Set Of Performance Specifications Research Articles

Introducing an efficiency index to evaluate eVTOL designs

The evolution of electric vertical takeoff and landing (eVTOL) aircraft as part of the Advanced Air Mobility initiative will affect our society and the environment in fundamental ways. Technological forecasting suggests that commercial services are fast emerging to transform urban and regional air mobility for people and cargo. However, the complexities of diverse design choices pose a challenge for potential adopters or service providers because there are no objective and simple means to compare designs based on the available set of performance specifications. This analysis defines an aeronautically informed propulsion efficiency index (PEX) to compare the performance of eVTOL designs. Range, payload ratio, and aspect ratio are the minimum set of independent parameters needed to compute a PEX that can distinguish among eVTOL designs. The distribution of the PEX and the range are lognormal in the design space. There is no association between PEX values and the mainstream eVTOL architecture types or the aircraft weight class. A multilinear regression showed that the three independent parameters explained >90 % of the PEX distribution in the present design space.

Fast and reliable knowledge-based design closure of antennas by means of iterative prediction-correction scheme

PurposeA novel framework for expedited antenna optimization with an iterative prediction-correction scheme is proposed. The methodology is comprehensively validated using three real-world antenna structures: narrow-band, dual-band and wideband, optimized under various design scenarios.Design/methodology/approachThe keystone of the proposed approach is to reuse designs pre-optimized for various sets of performance specifications and to encode them into metamodels that render good initial designs, as well as an initial estimate of the antenna response sensitivities. Subsequent design refinement is realized using an iterative prediction-correction loop accommodating the discrepancies between the actual and target design specifications.FindingsThe presented framework is capable of yielding optimized antenna designs at the cost of just a few full-wave electromagnetic simulations. The practical importance of the iterative correction procedure has been corroborated by benchmarking against gradient-only refinement. It has been found that the incorporation of problem-specific knowledge into the optimization framework greatly facilitates parameter adjustment and improves its reliability.Research limitations/implicationsThe proposed approach can be a viable tool for antenna optimization whenever a certain number of previously obtained designs are available or the designer finds the initial effort of their gathering justifiable by intended re-use of the procedure. The future work will incorporate response features technology for improving the accuracy of the initial approximation of antenna response sensitivities.Originality/valueThe proposed optimization framework has been proved to be a viable tool for cost-efficient and reliable antenna optimization. To the knowledge, this approach to antenna optimization goes beyond the capabilities of available methods, especially in terms of efficient utilization of the existing knowledge, thus enabling reliable parameter tuning over broad ranges of both operating conditions and material parameters of the structure of interest.

Nested Kriging with Variable Domain Thickness for Rapid Surrogate Modeling and Design Optimization of Antennas

Design of modern antennas faces numerous difficulties, partially rooted in stringent specifications imposed on both electrical and field characteristics, demands concerning various functionalities (circular polarization, pattern diversity, band-notch operation), but also constraints imposed upon the physical size of the radiators. Conducting the design process at the level of full-wave electromagnetic (EM) simulations, otherwise dictated by reliability, entails considerable computational expenses, which is another and a serious challenge. It is especially pronounced for the procedures involving repetitive EM analyses, e.g., parametric optimization. Utilization of fast surrogate models as a way of mitigating this issue has been fostered in the recent literature. Unfortunately, construction of reliable surrogates for antenna structures is hindered by their highly nonlinear responses and even more by the utility requirements: design-ready models are to be valid over wide ranges of operating conditions and geometry parameters. Recently proposed performance-driven modeling, especially the nested kriging framework, addresses these difficulties by confining the surrogate model domain to a region that encapsulates the designs being optimum with respect to the relevant figures of interest. The result is a dramatic reduction of the number of training samples needed to render a usable model. This paper introduces a variable-thickness domain, which is an important advancement over the basic nested kriging. The major benefit demonstrated using two antenna examples is a further and significant (up to seventy percent) reduction of the training data acquisition cost. It is achieved while ensuring that the model domain covers the regions containing optimum designs for various sets of performance specifications.

Accelerated design optimization of miniaturized microwave passives by design reusing and Kriging interpolation surrogates

Electromagnetic (EM) analysis has become ubiquitous in the design of microwave components and systems. One of the reasons is the increasing topological complexity of the circuits. Their reliable evaluation—at least at the design closure stage—can no longer be carried out using analytical or equivalent network representations. This is especially pertinent to miniaturized structures, where considerable EM cross-coupling effects occurring in densely arranged layouts affect the performance in a non-negligible manner. Although mandatory, EM-driven design is normally associated with significant computational expenses. Consequently, expediting the procedures that require massive simulations, such as parametric optimization, is a practical necessity. In this paper, a framework for accelerated parameter tuning is proposed. The keystones of our methodology are a set of pre-existing designs optimized for various design objectives, as well as kriging interpolation surrogates. The latter are constructed to yield—for a given set of performance specifications—a reasonably good starting point and to enable rapid optimization by providing the initial approximation of the Jacobian matrix of the circuit outputs. The proposed approach is validated using two compact impedance matching transformers designed within the objective spaces defined by wide ranges of operating bandwidths. As demonstrated, the average tuning cost corresponds to a few EM simulations of the respective circuit despite large numbers of adjustable parameters.

Expedited Dimension Scaling of Microwave and Antenna Structures Using Inverse Surrogates

Re-designing circuits for various sets of performance specifications is an important problem in microwave and antenna engineering. Unfortunately, this is a difficult task that is normally realized as a separate design process, which is often as expensive (in computational terms) as obtaining the original design. In this work, we consider the application of inverse surrogate modeling for fast geometry scaling of microwave and antenna structures. Computational efficiency of the discussed procedure is ensured by representing the structure at the low-fidelity model level. The explicit relation between design specifications (here, operating frequency) of the structure and its geometry dimensions is determined based on a set of predetermined reference designs. Subsequently, the model is corrected to elevate the re-designed geometry to the high-fidelity electromagnetic (EM) model level. Our approach is demonstrated through a compact rat-race coupler and a patch antenna with enhanced bandwidth.

Design of robust fractional-order controllers and prefilters for multivariable system using interval constraint satisfaction technique

Design of robust controller for multivariable systems is very challenging and their automation is a key concern in control system design. In this paper, a new, simple, and reliable automated fractional-order multivariable Quantitative Feedback Theory (QFT) controllers design methodology is proposed. A fixed structure fractional-order multivariable QFT controller has been synthesized by solving QFT quadratic inequalities of robust stability and tracking specifications. The quadratic inequalities (constraints) are posed as Interval Constraint Satisfaction Problem (ICSP). The constraints are solved by constraint solver-RealPaver. The synthesis problem consists of obtaining a controller that ensures stability and meets a given set of performance specifications, in spite of disturbance and model uncertainties. In addition to perform the above tasks, a MIMO controller also has to perform the difficult task of minimizing interaction between the various control loops. Unlike existing manual or convex optimization based QFT design approaches, the proposed method gives a controller which meets all performance requirements in QFT, without going through the conservative and sequential design stages for each of the multivariable sub-systems. In the design method, we pose the prefilter design problem as an ICSP and solve it using the well-established constraint solver. The designed controllers and prefilters are tested for a quadruple tank process and their efficacy is demonstrated.

Automated synthesis of multivariable QFT controller using interval constraint satisfaction technique

Robust controller synthesis of Multi-Input–Multi-Output (MIMO) systems is of great practical interest and their automation is a key concern in control system design. The synthesis problem consists of obtaining a controller that ensures stability and meets a given set of performance specifications, in spite of the disturbance and model uncertainties. In addition to perform the above tasks, a MIMO controller also has to perform the difficult task of minimizing the interaction between the various control loops.Unlike existing manual or convex optimization based Quantitative Feedback Theory (QFT) design approaches, the proposed method gives a controller which meets all performance requirements in QFT, without going through the conservative and sequential design stages for each of the multivariable sub-systems. In this paper, a new, simple, and reliable automated MIMO QFT controllers design methodology is proposed. A fixed structure MIMO QFT controller has been synthesized by solving QFT quadratic inequalities of robust stability and tracking specifications. The quadratic inequalities (constraints) are posed as Interval Constraint Satisfaction Problem (ICSP). The constraints are solved by constraint solver — RealPaver. The main feature of this method is that the algorithm finds all the solutions to within the user-specified accuracy. The designed MIMO QFT controllers are tested on the experimental setup designed by Educational Control Product (ECP) Magnetic Levitation Setup ECP 730. From the experimental results presented, it is observed that, the designed controller satisfies the desired performance specifications. It is also observed that, the interactions between the loops are within the specified limits. The robustness of the designed controllers are verified by putting extra weights on the magnets.

An Application of the Individual Channel Analysis and Design Approach to Control of a Two-input Two-output Coupled-tanks System

Frequency-domain methods have provided an established approach to the analysis and design of single-loop feedback control systems in many application areas for many years. Individual Channel Analysis and Design (ICAD) is a more recent development that allows neo-classical frequency-domain analysis and design methods to be applied to multi-input multi-output control problems. This paper provides a case study illustrating the use of the ICAD methodology for an application involving liquid-level control for a system based on two coupled tanks. The complete nonlinear dynamic model of the plant is presented for a case involving two input flows of liquid and two output variables, which are the depths of liquid in the two tanks. Linear continuous proportional plus integral controllers are designed on the basis of linearised plant models to meet a given set of performance specifications for this two-input two-output multivariable control system and a computer simulation of the nonlinear model and the controllers is then used to demonstrate that the overall closed-loop performance meets the given requirements. The resulting system has been implemented in hardware and the paper includes experimental results which demonstrate good agreement with simulation predictions. The performance is satisfactory in terms of steady-state behaviour, transient responses, interaction between the controlled variables, disturbance rejection and robustness to changes within the plant. Further simulation results, some of which involve investigations that could not be carried out in a readily repeatable fashion by experimental testing, give support to the conclusion that this neo-classical ICAD framework can provide additional insight within the analysis and design processes for multi-input multi-output feedback control systems.

Integrated design & control of a buck boost converter

This paper presents the integrated design and control of a buck boost converter (BBC). In the proposed methodology the design tool provides simultaneously the controller tuning and BBC design parameters in such a way that some closed-loop pre-specified static and dynamic behavior is obtained. This approach contrasts with the traditional methodology, where the design of BBC is performed without taking into account its dynamical behavior. An optimization procedure is used to obtain the electronic components of the BBC and the tuning parameters of the controller, minimizing an objective function that considers the set of performance specifications. Although the methodology can be applied to any converter and any control strategy, in this particular case an ideal BBC and a Sliding Model Control (SMC) strategy are used. Some simulation results show the advantages and principally the flexibility that can be obtained with this approach.

A study of convergence and mapping in preliminary vehicle design

In this paper, we investigate the issue of convergence in multi-objective optimisation problems developed for vehicle analyses when using a Multi-Objective Genetic Algorithm (MOGA) to determine the set of Pareto optimal automobile configurations. Additionally, given a Pareto set for a multi-objective problem, the mapping between the performance and design space is studied to determine new automobile design configurations for a given set of performance specifications. The advantage of this study is that the automobile's design information is obtained without having to repeat system analyses. The tools developed in this paper are applied both to a simple multi-objective optimisation problem to illustrate the methodology and to a preliminary vehicle design framework to develop a Technical Feasibility Model (TFM) for use in the early stages of automobile design.

Multiobjective process controllability analysis

A new approach for process controllability analysis by using multiobjective optimisation techniques is proposed. Within the approach, a set of performance specifications, such as minimum control error and input effort with closed-loop pole placement are represented as a set of linear matrix inequalities (LMI). The solution to the LMI conditions can be identified as feasible or infeasible. If the solution is feasible there is at least one controller that can make the closed-loop system satisfy all performance specifications simultaneously. Therefore, for the process plant, these performance specifications are achievable. Otherwise, they are unachievable. There is a Pareto-optimal set or a trade-off curve in the performance space to separate these two areas. The paper shows that such trade-off curves can be used for process controllability analysis, and therefore, can be applied to control structure selection problems.

A method for analog circuit design that stores and reuses design procedures

AbstractThis paper proposes a new design methodology that improves the efficiency of analog circuit design. In the conventional design environment, designers try to enhance design productivity by storing designed circuits in a library for future reuse. However, a fixed circuit stored in a library is optimized to a particular set of performance specifications; and, hence, its reusability is low.By contrast, the proposed methodology stores not only designed results but also design methods that show how to design circuits. When different sets of specifications are required, circuits are designed automatically based on the stored design methods, which improves design efficiency.To evaluate the proposed design methodology, a method is devised that automatically stores a design procedure from the design process of a human designer and reuses it for circuit analysis. A prototype design system that realizes it is implemented. Experimental results on the design of an operational amplifier show the effectiveness of the proposed methodology.

STAIC: an interactive framework for synthesizing CMOS and BiCMOS analog circuits

STAIC is an interactive design tool that synthesizes CMOS and BiCMOS analog integrated circuits that conform to specified performance constraints. STAIC features an input modeling language for entering hierarchical circuit descriptions and a symbolic/numeric solve unit that dynamically integrates analytical model equations across hierarchical boundaries. The output of the solver is a flattened homogeneous model that is customized to a user-specified topology and set of performance specifications. The output is thus tailored for optimization and other numerically intense design exploration procedures. All model descriptions include physical layout so that important net parasitics may be fully accounted for during design evaluation. Synthesis proceeds via a successive solution refinement methodology. Multilevel models of increasing sophistication are used by scan and optimization modules to converge to what is likely a globally optimal solution. Design experiments have shown that STAIC can produce satisfactory results.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Instructional leadership specifications for school executives: A preliminary validation study

A set of performance specifications relating to instructional leadership for superintendents and their assistants is being developed at the University of Texas at Austin under the auspices of the American Association of School Administrators, and with initial funding from the Meadows Foundation. These specifications are part of a more comprehensive array being developed to guide and give focus to AASA’s new National Executive Development Center projected for full-scale implementation in the 1990s across the United States. Based on the performance specifications developed in the instructional leadership domain, a diagnostic assessment system has been designed and has been field tested using over 250 school executives. The system design and the performance specifications are being evaluated in use, representing one of the first offering diagnostic assessment services.

Client requirements for real-time communication services

A set of performance specifications that seem appropriate for real-time computer communication services is proposed. They include various types of delay bounds, throughput bounds, and reliability bounds. Other requirements and desirable properties are described from a client's viewpoint, and the ways in which each requirement is to be translated to make it suitable for lower levels in the protocol hierarchy are examined. Some examples of requirements specification are presented, and possible objections to the approach are discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Operational-amplifier compilation with performance optimization

A method for designing analog circuits in which topological design is followed by simultaneous device sizing and layout design is described. By merging circuit and layout design into a single design process, analog circuits can be optimally designed taking layout parasitics fully into account. Using the method, a CMOS operational-amplifier compiler (OAC) has been developed. Given a set of performance specifications and process parameters, OAC generates a layout with circuit performance optimized to meet specified performance constraints. A procedural layout technique is employed to generate a compact and practical layout. A nonlinear optimization method for device sizing which relies on the results of simulations based on the circuit extracted from the layout is applied. Design experiments have shown that OAC can produce satisfactory results with respect to both circuit performance and layout density. >

Self-reconstructing technique for expert system-based analog IC designs

The flexible-architecture approach to expert-system-based analog IC designs is presented. The self-reconstructing technique which uses circuit primitives as replacement parts in a design is described. The expert system used is capable of making an intelligent initial choice among circuits of fixed architecture as well as reconstructing the selected circuit to better satisfy a given set of performance specifications. Software implementation and experimental results are shown to demonstrate the power of the approach.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Robust compliant motion for manipulators, part II: Design method

A controller design methodology to develop a robust compliant motion for robot manipulators is described. The achievement of the target dynamics (the target impedance is introduced in Part I) and preservation of stability robustness in the presence of bounded model uncertainties are the key issues in the design method. State-feedback and force-feedforward gains are chosen to guarantee the achievement of the target dynamics, while preserving stability in the presence of the model uncertainties. In general, the closed-loop behavior of a system cannot be shaped arbitrarily over an arbitrarily wide frequency range. It is proved that a special class of impedances that represent our set of performance specifications are mathematically achievable asymptotically through state-feedback and interaction-force feedforward as actuator bandwidths become large, and we offer a geometrical design method for achieving them in the presence of model uncertainties. The design method reveals a classical trade-off between a system's performance over a bounded frequency range and its stability relative to model uncertainties via multivariable Nyquits criteria. Two classes of such uncertainties are dealt with. While the first class of model uncertainties is formed from the uncertainties in the parameters of the modeled dynamics, the high-frequency unmodeled dynamics form the second class of model uncertainties. The multivariable Nyquist criterion is used to examine trade-offs in stability robustness against approximation of desired target impedances over bounded frequency ranges.

Design of a longitudinal ride-control system by Zakian's method of inequalities

In this paper, Zakian's method of inequalities is applied to the design of a ride-control system for a STOL aircraft. The purpose of the controller is to reduce the normal acceleration experienced by both passengers and crew. The method is based on the synthesis of a controller such that a set of performance specifications and constraints is satisfied. Controllers are designed on the basis of the characteristics of both the closed-loop step response and the closed-loop error response. It is shown that the design of a single-input, single-output controller by the method of inequalities is straightforward, and can be achieved by using a sequence of formulations until the designer is satisfied that no further improvement is necessary.

Optimum synthesis of non-minimum phase feedback systems with plant uncertainty†

Linear time-invariant feedback systems in which the constrained plant transfer function has right half-plane zeros, are perforce non-minimum-phase, and their attainable benefits of feedback are inherently restricted. This paper presents criteria for determining whether a given set of performance specifications are achievable and, if so, a synthesis procedure is included for deriving the optimum design, defined as that with an effectively minimum loop transmission bandwidth. The properties of the optimum design are derived and its uniqueness proven, for both the minimum and non-minimum-phase feedback systems.