Towards a generic optimal co-design of hardware architecture and control configuration for interacting subsystems

In plants consisting of multiple interacting subsystems, the decision on how to optimally select and place actuators and sensors and the accompanying question on how to control the overall plant is a challenging task. Since there is no theoretical framework describing the impact of sensor and actuator placement on performance, an optimization method exploring the possible configurations is introduced in this paper to find a trade-off between implementation cost and achievable performance. Moreover, a novel model-based procedure is presented to simultaneously co-design the optimal number, type and location of actuators and sensors and to determine the corresponding optimal control architecture and accompanying control parameters. This paper adds the optimization of the control architecture to the current state-of-the-art. As an optimization output, a Pareto front is presented, providing insights on the optimal total plant performance related to the hardware and control design implementation cost. The proposed algorithm is not focused on one particular application or a specific optimization problem, but is instead a generally applicable method and can be applied to a wide range of applications (e.g., mechatronic, electrical, thermal). In this paper, the co-design approach is validated on a mechanical setup

Comparison of Direct Multiobjective Optimization Methods for the Design of Electric Vehicles

"System design oriented methodologies" are discussed in this paper through the comparison of multiobjective optimization methods applied to heterogeneous devices in electrical engineering. Avoiding criteria function derivatives, direct optimization algorithms are used. In particular, deterministic geometric methods such as the Hooke & Jeeves heuristic approach are compared with stochastic evolutionary algorithms (Pareto genetic algorithms). Different issues relative to convergence rapidity and robustness on mixed (continuous/discrete), constrained and multiobjective problems are discussed. A typical electrical engineering heterogeneous and multidisciplinary system is considered as a case study: the motor drive of an electric vehicle. Some results emphasize the capacity of each approach to facilitate system analysis and particularly to display couplings between optimization parameters, constraints, objectives and the driving mission

A New Hybrid Optimization Method, Application to a Single Objective Active Flow Control Test Case

Genetic Algorithms (GA) are useful optimization methods for exploration of the search space, but they usually have slowness problems to exploit and converge to the minimum. On the other hand, gradient based methods converge faster to local minimums, although are not so robust (e.g., flat areas and discontinuities can cause problems) and they lack exploration capabilities. This article presents a hybrid optimization method trying to combine the virtues of genetic and gradient based algorithms, and to overcome their corresponding drawbacks. The performance of the Hybrid Method is compared against a gradient based method and a Genetic Algorithm, both used alone. The rate of convergence of the methods is used to compare their performance. To take into account the robustness of the methods, each one has been executed more than once, with different starting points for the gradient based method and different random seeds for the Genetic Algorithm and the Hybrid Method. The performance of the different methods is tested against an optimization Active Flow Control (AFC) problem over a 2D Selig–Donovan 7003 (SD7003) airfoil at Reynolds number 6×104 and a 14 degree angle of attack. Five design variables are considered: jet position, jet width, momentum coefficient, forcing frequency and jet inclination angle. The objective function is defined as minus the lift coefficient (-Cl), so it is defined as a minimization problem. The proposed Hybrid Method enables working with N optimization algorithms, multiple objective functions and design variables per optimization algorithm.This research has been partially supported through the Severo Ochoa Centre of Excellence (2019-2023) under the grant CEX2018-000797-S funded by MCIN/AEI/10.13039/501100011033. The third author, Jordi Pons-Prats, is a Serra Hunter Fellow.Peer ReviewedObjectius de Desenvolupament Sostenible::13 - Acció per al ClimaObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPostprint (published version

A hybrid multi-objective evolutionary approach for optimal path planning of a hexapod robot

Hexapod robots are six-legged robotic systems, which have been widely investigated in the literature for various applications including exploration, rescue, and surveillance. Designing hexapod robots requires to carefully considering a number of different aspects. One of the aspects that require careful design attention is the planning of leg trajectories. In particular, given the high demand for fast motion and high-energy autonomy it is important to identify proper leg operation paths that can minimize energy consumption while maximizing the velocity of the movements. In this frame, this paper presents a preliminary study on the application of a hybrid multi-objective optimization approach for the computer-aided optimal design of a legged robot. To assess the methodology, a kinematic and dynamic model of a leg of a hexapod robot is proposed as referring to the main design parameters of a leg. Optimal criteria have been identified for minimizing the energy consumption and efficiency as well as maximizing the walking speed and the size of obstacles that a leg can overtake. We evaluate the performance of the hybrid multi-objective evolutionary approach to explore the design space and provide a designer with an optimal setting of the parameters. Our simulations demonstrate the effectiveness of the hybrid approach by obtaining improved Pareto sets of trade-off solutions as compared with a standard evolutionary algorithm. Computational costs show an acceptable increase for an off-line path planner. © Springer International Publishing Switzerland 2016

Optimal design for active damping in sandwich structures using the Direct MultiSearch method

This paper addresses the problem of optimal positioning of surface bonded piezoelectric patches in sandwich plates with viscoelastic core and laminated face layers. The objective is to maximize a set of modal loss factors for a given frequency range using multiobjective topology optimization. Active damping is introduced through co-located negative velocity feedback control. The multiobjective topology optimization problem is solved using the Direct MultiSearch Method. An application to a simply supported sandwich plate is presented with results for the maximization of the first six modal loss factors. The influence of the finite element mesh is analyzed and the results are, to some extent, compared with those obtained using alternative single objective optimization

Optimal Reconfiguration of a Parallel Robot for Forward Singularities Avoidance in Rehabilitation Therapies. A Comparison via Different Optimization Methods

[EN] This paper presents an efficient algorithm for the reconfiguration of a parallel kinematic manipulator with four degrees of freedom. The reconfiguration of the parallel manipulator is posed as a nonlinear optimization problem where the design variables correspond to the anchoring points of the limbs of the robot on the fixed platform. The penalty function minimizes the forces applied by the actuators during a specific trajectory. Some constraints are imposed to avoid forward singularities and guarantee the feasibility of the active generalized coordinates for a certain trajectory. The results are compared with different optimization approaches with the aim of avoiding getting trapped into a local minimum and undergoing forward singularities. The comparison covers evolutionary algorithms, heuristics optimizers, multistrategy algorithms, and gradient-based optimizers. The proposed methodology has been successfully tested on an actual parallel robot for different trajectories.This research was funded by the Spanish Ministry of Education, Culture and Sports, grant number DPI2017-84201-R.Llopis-Albert, C.; Valero Chuliá, FJ.; Mata Amela, V.; Pulloquinga-Zapata, J.; Zamora-Ortiz, P.; Escarabajal-Sánchez, RJ. (2020). Optimal Reconfiguration of a Parallel Robot for Forward Singularities Avoidance in Rehabilitation Therapies. A Comparison via Different Optimization Methods. Sustainability. 12(14):1-18. https://doi.org/10.3390/su12145803S1181214Rubio, F., Valero, F., & Llopis-Albert, C. (2019). A review of mobile robots: Concepts, methods, theoretical framework, and applications. International Journal of Advanced Robotic Systems, 16(2), 172988141983959. doi:10.1177/1729881419839596Jamwal, P. K., Xie, S. Q., Hussain, S., & Parsons, J. G. (2014). An Adaptive Wearable Parallel Robot for the Treatment of Ankle Injuries. IEEE/ASME Transactions on Mechatronics, 19(1), 64-75. doi:10.1109/tmech.2012.2219065Niu, X., Yang, C., Tian, B., Li, X., & Han, J. (2019). Modal Decoupled Dynamics Feed-Forward Active Force Control of Spatial Multi-DOF Parallel Robotic Manipulator. Mathematical Problems in Engineering, 2019, 1-13. doi:10.1155/2019/1835308Chablat, D., Kong, X., & Zhang, C. (2018). Kinematics, Workspace, and Singularity Analysis of a Parallel Robot With Five Operation Modes. Journal of Mechanisms and Robotics, 10(3). doi:10.1115/1.4039400Gao, Z., & Zhang, D. (2011). Workspace Representation and Optimization of a Novel Parallel Mechanism with Three-Degrees-of-Freedom. Sustainability, 3(11), 2217-2228. doi:10.3390/su3112217Hu, B., Shi, D., Xie, T., Hu, B., & Ye, N. (2020). Kinematically identical manipulators derivation for the 2-RPU+UPR parallel manipulator and their constraint performance comparison. Journal of Mechanisms and Robotics, 1-13. doi:10.1115/1.4047540Schappler, M., Tappe, S., & Ortmaier, T. (2019). Modeling Parallel Robot Kinematics for 3T2R and 3T3R Tasks Using Reciprocal Sets of Euler Angles. Robotics, 8(3), 68. doi:10.3390/robotics8030068Chen, Z., Xu, L., Zhang, W., & Li, Q. (2019). Closed-form dynamic modeling and performance analysis of an over-constrained 2PUR-PSR parallel manipulator with parasitic motions. Nonlinear Dynamics, 96(1), 517-534. doi:10.1007/s11071-019-04803-2Zhang, D., & Wei, B. (2017). Interactions and Optimizations Analysis between Stiffness and Workspace of 3-UPU Robotic Mechanism. Measurement Science Review, 17(2), 83-92. doi:10.1515/msr-2017-0011Wu, G., & Zou, P. (2016). Comparison of 3-DOF asymmetrical spherical parallel manipulators with respect to motion/force transmission and stiffness. Mechanism and Machine Theory, 105, 369-387. doi:10.1016/j.mechmachtheory.2016.07.017Meng, W., Xie, S. Q., Liu, Q., Lu, C. Z., & Ai, Q. (2017). Robust Iterative Feedback Tuning Control of a Compliant Rehabilitation Robot for Repetitive Ankle Training. IEEE/ASME Transactions on Mechatronics, 22(1), 173-184. doi:10.1109/tmech.2016.2618771Yang, Z., & Zhang, D. (2019). ENERGY OPTIMAL ADAPTION AND MOTION PLANNING OF A 3-RRS BALANCED MANIPULATOR. International Journal of Robotics and Automation, 34(5). doi:10.2316/j.2019.206-0171Zhang, D., & Gao, Z. (2012). Optimal Kinematic Calibration of Parallel Manipulators With Pseudoerror Theory and Cooperative Coevolutionary Network. IEEE Transactions on Industrial Electronics, 59(8), 3221-3231. doi:10.1109/tie.2011.2166229Lou, Y., Zhang, Y., Huang, R., Chen, X., & Li, Z. (2014). Optimization Algorithms for Kinematically Optimal Design of Parallel Manipulators. IEEE Transactions on Automation Science and Engineering, 11(2), 574-584. doi:10.1109/tase.2013.2259817Dumlu, A., & Erenturk, K. (2014). Trajectory Tracking Control for a 3-DOF Parallel Manipulator Using Fractional-Order $\hbox{PI}^{\lambda}\hbox{D}^{\mu}$ Control. IEEE Transactions on Industrial Electronics, 61(7), 3417-3426. doi:10.1109/tie.2013.2278964Llopis-Albert, C., Rubio, F., & Valero, F. (2018). Optimization approaches for robot trajectory planning. Multidisciplinary Journal for Education, Social and Technological Sciences, 5(1), 1. doi:10.4995/muse.2018.9867Gosselin, C., & Angeles, J. (1990). Singularity analysis of closed-loop kinematic chains. IEEE Transactions on Robotics and Automation, 6(3), 281-290. doi:10.1109/70.56660Briot, S., Arakelian, V., Bonev, I. A., Chablat, D., & Wenger, P. (2008). Self-Motions of General 3-RPR Planar Parallel Robots. The International Journal of Robotics Research, 27(7), 855-866. doi:10.1177/0278364908092466Karimi, A., Masouleh, M. T., & Cardou, P. (2016). Avoiding the singularities of 3-RPR parallel mechanisms via dimensional synthesis and self-reconfigurability. Mechanism and Machine Theory, 99, 189-206. doi:10.1016/j.mechmachtheory.2016.01.006Patel, Y. D., & George, P. M. (2012). Parallel Manipulators Applications—A Survey. Modern Mechanical Engineering, 02(03), 57-64. doi:10.4236/mme.2012.23008Araujo-Gómez, P., Díaz-Rodríguez, M., Mata, V., & González-Estrada, O. A. (2019). Kinematic analysis and dimensional optimization of a 2R2T parallel manipulator. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(10). doi:10.1007/s40430-019-1934-1Araujo-Gómez, P., Mata, V., Díaz-Rodríguez, M., Valera, A., & Page, A. (2017). Design and Kinematic Analysis of a Novel 3UPS/RPU Parallel Kinematic Mechanism With 2T2R Motion for Knee Diagnosis and Rehabilitation Tasks. Journal of Mechanisms and Robotics, 9(6). doi:10.1115/1.4037800Vallés, M., Araujo-Gómez, P., Mata, V., Valera, A., Díaz-Rodríguez, M., Page, Á., & Farhat, N. M. (2017). Mechatronic design, experimental setup, and control architecture design of a novel 4 DoF parallel manipulator. Mechanics Based Design of Structures and Machines, 46(4), 425-439. doi:10.1080/15397734.2017.1355249Koziel, S., & Yang, X.-S. (Eds.). (2011). Computational Optimization, Methods and Algorithms. Studies in Computational Intelligence. doi:10.1007/978-3-642-20859-1Beiranvand, V., Hare, W., & Lucet, Y. (2017). Best practices for comparing optimization algorithms. Optimization and Engineering, 18(4), 815-848. doi:10.1007/s11081-017-9366-1Page, A., De Rosario, H., Mata, V., Hoyos, J. V., & Porcar, R. (2006). Effect of marker cluster design on the accuracy of human movement analysis using stereophotogrammetry. Medical and Biological Engineering and Computing, 44(12), 1113-1119. doi:10.1007/s11517-006-0124-3Arora, J. S., Chahande, A. I., & Paeng, J. K. (1991). Multiplier methods for engineering optimization. International Journal for Numerical Methods in Engineering, 32(7), 1485-1525. doi:10.1002/nme.1620320706Modefrontier Toolhttps://www.esteco.com.202

Topology Optimization Applications on Engineering Structures

Over the years, several optimization techniques were widely used to find the optimum shape and size of engineering structures (trusses, frames, etc.) under different constraints (stress, displacement, buckling instability, kinematic stability, and natural frequency). But, most of them require continuous data set where, on the other hand, topology optimization (TO) can handle also discrete ones. Topology optimization has also allowed radical changes in geometry which concludes better designs. So, many researchers have studied on topology optimization by developing/using different methodologies. This study aims to classify these studies considering used methods and present new emerging application areas. It is believed that researchers will easily find the related studies with their work

Optimization on industrial problems focussing on multi-player strategies

Algorithms (EA) are useful optimization methods for exploration of the search space, but they usually have slowness problems to exploit and converge to the minimum with accuracy. On the other hand, gradient based methods converge faster to local minimums, although are not so robust (e.g., flat areas and discontinuities can cause problems) and they lack exploration capabilities. This thesis presents and analyze four versions of a hybrid optimization method trying to combine the virtues of Evolutionary Algorithms (EA) and gradient based algorithms, and to overcome their corresponding drawbacks. The proposed Hybrid Methods enables working with N optimization algorithms (called players), multiple objective functions and design variables, and define them differently for each player. The performance of the Hybrid Methods are compared against a gradient based method, two Genetic Algorithms (GA) and a Particle Swarm Optimization (PSO). Tests have been conducted with mathematical benchmark problems (synthetic tests designed to specifically test optimization methods) and an engineering application with high demanding computational resources, a Synthetic Jet actuator for Active Flow Control (AFC) over a 2D Selig-Donovan 7003 (SD7003) airfoil at Reynolds number 6 x 10^4 and a 14 degree angle of attack. The Active Flow control problem has been used in a single optimization problem and in a two objective optimization problemEls Algoritmes Evolutius (EA) són mètodes d'optimització útils per a l'exploració de l'espai de cerca, però solen tenir problemes de lentitud per explotar-ne el mínim i convergir amb precisió. D'altra banda, els mètodes basats en gradients convergeixen més ràpidament als mínims locals, encara que no són tan robusts (per exemple, les àrees planes i les discontinuïtats poden causar problemes) i no tenen capacitats d'exploració. Aquesta tesi presenta i analitza quatre versions d'un mètode d'optimització híbrid que intenta combinar les virtuts dels Algoritmes Evolutius (EA) i els algoritmes basats en gradients, i superar-ne els inconvenients corresponents. Els Mètodes Híbrids proposats permeten treballar amb N algoritmes d'optimització (anomenats jugadors), múltiples funcions objectiu i variables de disseny, i definir-les de manera diferent per a cada jugador. El rendiment dels mètodes híbrids es compara amb un mètode basat en gradient, dos Algoritmes Genètics (GA) i un mètode d'optimització d'eixam de partícules (PSO). S'han fet proves amb problemes matemàtics de referència (proves sintètiques dissenyades per provar específicament mètodes d'optimització) i una aplicació d'enginyeria amb recursos computacionals molt exigents, un actuador de jet sintètic per a control de flux actiu (AFC) sobre un perfil aerodinàmic 2D Selig -Donovan 7003 (SD7003) al número de Reynolds 6 x 104 i un angle d'atac de 14 graus. El problema de control de flux actiu s'ha utilitzat en un problema d'optimització monoobjectiu i en un problema d'optimització de dos objectius.Postprint (published version

Fractional Order Load-Frequency Control of Interconnected Power Systems Using Chaotic Multi-objective Optimization

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Fractional order proportional-integral-derivative (FOPID) controllers are designed for load frequency control (LFC) of two interconnected power systems. Conflicting time domain design objectives are considered in a multi objective optimization (MOO) based design framework to design the gains and the fractional differ-integral orders of the FOPID controllers in the two areas. Here, we explore the effect of augmenting two different chaotic maps along with the uniform random number generator (RNG) in the popular MOO algorithm - the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Different measures of quality for MOO e.g. hypervolume indicator, moment of inertia based diversity metric, total Pareto spread, spacing metric are adopted to select the best set of controller parameters from multiple runs of all the NSGA-II variants (i.e. nominal and chaotic versions). The chaotic versions of the NSGA-II algorithm are compared with the standard NSGA-II in terms of solution quality and computational time. In addition, the Pareto optimal fronts showing the trade-off between the two conflicting time domain design objectives are compared to show the advantage of using the FOPID controller over that with simple PID controller. The nature of fast/slow and high/low noise amplification effects of the FOPID structure or the four quadrant operation in the two inter-connected areas of the power system is also explored. A fuzzy logic based method has been adopted next to select the best compromise solution from the best Pareto fronts corresponding to each MOO comparison criteria. The time domain system responses are shown for the fuzzy best compromise solutions under nominal operating conditions. Comparative analysis on the merits and de-merits of each controller structure is reported then. A robustness analysis is also done for the PID and the FOPID controllers