MATLAB Optimization Toolbox Research Articles

CONTROLLER TUNING FOR DISTURBANCE REJECTION ASSOCIATED WITH DELAYED DOUBLE INTEGRATING PROCESSES, PART II: I-PD CONTROLLER

An I-PD controller is investigated for disturbance rejection associated with delayed double integrating processes. The controller is tuned using the MATLAB optimization toolbox and five different error-based objective functions for process time delay between 0.1 and 5 s. The more suitable objective function for disturbance rejection with the I-PD controller used with the delayed double integrating process is assigned and the effect of the process time delay on the performance of the control system in the time domain is shown. The unit step disturbance input time response of the control system has a maximum value less than 0.431, time of maximum time response less than 1.01 s and a settling time less than 15 s for time delay ≤ 1 s. The simulation results using the I-PD controller are superior when compared with other disturbance rejection techniques based on using PD-PI and PIDF controllers.

PPI CONTROLLER TUNING FOR USE WITH A HIGHLY OSCILLATING SECONDORDER-LIKE PROCESS

A PPI controller is investigated for set-point tracking associated with a highly oscillating secondorder-like process. The controller is tuned using the MATLAB optimization toolbox and five different errorbased objective functions. All the objective functions result in a same time response of the closed-loop control system to a unit step input. The unit step reference input time response of the control system has a zero maximum overshoot and a settling time of 16 seconds. It has an oscillatory nature for a response time up to 10 seconds. The simulation results using the PPI controller are compared with using I-PD, PD-PI, PIPD, PID + first-order lag and PID controllers. The PPI can compete with I-PD, PD-PI and PI-PD controllers regarding the maximum percentage overshoot. However, it cannot compete with all the other five controllers regarding the settling time.

Development of an HTS Magnet for Ultra-Compact MRI System: Optimization Using Genetic Algorithm (GA) Method

© 2002-2011 IEEE. This paper presents the design of an HTS magnet for an ultra compact MRI system, potentially for the rapid and early diagnosis of brain trauma. Early diagnosis and therapy stratification can reduce the risk for critically brain ill patients with the use of near patient imaging, and can aid with precision medicine. High temperature superconductors (HTS) have the ability to carry large currents in the cryogen free contrition, which can make the MRI system even smaller and lighter. The design and Genetic Algorithm (GA) optimization were based on the FEM package COMSOL Multiphysics with the LiveLink for MATLAB, together with the GA module in the MATLAB optimization toolbox. The relatively thick HTS tape, ST-12-L from the Shanghai Superconductor Technology was chosen and that made more difficulty on optimization process. Genetic Algorithm method improved the optimization performance, and the uniformity achieved 2.36 ppm in a 10 × 10 × 10 cm DSV. Two cases of the end double-pancake were compared. Further sensitivity studies were performed on the homogeneity with its relationship to the magnet length, and the thickness of HTS tape.

Application of resistance energy model to optimising electric power consumption of a belt conveyor system

Driven by constantly increasing energy demands, prices, environmental impact caused by carbon dioxide emissions and global warming, efficient use of energy is gaining grounds in both public and private enterprises. The energy consumption of belt conveyors can be lowered using energy modelling techniques. In this research, 
 a resistance-based mathematical energy model was utilised in 
 the electrical energy efficiency optimisation of the troughed, inclined belt conveyor system taking into account indentation rolling resistance, bulk solid flexure resistance and secondary resistance as they together contribute 89% resistance to motion. An optimisation problem was formulated to optimise the electrical energy efficiency of the belt conveyor system and subsequently solved using 
 the “fmincon” solver and interior point algorithm of the MATLAB optimisation toolbox. Analysis of simulation results showed that for the same given operating capacities, an average energy saving of about 7.42% and an annual total cost savings of Gh¢ 5, 852, 669.00 (USD 1, 083, 827.59) for a 2592-hour operation can be achieved when the used model and optimisation technique are employed over the constant speed operation.

Minimization of aircraft fuel consumption subjected to arrival time constraint

PurposeThis paper aims to minimize aircraft fuel consumption during the cruise phase when the flight is subjected to a specific time of arrival for different weights and distances.Design/methodology/approachThe approach adopted herein uses sequential quadratic programming algorithm from MATLAB optimization toolbox, which includes a mathematical model of a jet airliner based on the Base of Aircraft Data as a function evaluator, to find out the impact of meet-time of arrival constraints on fuel consumption. The cruising speeds at predefined segments and the altitude are defined as the design variables.FindingsThe algorithm determines the optimum cruise altitudes and speeds for minimum fuel consumption in the case of no time constraints, also, for different time constraints where the flight time shall be reduced by increasing speed and lowering the altitude in most of the investigated cases.Practical implicationsThe algorithm computes the optimum speed and the altitude according to different flight scenarios with the meet-time of arrival constraints for minimum fuel consumption which affects the direct operating cost of the flight. The algorithm might greatly help in decision-making for the meet-time of arrival operations.Originality/valueDeveloping an algorithm to optimize the speed and the altitude of an aircraft based on weight and range for minimization of fuel consumption. It is a pioneer study in the literature that deals with the effect of meet-time constraints on fuel consumption.

Reconstruction of the thermal properties in a wave-type model of bio-heat transfer

Purpose This study aims to at numerically retrieve five constant dimensional thermo-physical properties of a biological tissue from dimensionless boundary temperature measurements. Design/methodology/approach The thermal-wave model of bio-heat transfer is used as an appropriate model because of its realism in situations in which the heat flux is extremely high or low and imposed over a short duration of time. For the numerical discretization, an unconditionally stable finite difference scheme used as a direct solver is developed. The sensitivity coefficients of the dimensionless boundary temperature measurements with respect to five constant dimensionless parameters appearing in a non-dimensionalised version of the governing hyperbolic model are computed. The retrieval of those dimensionless parameters, from both exact and noisy measurements, is successfully achieved by using a minimization procedure based on the MATLAB optimization toolbox routine lsqnonlin. The values of the five-dimensional parameters are recovered by inverting a nonlinear system of algebraic equations connecting those parameters to the dimensionless parameters whose values have already been recovered. Findings Accurate and stable numerical solutions for the unknown thermo-physical properties of a biological tissue from dimensionless boundary temperature measurements are obtained using the proposed numerical procedure. Research limitations/implications The current investigation is limited to the retrieval of constant physical properties, but future work will investigate the reconstruction of the space-dependent blood perfusion coefficient. Practical implications As noise inherently present in practical measurements is inverted, the paper is of practical significance and models a real-world situation. Social implications The findings of the present paper are of considerable significance and interest to practitioners in the biomedical engineering and medical physics sectors. Originality/value In comparison to Alkhwaji et al. (2012), the novelty and contribution of this work are as follows: considering the more general and realistic thermal-wave model of bio-heat transfer, accounting for a relaxation time; allowing for the tissue to have a finite size; and reconstructing five thermally significant dimensional parameters.

Trajectory Optimization for a Connected Automated Traffic Stream: Comparison Between an Exact Model and Fast Heuristics

Numerous fast heuristic algorithms, including shooting heuristics (SH), have been developed for real-time trajectory optimization, although their optimality has not yet been quantified. This paper compares the performance between fast heuristics and exact optimization models. We investigate a core trajectory optimization problem as a building block for numerous trajectory optimization problems, i.e., guiding movements of connected automated vehicles on a one-lane highway when the arrival and departure times and velocity are given. To apply the SH algorithm to this problem, we adapt it to a fast-simplified shooting heuristic (FSSH) model to solve the trajectory smoothing problems with different arrival and departure velocities. An exact trajectory optimization (ETO) model is formulated that takes the vehicle position and velocity as the decision variables, and the fuel consumption and driving comfort as the objective function. The constraints of the model are based on the limits and safety of the vehicle dynamics between consecutive vehicles. We demonstrate the convexity of the ETO objective function, ensuring the solvability of the ETO model at the true optimum using gradient descent algorithms supplied by the MATLAB optimization toolbox. Six groups of numerical experiments using different input parameters and one experiment using real Next Generation Simulation (NGSIM) data are conducted. ETO can improve the objective values by a few to tens of percentage points. However, FSSH achieves a greater solution efficiency with an average solution time of less than 0.1 s compared to ~450 s for ETO.

Simulation of PMSM Operating at Different Speeds and Optimization of PI Controller Parameters

This study aims to contribute to design and development studies by investigating current, speed and torque responses of permanent magnet synchronous motor (PMSM) with different loads and powers without any experimental study. For this reason, firstly, PMSM was simulated using Matlab/Simulink package program. The simulation results were then tested using a 0.25 kW PMSM coded MCS06C41, a motor driver coded EVS9322-ESV004, and the Global Drive Control interface program produced by Lenze. In addition, the model was tested on another PMSM (1.1 kW) to determine the validity of the model. Since the driver used during the experiment was designed according to field-oriented vector control, the field-oriented vector control was also preferred in the simulation. The PI controller parameters in driver simulation were optimized by using the Signal Constraint Block in Simulink Response Optimization toolbox of Matlab.

Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle Time

This paper presents a framework for optimizing injection molding process parameters for minimum product cycle time subjected to constraints on the product defects. Two product defects, namely, volumetric shrinkage and warpage, as well as seven process parameters including injection speed, injection pressure, cooling time, packing pressure, mold temperature, packing time, and melt temperature, were considered. Injection molding experiments were conducted on specifically chosen test points and results were used to compute the volumetric shrinkage and warpage (at each test point). Thereafter, three relationships between the product cycle time (one relationship), the two product defects (two relationships), and the injection molding parameters were constructed using the kriging technique. An optimization problem to minimize the product cycle time (described by the first relationship) subject to constraints on the product defects (described by the latter two relationships) was then formulated. A combination set of points between the lower and upper extreme values of acceptable product defect was generated to serve as constraints for the two product defects. The optimization problem was then solved using the Fmincon function, available in the Matlab optimization toolbox. A plot of the optimization results revealed an appreciable tradeoff between the cycle time and the two product defects. To validate the optimization, an additional injection molding experiment was conducted for one of the optimization results. Results from the additional experiment showed reasonably close agreement with simulation optimization results differing in the cycle time, the warpage and volumetric shrinkage by 6.7%, 3.2%, and 8%, respectively.

Inter-trip links incorporated optimal protection coordination

Due to advances in smart grid, different communication links as delay, inter-trip and activation are used between relays to enhance the protection system performance. In this paper, the effect of inter-trip links on optimal coordination of directional overcurrent relays (DOCRs) is analytically investigated and modelled. Moreover, an index is proposed to find the optimum locations for inter-trip link installation to reach the minimal fault clearance times under the selectivity constraint. Then a method is proposed to determine the candidate locations of inter-trip links and the associated reduced operating times. An Exhaustive search approach is also used to validate the efficiency of the proposed method. The method is simulated and tested on distribution network of IEEE 33 bus using the Power Factory software and MATLAB optimization toolbox. Genetic algorithm is used as an optimization tool to find optimal settings of relays. The results indicate the capability of proposed method in optimal protection coordination with optimum inter-trips.

Study of AA-1050 sheet metal parts processed by single point incremental forming with dummy sheet

The present paper describes an experimental study of AA-1050 sheet metal part processed by single point incremental forming (SPIF) with dummy sheet. Influence of process parameters namely step-down size, tool size, feed rate, dummy sheet thickness and forming angle on surface roughness of formed part is investigated. From the analysis of results, it is observed that step-down size, tool size, dummy sheet thickness and forming angle are significant process parameter and feed rate is insignificant. Surface roughness decreases with increase in tool size, dummy sheet thickness and forming angle; while it increases with increase in step-down size. Based on experimentation and analysis of results, a mathematical model to predict surface roughness is developed. Further, optimisation is performed on the basis of desirability function to minimise surface roughness. Also, optimisation algorithm namely genetic algorithm and simulated annealing available in MATLAB optimisation tool box is applied to find out the optimum surface roughness. Experimental results are found to be in good agreement with results predicted by the developed mathematical model.

Implementation of Decentralized Control Scheme to Control a MIMO System using Response Optimization Toolbox in MATLAB

In this paper, Model based approach is implemented to control a heat exchanger prototype using optimization technique for parameter tuning of PID controller. Mathematical modelling of heat exchanger is done using mechanical specifications and differential equations of “Shell and Tube heat exchanger”. Optimally tuned PID controller is used to control the process model. Output response of optimal PID controlled model is compared with ordinary PID controlled model’s output response in results. Response optimization technique is implemented in this process to tune the parameters of the PID controller. It makes the response as a settled one on the desired value and also gives the stable response.

General Parameter Identification Procedure and Comparative Study of Li-Ion Battery Models

Accurate and robust battery models are required for the proper design and operation of battery-powered systems. However, the parametric identification of these models requires extensive and sophisticated methods to achieve enough accuracy. This article shows a general and straightforward procedure, based on Simulink and Simscape of Matlab, to build and parameterize Li-ion battery models. The model parameters are identified with the Optimization Toolbox of Matlab, by means of an iterative process to minimize the sum of the squared errors. In addition, this procedure is applied to a selection of five different models available in the literature for electric vehicle applications, obtaining a comparative study between them. Also, the performance of each battery model is evaluated through two current profiles from two driven profiles known as the Urban Driving Cycle (ECE-15 or UDC) and the Hybrid Pulse Power Characterization (HPPC). The experimental results obtained from a Li-ion polymer battery have been compared with the data provided by the models, confirming the effectiveness of the proposed procedure, and also, the application field of each model as a function of the required accuracy.

Optimal Coordination of Wind Power and Pumped Hydro Energy Storage

A study combining wind power with pumped hydro energy storage for the Jordanian utility grid is presented. Three solvers of the Matlab optimization toolbox are used to find the optimal solution for the cost of energy in a combined on-grid system. Genetic algorithm, simulated annealing (SA), and pattern search (PS) solvers are used to find the optimal solution. The GA solution of 0.0955388 $/kWh is economically feasible. This is 28.7% lower than the electricity purchased from the conventional utility grid. The discounted payback period to recover the total cost is 10.271 years. The suggested configuration is shown to be feasible by comparing it to real measurements for this case and a previous wind-only case. It is shown that the indicators of the optimal solution are improved. For instance, carbon dioxide emissions (ECO2) and conventional grid energy purchases are reduced by 24.69% and 24.68%, respectively. Moreover, it is shown that the benefits of adding hydro storage, combined with increasing the number of wind turbine units, reduces the cost of energy of renewables (COERenewables). Therefore, combining hydro storage with wind power is economically, environmentally, and technically a more efficient alternative to the conventional power generation.

Aerodynamic Optimization of a UAV Wing subject to Weight, Geometric, Root Bending Moment, and Performance Constraints

In this study, the optimization of a low-speed wing with functional constraints is discussed. The aerodynamic analysis tool developed by the coupling of the numerical nonlinear lifting-line method to Xfoil is used to obtain lift and drag coefficients of the baseline wing. The outcomes are compared with the results of the solver based on the nonlinear lifting-line theory implemented into XLFR5 and the transition shear stress transport model implemented into ANSYS-Fluent. The agreement between the results at the low and moderate angle of attack values is observed. The sequential quadratic programming algorithm of the MATLAB optimization toolbox is used for the solution of the constrained optimization problems. Three different optimization problems are solved. In the first problem, the maximization of CL3/2/CD is the objective function, while level flight condition at maximum CL3/2/CD is defined as a constraint. The functional constraints related to the wing weight, the wing planform area, and the root bending moment are added to the first optimization problem, and the second optimization problem is constructed. The third optimization problem is obtained by adding the level flight condition and the available power constraints at the maximum speed and the level flight condition at the minimum speed of the baseline unmanned air vehicle to the second problem. It is demonstrated that defining the root bending moment, the wing area, and the available power constraints in the aerodynamic optimization problems leads to more realistic wing planform and airfoil shapes.

On the Improvement of Vibration Mitigation and Energy Harvesting Using Electromagnetic Vibration Absorber-Inerter: Exact H2 Optimization

AbstractElectromagnetic resonant shunt tuned mass damper-inerter (ERS-TMDI) has recently been developed for dual-functional vibration suppression and energy harvesting. However, energy harvesting and vibration mitigation are conflicting objectives, thus rendering the multi-objectives optimization problem a very challenging task. In this paper, we aim at solving the design trade-off between these two objectives by proposing alternative configurations and finding the model with the best performance for both vibration suppression and energy harvesting. Three novel configurations are presented and are compared with the conventional ERS-TMDI. In the first two configurations, the primary structure and the absorber are only coupled through the spring. Both inerter and electromagnetic devices are connected to the ground in the first configuration, whereas only the inerter is connected to the ground in the second configuration. The third configuration is inspired by the recently developed three-element vibration-inerter (TEVAI), but in this case an electromagnetic device is sandwiched in between the primary structure and the absorber. Closed-form expressions are presented for optimum vibration mitigation and energy harvesting performances using H2 criteria for both ground and force excitations. The obtained explicit expressions are validated using matlab optimization toolbox. Simulation examples reveal that the first configuration performs the best, whereas the second performs the worst in terms of both vibration mitigation and energy harvesting. It is also demonstrated that replacing the series RLC with a parallel circuit can improve or degrade the vibration mitigation performance, but it constantly enhances the energy harvesting performance in all four models.

Evaluation of a commercial MR damper for application in semi-active suspension

As the rheology of a magneto-rheological (MR) fluid can be controlled by an externally applied magnetic field, the damping force generated by a MR damper can be controlled by varying the current supplied to an electromagnet inside the damper. This paper presents the experimental evaluation of such a MR damper RD-8040-1 by Lord Corporation, USA, and its application in a semi-active suspension. The experiments were carried out in damping force testing machine. Sinusoidal displacement input was given to the test damper. The set of experiments were repeated for different levels of current (0–1.5 A in steps of 0.25 A) supplied to the MR damper. Plots of force versus displacement for each frequency of excitation and plots of maximum force versus frequency of excitation show that higher values of current lead to elevated values of MR damper forces. This increase in MR damper load with current supplied is studied and analyzed to develop a mathematical model of the MR damper under investigation. The nonlinear softening hysteretic behavior of the MR damper is simulated by using genetic algorithm provided in the optimization toolbox of MATLAB. Calculations on energy dissipation and equivalent damping coefficient of the MR damper show that the same damper can make the suspension system behave as an underdamped system, critically damped system or overdamped system depending on the value of current supplied to it. The application of this MR damper for heavy vehicle driver’s seat suspension is explored with the help of MATLAB simulations.

Optimization design of structure parameters of dynamic recoil device

The muzzle dynamic recoil device for guns was designed. The optimization of dynamic recoil device was studied in detail. Using the MATLAB optimization toolbox, a series of optimized parameters of dynamic recoil device were got. By compared the results of dynamic recoil test with live-fire of the gun, the rationality and practicability of the dynamic recoil device has been proved. It is also proved that the muzzle dynamic recoil device can meet the dynamic recoil test requirements of guns.

Dynamic Analysis and Optimization of the Planar Model of the Trolleybus Škoda 21Tr

The article deals about modelling, dynamic analysis and optimization of stiffness and damping parameters of the main suspension of the Skoda 21Tr trolleybus. The trolleybus is excited by a ride on a rough road modelled using the Shinozuka method with the specified spectral power density. After examining the impact of tire stiffness and damping on the effective values of driving comfort characteristics, dynamic tire-to-road forces, and relative displacements between sprung and unsprang mass, the effect of spring stiffness and damping of dampers in main suspension are investigated. After selecting appropriate optimization parameters, the stiffness and damping parameters of the main suspension are optimized using the MATLAB Optimization Toolbox. The objective function is the sum of the effective values of the suspension mass acceleration and its angular acceleration. The results are the improved driving comfort without increasing the dynamic forces between the tires and the road and the relative displacements between the sprung and unsprung masses.

DUCTILE FRACTURE LOCUS VALIDATION METHOD OF THIN STEEL PLATES CONSIDERING THE LODE ANGLE PARAMETER

It was observed that shear fracture dominates in the fracture of steel beam webs. For this reason, the lode angle parameter should be taken into account along with the stress triaxiality. A new ductile fracture calibration method applicable to thin steel plates is proposed in this paper. Five groups of specimens were designed in this paper. They are flat plates, holed flat plates, flat grooved plates, 90° shear plates and 45° shear plates. The true stress-ture strain (σ-e) curves were obtained through flat plate, halted flat plate specimens and relevant finite element (FE) method iterations. The FE models of other specimens were computed with this σ-e relationship and compared with related experimental results to obtain the corresponding equivalent fracture strain, average stress triaxiality and average lode angle parameter. With the help of the Matlab Optimization Toolbox, the optimal parameters of the fracture model can be determined.