Redesign Problem Research Articles

Zero assignment of matrix pencils by additive structured transformations

Matrix pencil models are natural descriptions of linear networks and systems. Changing the values of elements of networks, that is redesigning them, implies changes in the zero structure of the associated pencil and this is achieved by structured additive transformations. The paper examines the problem of zero assignment of regular matrix pencils by a special type of structured additive transformations. For a certain family of network redesign problems the additive perturbations may be described as diagonal perturbations and such modifications are considered here. This problem has certain common features with the pole assignment of linear systems by structured static compensators and thus the new powerful methodology of global linearization [J. Leventides, N. Karcanias, Sufficient conditions for arbitrary Pole assignment by constant decentralised output feedback, Mathematics of Control for Signals and Systems 8 (1995) 222–240; J. Leventides, N. Karcanias, Global asymptotic linearisation of the pole placement map: A closed form solution for the constant output feedback problem, Automatica 31 (1995) 1303–1309] can be used. For regular pencils with infinite zeros, families of structured degenerate additive transformations are defined and parameterized and this lead to the derivation of conditions for zero structure assignment, as well as methodology for computing such solutions. The case of regular pencils with no infinite zeros is also considered and conditions of zero assignment are developed. The results here provide the means for studying problems of linear network redesign by modification of the non-dynamic elements.

Discretization Method of Continuous-Time Controllers Based on Frequency Response Fitting

In the present paper, a digital redesign problem that converts continuous-time controllers into digital controllers is considered. A new discretization method based on matching of the frequency res...

The minimized dead‐end elimination criterion and its application to protein redesign in a hybrid scoring and search algorithm for computing partition functions over molecular ensembles

One of the main challenges for protein redesign is the efficient evaluation of a combinatorial number of candidate structures. The modeling of protein flexibility, typically by using a rotamer library of commonly-observed low-energy side-chain conformations, further increases the complexity of the redesign problem. A dominant algorithm for protein redesign is dead-end elimination (DEE), which prunes the majority of candidate conformations by eliminating rigid rotamers that provably are not part of the global minimum energy conformation (GMEC). The identified GMEC consists of rigid rotamers (i.e., rotamers that have not been energy-minimized) and is thus referred to as the rigid-GMEC. As a postprocessing step, the conformations that survive DEE may be energy-minimized. When energy minimization is performed after pruning with DEE, the combined protein design process becomes heuristic, and is no longer provably accurate: a conformation that is pruned using rigid-rotamer energies may subsequently minimize to a lower energy than the rigid-GMEC. That is, the rigid-GMEC and the conformation with the lowest energy among all energy-minimized conformations (the minimized-GMEC) are likely to be different. While the traditional DEE algorithm succeeds in not pruning rotamers that are part of the rigid-GMEC, it makes no guarantees regarding the identification of the minimized-GMEC. In this paper we derive a novel, provable, and efficient DEE-like algorithm, called minimized-DEE (MinDEE), that guarantees that rotamers belonging to the minimized-GMEC will not be pruned, while still pruning a combinatorial number of conformations. We show that MinDEE is useful not only in identifying the minimized-GMEC, but also as a filter in an ensemble-based scoring and search algorithm for protein redesign that exploits energy-minimized conformations. We compare our results both to our previous computational predictions of protein designs and to biological activity assays of predicted protein mutants. Our provable and efficient minimized-DEE algorithm is applicable in protein redesign, protein-ligand binding prediction, and computer-aided drug design.

ADAPTABLE DESIGN OF MACHINE TOOLS STRUCTURES

Adaptable design aims to extend the utilities of design and product.The specific methods are developed for practical applications of adaptable design in the design of mechanical structures, including adaptable platform,interface and module designs.Adaptable redesign problems are formulated as adaptable platform design under adaptability bound constraints.Analysis tools are then suggested for the implementation of the redesign of machine tool structures,including variation techniques based sensitivity analysis,similarity-based commonality analysis,performance improvement,and adaptability measures.The specific measure of adaptability for machine tool structures is measured through the quantification of the structural similarity and performance improvement gained from adaptable design.The method provides designers with an approach that brings adaptability into the design process,with considering the cost and benefits of such adaptability. The redesign of CNC spiral bevel gear cutting machine structures has been included to illustrate these concepts and methods.

Rediseño paramétrico del pendubot para posicionamiento vertical en tiempo mínimo

A parametric redesign methodology of nonlinear systems for minimum-time control without constraints on the state trajectory and bounded control is proposed. This methodology states the optimum redesign problem as a dynamic optimization one. This methodology simultaneously finds both the structural parameters of the system and the switching intervals of the control signal which minimize the required time to take the system from an initial state to a final one. Experimental results applying the minimum-time control methodology and the parametric redesign methodology to the Pendubot are shown.

스마트 스페이스를 위한 난방, 환기 및 공기조화 시스템의 지능형 디지털 제어

This paper studies an automation problem of a heating, a ventilating, and an air conditioning (HVAC) for the development of smart space. The HVAC system is described by the fuzzy system for the stability analysis and the controller design. The linear matrix inequalities (LMIs) conditions are derived for the stabilization problem of the closed-loop system under the analog control. Also, it is required to digitally redesign the pre-designed the analog HVAC control system in order to accomplish the remote control via web. It is shown the this digital redesign problem can be converted to the convex optimization problem with the LMI constraints. An example is provided to show the effectiveness of the proposed method.

Redesigning a warehouse network

To take advantage of economies of scale, a growing number of firms have begun to explore the possibility of integrating supply chain activities. The advent of such a possibility would necessitate the redesign of a warehouse network. Typically, a warehouse redesign problem involves the consolidation of regional warehouses into a fewer number of master stocking points and the subsequent phase-out of redundant or underutilized warehouses without deteriorating customer services. This paper develops a mixed-integer programming model to solve the warehouse redesign problem. The usefulness of the model was validated by its successful application to a real-world problem and by its sensitivity analyses when used with changing scenarios within a warehouse network configuration.

Redesigning network topology with technology considerations

AbstractWe present a redesign methodology that automatically redesigns a network topology while considering the different network technology interfaces. The network redesign problem is to preserve as many as possible of the network devices within the original network topology to satisfy the redesign factors while minimizing the redesign cost and time. The redesign factors can be various parameters that are involved in the design of a network topology, such as the workload and number of clients. In this paper we used a uniform growth of the network workload as the main factor for topology redesign; moreover, our methodology attempts to maintain as many as possible of the network devices within the original topology while satisfying the extra growth of the clients' loads. We formulated the network redesign problem as an optimization problem and used an evolutionary approach to search the redesign space. The experimental results for a three‐level network redesign problem described here demonstrate how valuable the redesign methodology is in finding good solutions with low redesign cost and short redesign time for an enterprise networks consisting of 65 client nodes. Copyright © 2006 John Wiley & Sons, Ltd.

Model-based Rapid Redesign Using Decomposition Patterns

This paper presents a pattern-based decomposition methodology for rapid redesign to support design customization in agile manufacturing of evolutionary products. The methodology has three functional phases. The first phase, called design dependency analysis, systematizes and reorganizes the intrinsic coupling structure of a given existing design model that is represented using the design dependency matrix. The second phase, called redesign partitioning analysis, generates alternative redesign pattern solutions to form a solution selection space through a three-stage procedure. The third phase, called pattern selection analysis, finds an optimal redesign pattern solution that entails the least potential redesign effort (in the subsequent solution process). Each pattern solution identifies and delimits the portions of the design model that need to be recomputed, thus expediting the redesign solution process. In such a way, one can treat the recomputation of the entire model, which is a conventional and computation-expensive solution approach, only as the last resort to solve the redesign problem given. An example redesign problem is used for the methodology illustration.

Towards Rapid Redesign: Pattern-based Redesign Planning for Large-Scale and Complex Redesign Problems

We have developed a decomposition-based rapid redesign methodology for large and complex computational redesign problems. While the overall methodology consists of two general steps: diagnosis and repair, in this paper we focus on the repair step in which decomposition patterns are utilized for redesign planning. Resulting from design diagnosis, a typical decomposition pattern solution to a given redesign problem indicates the portions of the design model necessary for recomputation as well as the interaction part within the model accountable for design change propagation. Following this, in this paper we suggest repair actions with an approach derived from an input pattern solution, to generate a redesign road map allowing for taking a shortcut in the redesign solution process. To do so, a two-stage redesign planning approach from recomputation strategy selection to redesign road map generation is proposed. An example problem concerning the redesign of a relief valve is used for illustration and validation.

A Novel Ensemble-Based Scoring and Search Algorithm for Protein Redesign and Its Application to Modify the Substrate Specificity of the Gramicidin Synthetase A Phenylalanine Adenylation Enzyme

Realization of novel molecular function requires the ability to alter molecular complex formation. Enzymatic function can be altered by changing enzyme-substrate interactions via modification of an enzyme's active site. A redesigned enzyme may either perform a novel reaction on its native substrates or its native reaction on novel substrates. A number of computational approaches have been developed to address the combinatorial nature of the protein redesign problem. These approaches typically search for the global minimum energy conformation among an exponential number of protein conformations. We present a novel algorithm for protein redesign, which combines a statistical mechanics-derived ensemble-based approach to computing the binding constant with the speed and completeness of a branch-and-bound pruning algorithm. In addition, we developed an efficient deterministic approximation algorithm, capable of approximating our scoring function to arbitrary precision. In practice, the approximation algorithm decreases the execution time of the mutation search by a factor of ten. To test our method, we examined the Phe-specific adenylation domain of the nonribosomal peptide synthetase gramicidin synthetase A (GrsA-PheA). Ensemble scoring, using a rotameric approximation to the partition functions of the bound and unbound states for GrsA-PheA, is first used to predict binding of the wildtype protein and a previously described mutant (selective for leucine), and second, to switch the enzyme specificity toward leucine, using two novel active site sequences computationally predicted by searching through the space of possible active site mutations. The top scoring in silico mutants were created in the wetlab and dissociation/binding constants were determined by fluorescence quenching. These tested mutations exhibit the desired change in specificity from Phe to Leu. Our ensemble-based algorithm, which flexibly models both protein and ligand using rotamer-based partition functions, has application in enzyme redesign, the prediction of protein-ligand binding, and computer-aided drug design.

Exploring Open-Ended Design Space of Mechatronic Systems

To realize design automation of mechatronic systems, there are two major issues to be dealt with: open-topology generation of mechatronic systems and simulation or analysis of those models. For the first issue, we exploit the strong topology exploration capability of genetic programming to create and evolve structures representing mechatronic systems. With the use of ERCs (ephemeral random constants) in genetic programming, we can evolve the sizing of mechatronic system components together with the system structures simultaneously. The second issue, simulation and analysis of those system models, is made more complex when the systems are mixed-energy-domain systems. We take advantage of bond graphs as a tool for multi- or mixed-domain modeling and simulation of mechatronic systems. Because there are many considerations in mechatronic system design that are not completely captured by a bond graph, it is beneficial to generate multiple solutions, allowing the designer more latitude in choosing a model to implement. The approach in this paper is capable of providing a variety of design choices to the designer for further analysis, comparison and trade-off study. The approach is shown to be efficient and effective and is demonstrated in an example of open-ended real-world mechatronic system design application, a typewriter re-design problem.

Structural Dynamics Optimization Based on a Hybrid Inverse Synthesis Method Using a Quadratic Approximation

This paper lies within the framework of the so-called redesign problem of structures subjected to dynamic constraints. A hybrid synthesis algorithm is developed, combining the truncated modal basis of the initial system and the spatial or material co-ordinates of an added component, which is modelled with shell-type finite elements parameterized with respect to a shape factor. Based upon a quadratic inverse formulation, the proposed technique shows several advantages in comparison to other synthesis methods, such as a refined sensitivity strategy, a powerful modal synthesis approach and a simplified optimization phase. Numerical examples are provided illustrating the capabilities of the novel procedure.

A New Intelligent Digital Redesign for T–S Fuzzy Systems: Global Approach

This paper proposes a novel and efficient global intelligent digital redesign technique for a Takagi-Sugeno (T-S) fuzzy system. The term of intelligent digital redesign involves converting an existing analog fuzzy-model-based controller into an equivalent digital counterpart in the sense of state-matching. The proposed method should be notably discriminated from the previous works in that it allows us to globally match the states of the overall closed-loop T-S fuzzy system with the predesigned analog fuzzy-model-based controller and those with the digitally redesigned fuzzy-model-based controller, and further to examine the stabilizability by the redesigned controller in the sense of Lyapunov. The key idea is that the global intelligent digital redesign problem is viewed as a convex minimization problem of the norm distance between nonlinearly interpolated linear operators to be matched. Sufficient conditions for the global state-matching and the stability of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). A complex nonlinear system, Duffing-like chaotic oscillator is simulated and demonstrated to validate the feasibility and effectiveness of the proposed digital redesign technique, which implies the safe applicability to the digital control system.

Integrated Redesign of Large-Scale Structures by Large Admissible Perturbations

In structural redesign (inverse design), selection of the number and type of performance constraints is a major challenge. This issue is directly related to the computational effort and, most importantly, to the success of the optimization solver in finding a solution. These issues are the focus of this paper, which provides and discusses techniques that can help designers formulate a well-posed integrated complex redesign problem. LargE Admissible Perturbations (LEAP) is a general methodology, which solves redesign problems of complex structures with, among others, free vibration, static deformation, and forced response amplitude constraints. The existing algorithm, referred to as the Incremental Method is improved in this paper for problems with static and forced response amplitude constraints. This new algorithm, referred to as the Direct Method, offers comparable level of accuracy for less computational time and provides robustness in solving large-scale redesign problems in the presence of damping, nonstructural mass, and fluid-structure interaction effects. Common redesign problems include several natural frequency constraints and forced response amplitude constraints at various frequencies of excitation. Several locations on the structure and degrees of freedom can be constrained simultaneously. The designer must exercise judgment and physical intuition to limit the number of constraints and consequently the computational time. Strategies and guidelines are discussed. Such techniques are presented and applied to a 2,694 degree of freedom offshore tower.

Static Stress Redesign of Structures by Large Admissible Perturbations

The LargeE Admissible Perturbation (LEAP) methodology is developed further to solve static stress redesign problems. The static stress general perturbation equation, which expresses the unknown nodal stresses of the objective structure in terms of the baseline structure stresses, is derived first. This equation depends on the redesign variables for each element or group of elements; namely, the cross-sectional area and moment of inertia, and the distance between the neutral axis and the outer fiber of the cross section. This equation preserves the shape of the cross section in the redesign process. LEAP enables the designer to redesign a structure to achieve specifications on modal properties, static displacements, forced response amplitudes, and static stresses. LEAP is implemented in code RESTRUCT which post-processes the FEA results of the baseline structure. Changes on the order of 100% in the above performance particulars and in redesign variables can be achieved without repetitive finite element (FE) analyses. Several numerical applications on a simple cantilever beam and an offshore tower are used to verify the LEAP algorithm for stress redesign.

GA-based intelligent digital redesign of fuzzy-model-based controllers

Intelligent digital redesign involves converting a continuous-time fuzzy-model-based controller into an equivalent discrete-time counterpart for the digital control of continuous-time nonlinear systems by using the Takagi-Sugeno (TS) fuzzy models. In this paper, the authors present a new global state-matching intelligent digital redesign method for nonlinear systems by using genetic algorithms (GAs). More precisely, the intelligent digital redesign problem is converted to an equivalent optimization problem, and then GAs are adopted to find a solution. The search space, in which each problem variable is defined for GAs, are systematically obtained by the interval arithmetic operations. The proposed method results in global matching of the states of the analogously controlled system with those of the digitally controlled system while the conventional intelligent digital redesign method does not. The Chen's chaotic system is used as an illustrative example to show the effectiveness and the feasibility of the developed method. The proposed method provides a new approach for the digital redesign of a class of fuzzy-model-based controllers.

Cognate Space Identification for Forced Response Structural Redesign

Large admissible perturbations (LEAP) is a general methodology, which solves redesign problems of complex structures with, among others, forced response amplitude constraints. In previous work, two LEAP algorithms, namely the incremental method (IM) and the direct method (DM), were developed. A powerful feature of LEAP is the general perturbation equations derived in terms of normal modes, the selection of which is a determinant factor for a successful redesign. The normal modes of a structure may be categorized as stretching, bending, torsional, and mixed modes and grouped into cognate spaces. In the context of redesign by LEAP, the physical interpretation of a mode-to-response cognate space lies in the fact that a mode from one space barely affects change in a mode from another space. Perturbation equations require computation of many perturbation terms corresponding to individual modes. Identifying modes with negligible contribution to the change in forced response amplitude eliminates a priori computation of numerous perturbation terms. Two methods of determining mode-to-response cognate spaces, one for IM and one for DM, are presented and compared. Trade-off between computational time and accuracy is assessed in order to provide practical guidelines to the designer. The developed LEAP redesign algorithms are applied to the redesign of a simple cantilever beam and a complex offshore tower.

Structural Integrity Redesign Through Neural-Network Inverse Mapping

A neural-network inverse mapping approach was used in a structural integrity redesign problem to achieve the desired strength, corrosion, and fatigue properties. Also, through the inverse-mapping procedure the relative importance of damage parameters was obtained for two trained neural-network models. The damage parameters corresponding to a given strength and corrosion rate are predicted in one network, whereas the damage parameters corresponding to a given corrosion fatigue life are predicted in the other network. The results obtained from the inverse mapping procedure are compared with actual panel configurations and environments and experimental data. The results obtained through the inverse-mapping procedure are found to agree well with the experimental data, thus demonstrating the feasibility of the approach for the structural integrity redesign of aging aircraft structures.

Digital redesign of analog controllers based on minimizing integral of squared errors

AbstractDigital redesign is to replace an existing well‐designed analog feedback controller by a digital one along with a sampler and a hold. In this paper, we present a digital redesign technique which takes into account both closed‐loop and intersample behaviour. More precisely, we give a numerical procedure to optimally discretize an analog controller such that the integral of the squared error between the closed‐loop step responses of the analog and digital controlled systems is minimized. A parametric expression is derived for evaluating the integral performance index. With this expression, the optimal digital redesign problem becomes an optimal parameter selection problem which can be solved using existing optimal parameter search algorithms. Moreover, it allows one to obtain optimal reduced‐order digital controllers for sampled‐data control systems over a range of sampling periods. Copyright © 2003 John Wiley & Sons, Ltd.