Optimization Based Design Procedure Research Articles

Robust Output Regulation: Optimization-Based Synthesis and Event-Triggered Implementation

In this article, we investigate the problem of practical output regulation, i.e., to design a controller that brings the system output in the vicinity of a desired target value while keeping the other variables bounded. We consider uncertain systems that are possibly nonlinear and the uncertainty of their linear parts is modeled element wise through a parametric family of matrix boxes. An optimization-based design procedure is proposed that delivers a continuous-time control and estimates the maximal regulation error. We also analyze an event-triggered emulation of this controller, which can be implemented on a digital platform, along with an explicit estimate of the regulation error.

Design optimization of microfluidic-based solvent extraction systems for radionuclides detection

The development of reliable and fast automated methodologies to detect and identify radionuclides during the decommissioning of nuclear power plants is of paramount importance. In this regard, process flowsheeting and computational simulations are useful tools to aid the design and testing of these advanced detection technologies. We implement an optimization based design procedure for the design of continuous analysis systems based on microfluidic solvent extraction and on-line measurement to detect radionuclides in nuclear waste. The optimization of such detection systems is treated as a design under uncertainty problem. The systems are based on thermal lens microscopy as the detection instrument. We demonstrate our approach on a flowsheet for the detection of trivalent lanthanides in organic and aqueous solutions. We highlight the importance of using computer-aided optimization based procedures to design microsystems comprising several chemical operations and their coupling with the detection step. It constitutes a proof of concept and a first step towards robust optimization based modelling approaches for the design of microfluidic lab-on-a-chip platforms for the detection of radionuclides in nuclear waste.

Antenna Aperture Synthesis Using Mode-Converting Metasurfaces

Mode-converting metasurfaces are passive, lossless devices that can be designed to transform a set of incident modes to a desired set of transmitted modes. In this paper, mode-converting metasurfaces are utilized to synthesize arbitrary, azimuthally-invariant TM apertures. The methods presented in this work can be used to design antennas that can meet specific near-field and far-field criteria unlike most metasurfaces which solely manipulate the far field. The proposed antennas consist of a coaxially-excited, radial cavity topped by the mode-converting metasurface. The main role of the mode-converting metasurface is to establish the desired aperture by converting the modal distribution of the excitation to that of desired aperture. Its secondary role is to impedance match the coaxial feed to the radial cavity. Using modal network theory, an optimization-based design procedure is developed to synthesize the proposed metasurface antennas. The admittance profiles of the electric sheets that comprise the metasurface are optimized to establish the desired aperture profile. To illustrate the design procedure, a radial Gaussian beam antenna is synthesized at 10 GHz and its performance is verified using a full wave electromagnetic solver. The proposed antenna has a height and weight advantage over Gaussian beam horn antennas.

Interval observers for LPV systems and application to the guaranteed state estimation of an induction machine

The scope of this paper is the design of interval observers for linear parameter-varying systems subject to input and output uncertainties. To this, two coupled dynamical systems are designed which compute an upper bound and a lower bound of the state which enclose the real value with a bounded interval width. Besides of a full-order interval observer, a reduced-order interval observer is proposed to reduce the computational effort. In addition to sufficient conditions and the mathematical description of the interval observers, an optimization-based design procedure for their practical application is presented. The performance of the interval observers is shown by the guaranteed state estimation of an induction machine.

Fixed-order decentralized/distributed control of islanded inverter-interfaced microgrids

This paper focuses on the problem of voltage control of islanded inverter-interfaced microgrids consisting of several distributed generation (DG) units with radial structure. The main objectives are to (i) design a decentralized/distributed voltage controller with minimum information exchange between DG units and their local controllers (ii) design a fixed-/low-order dynamic output feedback controller which ensures stability as well as desired performance of the microgrid system in spite of load parameter uncertainties. To this end, the problem is formulated as an optimization problem which is the minimization of the cardinality of a pattern matrix subject to an H∞ performance constraint. Since the problem is intrinsically non-convex, a convex optimization-based design procedure for the controller synthesis is proposed in this paper. The effectiveness of the proposed controller is evaluated through simulation studies and Hardware-In-the-Loop (HIL) verifications. The simulation and experimental results demonstrate the effectiveness of the proposed control strategy.

Topology optimization-based lightweight primary mirror design of a large-aperture space telescope.

For the large-aperture space telescope, the lightweight primary mirror design with a high-quality optical surface is a critical and challenging issue. This work presents a topology optimization-based design procedure for a lightweight primary mirror and a new mirror configuration of a large-aperture space telescope is obtained through the presented design procedure. Inspired by the topology optimization method considering cast constraints, an optimization model for the configuration design of the mirror back is proposed, through which the distribution and the heights of the stiffeners on the mirror back can be optimized simultaneously. For the purpose of minimizing the optical surface deviation due to self-weight and polishing pressure loadings, the objective function is selected as to maximize the mirror structural stiffness, which can be achieved by minimizing the structural compliance. The total mass of the primary mirror is assigned as the constraint. In the application example, results of the optimized design topology for two kinds of mass constraints are presented. Executing the design procedure for specific requirements and postprocessing the topology obtained of the structure, a new mirror configuration with tree-like stiffeners and a multiple-arch back in double directions is proposed. A verification model is constructed to evaluate the design results and the finite element method is used to calculate the displacement of the mirror surface. Then the RMS deviation can be obtained after fitting the deformed surface by Zernike polynomials. The proposed mirror is compared with two classical mirrors in the optical performance, and the comparison results demonstrate the superiority of the new mirror configuration.

Frequency domain design of fractional order PID controller for AVR system using chaotic multi-objective optimization

A fractional order (FO) PID or FOPID controller is designed for an Automatic Voltage Regulator (AVR) system with the consideration of contradictory performance objectives. An improved evolutionary Non-dominated Sorting Genetic Algorithm (NSGA-II), augmented with a chaotic Henon map is used for the multi-objective optimization based design procedure. The Henon map as the random number generator outperforms the original NSGA-II algorithm and its Logistic map assisted version for obtaining a better design trade-off with an FOPID controller. The Pareto fronts showing the trade-offs between the different design objectives have also been shown for both the FOPID controller and the conventional PID controller to enunciate the relative merits and demerits of each. The design is done in frequency domain and hence stability and robustness of the design is automatically guaranteed unlike the other time domain optimization based controller design methods.

Distributed model predictive control based on agent negotiation

Abstract In this paper we consider the control of several subsystems coupled through the inputs by a set of independent agents that are able to communicate. We assume that each agent has access only to the model and the state of one of the subsystems. This implies that in order to take a cooperative decision, the agents must negotiate. At each sampling time agents make proposals to improve an initial feasible solution on behalf of their local cost function, state and model. These proposals are accepted if the global cost improves the cost corresponding to the current solution. In addition, we provide conditions that guarantee that the closed-loop system is asymptotically stable along with an optimization based design procedure that is based on the full model of the system. Finally, the proposed scheme is put to test through simulation.

An optimization-based design procedure for asymmetric bidirectional associative memories

In this letter, we consider the problem of designing asymmetric bidirectional associative memories (ABAM). Based on a newly derived theorem for the ABAM model, we propose an optimization-based design procedure for obtaining an ABAM that can store given bipolar vector pairs with certain error correction properties. Our design procedure consists of generalized eigenvalue problems, which can be efficiently solved by recently developed interior point methods. The validity of the proposed method is illustrated by a design example.

An Optimization Based Design Procedure for Biochemical Processes: Part I: Preliminary Design and Operation

A two stage optimization based design procedure for biochemical processes is presented. In the first stage, the processing rates and conditions of the unit operations and equipment capacities are determined through dynamic optimization, while simple scheduling considerations are accounted for. The second stage deals with detailed scheduling and design adjustments, required for an accurate determination of the sequence and timing of the unit operations, using the processing rates from the first stage. A scheduling model is developed to take account of batch integrity and is described in the second part of this paper. The design procedure is demonstrated using an example of a process common in the biochemical industries. The production of an intra-cellular enzyme requires a fermentation stage (or stages) followed by a number of primary separation stages, with high resolution steps for final purification. In this example the process is considered up to and including the primary separation stages only. The process consists of nine stages including four typical unit operations.

An Optimization Based Design Procedure for Biochemical Processes: Part II: Detailed Scheduling

The first part of this paper presented an overall approach to optimization based design of biochemical processes. The procedure is divided into two stages. In the first stage (described in part I of this paper1), the processing rates and conditions of the unit operations and equipment capacities are determined through dynamic optimization, while simple scheduling considerations are accounted for. The second stage, described here, deals with detailed scheduling and design adjustments, required for an accurate determination of the sequence and timing of the unit operations, using the processing rates from the first stage. A scheduling model is developed to take account of batch integrity. The design procedure is demonstrated using an example of a process common in the biochemical industries.

Nonlinear control of constrained linear systems

This paper addresses the problem of obtaining nonlinear state-feedback controllers for controlling constrained dynamic systems, a problem which is, perhaps, the most important outstanding problem in control design. A novel off-line, optimization-based design procedure is employed; the control law is constructed from the solution to a finite number of optimal open-loop control problems. The design procedure permits relatively simple modification and improvement to the control law to be made in those regions of the state-space in which simulation reveals deficiencies. This potential for incremental improvement constitutes an important advantage over alternative methods. The results are relevant when high performance is required of systems subject lo constraints on controls and states.