept of p-trees has also been studied. In one line of work, a so-called “hierarchical tree” approach is studied and compared to p-cycles on some points. Some of the qualitative conclusions drawn, however, apply only to p-cycle designs consisting of a single Hamiltonian p-cycle. There are other confounding factors in the comparison between the two, such as the fact that, while the tree-based approach is not 100% restorable, p-cycles are. The tree and p-cycle networks are also designed by highly dissimilar methods. In addition, the claims regarding hierarchical trees seem to contradict earlier work, which found pre-planned trees to be significantly less capacity-efficient than p-cycles. These contradictory findings need to be resolved; a correct understanding of how these two architectures rank in terms of capacity efficiency is a basic issue of network science in this field. We therefore revisit the question in a definitive and novel way in which a unified optimal design framework compares minimum capacity, 100% restorable p-tree and p-cycle network designs. Results confirm the significantly higher capacity efficiency of p-cycles. Supporting discussion provides intuitive appreciation of why this is so, and the unified design framework contributes a further theoretical appreciation of how pre-planned trees and pre-connected cycles are related. In a novel further experiment we use the common optimal design model to study p-cycle/p-tree hybrid designs. This experiment answers the question “To what extent can a selection of trees compliment a cycle-based design, or vice-versa?” The results demonstrate the intrinsic merit of cycles over trees for pre-planned protection.

An Efficient Unified Framework for Implementation of a Prime-Length DCT/IDCT With High Throughput

In this paper, a unified design framework for prime-length forward and inverse discrete cosine transforms with a high throughput is presented. The proposed design facilitates trade-off between the throughput and hardware cost or power consumption, and is well suited for low-power applications. The VLSI structure is highly regular and modular with a topology well suited for the VLSI implementation. The proposed approach is based on the derivation of new efficient systolic algorithms. The algorithms have the same core structure for both the transforms, and the core structure consists of two circular correlations, which unlike other similar computational structures, have the same length and form. Thus, they can be computed in parallel and mapped on the same linear systolic array with channels having a low I/O bandwidth requirement and their number being independent of the transform length N. Further, it is shown that the two transforms, can be efficiently implemented on the same VLSI chip, where only the pre- and post-processing stages are different. The proposed systolic algorithms retain the benefits provided by VLSI implementations based on circular or cyclic convolution structures, and at the same time has a simpler control structure, high speed and low complexity

Integrated Design of Structural and Control Systems Based on a Polynomial Matrix Approach: A Unified Framework for Structural and/or Control Design

A unified methodology of structural and/or control design for mechanical systems based on a polynomial matrix approach is proposed. A closed-loop D-stability specification is considered in this paper. By employing the polynomial matrix approach structural design parameters of mechanical systems, e.g., the mass, the damping and the stiffness and a feedback controller that is allowed to have a specified structure can be obtained simultaneously by solving LMIs. A simple iterative algorithm to obtain a better D-stable closed-loop system and a better central polynomial matrix is proposed. Design examples are provided to show the effectiveness of the present idea.

Social Foraging Theory for Robust Multiagent System Design

An analogy between an agent (e.g., an autonomous vehicle) and a biological forager is extended to a social environment by viewing a communication network as implementing interagent sociality. We first describe engineering design within an evolutionary game-theoretic framework. We then explain why sociality may emerge in some environments and for some agent objectives. Next, we derive the evolutionarily stable design strategy for an agent manufacturer: 1) choosing whether the agent it produces should cooperate with other agents in a search problem and 2) choosing the group size of a multiagent system tasked with a cooperative search problem. We show the impact of "agent relatedness," a measure of common descent between two agents based on their underlying manufacturers, on the choices in scenarios 1) and 2). Our predictions are evaluated in an autonomous vehicle simulation testbed. The results illustrate a new methodology for manufacturers to make robust, optimal choices for multiagent system design for a given set of objectives and domain of operation. Note to Practitioners-The design of autonomous multirobot systems with various applications, such as in parts production or search and destroy operations in a military environment, is of growing importance. Here, we integrate economic and technical issues into an unified engineering design framework for the manufacturers of robots. Our approach leads to manufacturer design decisions that are robust relative to the market for a manufacturer's products. Robot component aspects, such as sensors and communications as well as mission performance aspects, can be captured and coupled into the design process. We use the design of intervehicle cooperation and robot group size to illustrate this approach. The practical significance lies in the fact that we take a broad perspective on engineering design, one closer to the real world, due to the considerations of marketplace economics. Moreover, the approach provides a framework to study design choices that escape systematic analysis in other frameworks (e.g., group size)

Optimal design and verification of temporal and spatial filters using second-order cone programming approach

Temporal filters and spatial filters are widely used in many areas of signal processing. A number of optimal design criteria to these problems are available in the literature. Various computational techniques are also presented to optimize these criteria chosen. There are many drawbacks in these methods. In this paper, we introduce a unified framework for optimal design of temporal and spatial filters. Most of the optimal design problems of FIR filters and beamformers are included in the framework. It is shown that all the design problems can be reformulated as convex optimization form as the second-order cone programming (SOCP) and solved efficiently via the well-established interior point methods. The main advantage of our SOCP approach as compared with earlier approaches is that it can include most of the existing methods as its special cases, which leads to more flexible designs. Furthermore, the SOCP approach can optimize multiple required performance measures, which is the drawback of earlier approaches. The SOCP approach is also developed to optimally design temporal and spatial two-dimensional filter and spatial matrix filter. Numerical results demonstrate the effectiveness of the proposed approach.

A Unified Mathematical Framework for Strapdown Algorithm Design

A Unified Mathematical Framework for Strapdown Algorithm Design

A context-based simulation tool for design and evaluation of network processors

Network processor, a kind of highly integrated programmable circuit, attempts to strike a balance between performance and flexibility in network processing. Research on architecture design and system implementation concerning network processors requires powerful simulation tools. Many existing methods use execution-driven full-system simulators to build a virtual target platform running unmodified application binaries. However, they oversimplify the network environment in which the whole system is working. To address this issue, we develop a performance tool named Network Porcessor Network Simulator (NPNS) built upon a well-known network simulator—ns-2. This tool combines those full-system simulators to provide a unified framework for processor and software design within a network context. This article presents the principle, architecture and implementation issues of NPNS. To demonstrate the validity of the tool, two examples using the NPNS prototype to simulate the Intel IXP1200 network processor are illustrated and their performance is further evaluated. The performance results reveal the importance of considering network context for improving the accuracy of network models and achieving more realistic network simulations.

Scoping and Sequencing Educational Resources and Speech Acts: A Unified Design Framework for Learning Objects and Educational Discourse

Scoping and Sequencing Educational Resources and Speech Acts: A Unified Design Framework for Learning Objects and Educational Discourse

A unified framework for designing FIR filters with arbitrary magnitude and phase response

A unified framework for the optimal design of finite impulse response (FIR) filters with arbitrary magnitude and phase response using second-order cone (SOC) programming is proposed. FIR filters with desired frequency response can be implemented by minimizing the frequency domain response error measure (L1, L2, or L~ norm of the error) between the desired response and the designed filter response. Some constraints can also be imposed in the passband or/and stopband to satisfy applications-oriented requirements. These optimal design problems can be reformulated as convex optimization form as the second-order cone programming and solved efficiently via the well-established interior point method. The SOC programming approach allows much more design flexibility in comparison to the classical minimax, least-square, and eigenfilter approaches. Computer simulations are presented to illustrate the developed algorithms and to evaluate the design performance. Simulation results for the design of fractional delay FIR filters and filters with desired frequency response show good performance of the proposed methods.

A Framework for Stabilization of Nonlinear Sampled-Data Systems Based on Their Approximate Discrete-Time Models

A unified framework for design of stabilizing controllers for sampled-data differential inclusions via their approximate discrete-time models is presented. Both fixed and fast sampling are considered. In each case, sufficient conditions are presented which guarantee that the controller that stabilizes a family of approximate discrete-time plant models also stabilizes the exact discrete-time plant model for sufficiently small integration and/or sampling periods. Previous results in the literature are extended to cover: 1) continuous-time plants modeled as differential inclusions; 2) general approximate discrete-time plant models; 3) dynamical discontinuous controllers modeled as difference inclusions; and 4) stability with respect to closed arbitrary (not necessarily compact) sets.

Optimal design of frequency-response-masking filters using semidefinite programming

Since Lim's paper (see IEEE Trans. Circuits Syst., vol.33, p. 357-364, Apr. 1986) on the frequency-response-masking (FRM) technique for the design of finite-impulse response digital filters with very small transition widths, the analysis and design of FRM filters has been a subject of study. In this paper, a new optimization technique for the design of various FRM filters is proposed. Central to the new design method is a sequence of linear updates for the design variables, with each update carried out by semidefinite programming. Algorithmic details for the design of basic and multistage FRM filters are presented to show that the proposed method offers a unified design framework for a variety of FRM filters. Design simulations are included to illustrate the proposed algorithms and to evaluate the design performance in comparison with that of several existing methods.

A unified view for vector rotational CORDIC algorithms and architectures based on angle quantization approach

Vector rotation is the key operation employed extensively in many digital signal processing applications. In this paper, we introduce a new design concept called Angle Quantization (AQ). It can be used as a design index for vector rotational operation, where the rotational angle is known in advance. Based on the AQ process, we establish a unified design framework for cost-effective low-latency rotational algorithms and architectures. Several existing works, such as conventional COordinate Rotational Digital Computer (CORDIC), AR-CORDIC, MVR-CORDIC, and EEAS-based CORDIC, can be fitted into the design framework, forming a Vector Rotational CORDIC Family. Moreover, we address four searching algorithms to solve the optimization problem encountered in the proposed vector rotational CORDIC family. The corresponding scaling operations of the CORDIC family are also discussed. Based on the new design framework, we can realize high-speed/low-complexity rotational VLSI circuits, whereas without degrading the precision performance in fixed-point implementations.