This paper discusses the application of second order mode controls to hydraulic valve-cylinder drives with a special focus on the limitations resulting from nonlinear dynamic effects in flow control valves. Second order sliding mode algorithms appear highly attractive in the successive implementation of sliding mode control, achieving continuous control inputs, while maintaining the main properties of sliding modes. Under certain model assumptions, some of these controllers may even be applied as output feedback controllers. However, intrinsic nonlinear dynamic effects of hydraulic valves such as slew rates and time delays arising in the amplification stages, limits the applicability of such methods, and may lead to partial losses of robustness and limit cycles. These properties are analyzed and experimentally verified, and compensation methods are proposed. The application of the second order sliding algorithm known as the super twisting controller is considered for output feedback control and compared with conventional first order sliding mode control. The controllers under consideration are applied for position tracking control of a hydraulic valve-cylinder drive exhibiting strong variations in inertia- and gravitational loads. Results demonstrate that the super twisting algorithm may be successfully applied for output feedback control of hydraulic valve-cylinder drives, with modifications guaranteeing robust control performance in a small vicinity of the control target.

In this research, a novel inverse design algorithm called, Elastic Surface Algorithm (ESA), is developed for viscose and inviscid external flow regimes. ESA is a physically based iterative inverse design method that uses flow analysis code to estimate the pressure distribution on the solid structure, i.e. airfoil, and a 2D solid beam finite element code to calculate the deflections due to the difference between the calculated and target pressure distribution. The proposed method is validated through the inverse design of three different airfoils. In addition, two design examples are presented to prove the robustness of the method in various flow regimes. Also, the convergence rate of this method is compared with flexible membrane method (MGM) and Ball-Spine Algorithm (BSA) methods in inviscid flow regime. The results of this study showed that not only the ESA method is an effective method for inverse design of airfoils, but also it can considerably increase the convergence rate in transonic flow regimes.

Nowadays, the integration of micro-actuators in the micro-systems poses a significant problem due to the complex designs as well as due to the contact power supply systems (e.g., via micro-batteries or via wires). A way to overcome this problem is to provide remote power supply and control to the bistable micro-actuators. It is mainly done by RF (radio-frequency) or optical means. As a consequence, the stability of the two positions of this kind of micro-actuators and the switching time evolution between them have to be studied to determine the robustness of the contactless bistable micro-actuators. In this work, these system parameters were analysed by the ANOVA (Analysis Of Variance) method during a longlife test for 8 different configurations (Design of Experiments) of bistable micro-actuators controlled by laser. Transient and permanent regimes were observed for the stability of the positions, for the standard deviation around the positions and for the switching time as well. In each case, the transient regime represented only 3% of the total duration of the longlife test. A very good stabilisation was observed in the permanent regime whereas a decrease of the stroke was observed in the transient regime. As a consequence, during this regime, the switching time was reduced compared with the regular values (few seconds, optical power dependent). In the permanent regime, a progressive increase of this factor was noted that indicated the progressive fatigue of the bistable micro-actuator. A second indicator of the micro-actuator fatigue was given by the increase of the standard deviation of the stable position after cycle number 9000. Above this point, the micro-actuator was vibrating during the functioning even if the stability remained acceptable.

For Multi-Objective Robust Optimization Problem (MOROP), it is important to obtain design solutions that are both optimal and robust. To find these solutions, usually, the designer need to set a threshold of the variation of Performance Functions (PFs) before optimization, or add the effects of uncertainties on the original PFs to generate a new Pareto robust front. In this paper, we divide a MOROP into two Multi-Objective Optimization Problems (MOOPs). One is the original MOOP, another one is that we take the Robustness Functions (RFs), robust counterparts of the original PFs, as optimization objectives. After solving these two MOOPs separately, two sets of solutions come out, namely the Pareto Performance Solutions ( P P ) and the Pareto Robustness Solutions ( P R ). Make a further development on these two sets, we can get two types of solutions, namely the Pareto Robustness Solutions among the Pareto Performance Solutions ( P R ( P P ) ), and the Pareto Performance Solutions among the Pareto Robustness Solutions ( P P ( P R ) ). Further more, the intersection of P R ( P P ) and P P ( P R ) can represent the intersection of P R and P P well. Then the designer can choose good solutions by comparing the results of P R ( P P ) and P P ( P R ) . Thanks to this method, we can find out the optimal and robust solutions without setting the threshold of the variation of PFs nor losing the initial Pareto front. Finally, an illustrative example highlights the contributions of the paper.

Variability in fiber architecture and content introduces randomness in transport and mechanical properties of textile reinforcements and composites. Assessment of robustness of both manufacturing processes and composite parts require to link fabric variability to dominant properties. Irregular injection flow patterns or defects in the final products often occur due to the high variability in the fibrous media. Therefore, manufacturing robustness and part reliability have to be studied to avoid trial and error procedures. This study focuses on spatial variability in the fiber volume fraction and architecture and their influence on permeability of fiber reinforcements and mechanical performance of textile composite, relating these important properties to variation in reinforcement architecture. Methods to capture experimentally and model numerically the fabric randomness are presented and illustrated on typical non-woven fabrics. An efficient numerical approach is presented for the simulation of mold filling process with random fibrous permeability as input. Numerical examples for different injection schemes are presented to demonstrate the ability of the current approach in predicting the variability in mold filling results.

Within the last years mechatronics as a self-contained discipline doubtlessly shaped the development of technical systems. Mechatronics means the close interaction of mechanics, electronics, control engineering and software engineering in order to achieve a better systems behavior. Due to the outstanding deployment of information and communication technologies, the functionality of mechatronic systems will go far beyond the known standards with the intention to increase their robustness, flexibility and reliability. The objective is to develop intelligent systems that react autonomously on changing environmental conditions and optimize their behavior during operation. The design of such advanced mechatronic systems is a challenge. Additionally to mechanical, electrical, control and software engineers also expertise from mathematical optimization, artificial intelligence and even cognitive science is necessary. This requires an effective and continuous cooperation and communication between developers from different domains during the whole development process. As a consequence a domain-spanning methodology is necessary in order to guarantee an effective work flow between the participating developers from various domains and their domain-specific methods, terminologies and solutions. For this purpose an ontology-based computer support will be presented, that facilitates the systems engineer by analyzing the functional system model and identifying convenient solutions. This includes the generation and storage of once proven design solutions as well as the search for the effective and domain-spanning reuse.

The numerical optimization of the connecting rod big-end lubrication involves several main steps. The first, which can be considered as the most important one, is the identification of the main input factors and their varying range. In the same time, the meaningful resulting values have to be identified because the optimization will be performed on the basis of this choice. The computing time for a TEHD solution prevents from performing a huge amount of calculi to draw the Pareto-Front of the solutions. Thus, the next step is the creation of a metamodel, based on polynomials, with a good predictability property and a low computing cost. In the third step, a fast Multi Objective Optimization is performed on the metamodel. The Pareto-Front, which represents the best trade-offs of solutions, is identified: one can now easily choose the input parameters which will give a particular desired solution. In the last step, the robustness of the solutions has to be checked: if a given solution is chosen, the corresponding input parameters have to enclose a minimal uncertainty gap to be realistic. Otherwise, this wanted solution will never be reached, because in a real-life problem, the parameter values are not deterministic.

This paper presents a novel autopilot for a 3D helicopter. From desired trajectories defined by the user for elevation and travel angles, the autopilot is computing the desired trajectory of the pitch angle. Furthermore, the autopilot allows to decouple the system and to define “virtual” inputs in order to separately design controllers for each attitude angle. Travel and elevation controllers are based on adaptive version of super-twisting algorithm: this class of controllers keeps the robustness feature of sliding mode while reducing the well-known drawback of such control approach, the chattering, thanks to the online adaptation of the controller gain.

In the presented article we propose a mathematical model for nonlinear response of the polycristalline ferroelectrics, an efficient numerical algorithm for its parameters identification, and finally we deal with the ways of their using in practice. Piezoelectrics and ferroelectrics constitute an important class of materials known owing theirs wide application as sensors and actuators in a large number of devices and components. The control, description, and understanding of piezoelectrics and ferroelectrics behavior present thus an important and difficult undertaking from both the practical and theoretical point of view. The piezoelectric hysteresis is an important property of piezoelectric and ferroelectric materials caused by different physical processes that take place in ferroelectric materials, e.g. domain-wall pinning, defect ordering, etc. Most often hysteresis is undesired in high-precision sensor, actuator and capacitor applications. But leaving out of framework the origin and mechanisms of the piezoelectric hysteresis the necessity of devices rational design forces to develop the specialized CAE systems to be able to simulate and optimize an efficiency of the ferroelectric-based devices, considering both useful and undesirable phenomena. So, finite-element modeling of sensor and actuator devices requires knowledge of the supplementary constitutive relations that are valid at broad range of electric fields, including the cases of irreversible polarization or depolarization process. There are several approaches to deriving the governing relationships, particularly, orientation Jiles–Atherton model, where governing relationships are formulated by increments between some intrinsic and target parameters. At low mathematical complexity this model is based on the transparent physical meanings, allowing to describe the work of electric field rotating the domains, and energy destructing the fixed domain walls. The proposed model represents a nonlinear ordinary differential equation relative to polarization and driving by electric field. Together with incremental theory this model allows to describe the real behavior of the physical object and to determine all needed field features at list for quasistatic process. As many models describing a nonlinear behavior of whole class of polycristalline materials our model depends on the five intrinsic parameters which have a different physical nature, and have influence on the nonlinear hysteretic response of material. Settings of model imply an unambiguous determination of such parameters. Identification of these parameters is a coefficient inverse problem, and for its resolving we have used the experimentally obtained hysteretic loops. At numerical implementation the set of these five parameters minimize a discrepancy functional square depended on experimentally observed and calculated points of hysteretic loop. Due to complexity of the minimized functional behavior on the space of identified parameters the minimization procedure was realized by means of Genetic Algorithm Toolbox MATLAB. The developed numerical method for hysteresis differential operator parameters identification has shown the good efficiency, robustness, and speedy convergence. These parameters then have used for static and modal analysis by finite element package ACELAN that utilizes an incremental theory for describing of irreversible polarization process. Finally we demonstrate some calculation results for non-uniformly polarized piezoceramic elements.

In this paper, an adaptive control scheme for multi-agent formation control is proposed. This control method is based on artificial potential functions integrated with adaptive fuzzy sliding mode control technique. We consider fully actuated mobile agents with completely unknown dynamics. An adaptive fuzzy logic system is used to approximate the unknown system dynamics. Sliding Mode Control (SMC) theory is used to force agents’ motion to obey the dynamics defined by the simple inter-agent artificial potential functions. Stability proof is given using Lyapunov functions, which shows the robustness of controller with respect to disturbances and system uncertainties. Simulation results are demonstrated for a multi-agent formation problem, illustrating the effectiveness of the proposed method. Experimental results are included to verify the applicability of the scheme for a test-bed of six real mobile robots.

The plant under control is the hydraulic circuit arranged by CNH in a prototype agriculture tractor of medium segment, where instead of the conventional main hydraulic pump, a new device electronically piloted, is installed. The main purpose is basically to obtain some advantages according to the energetic point of view, by means of an appropriate control structure, managing the electronic variable displacement pump. The frontier of the new systems requires the employment of the advanced control techniques, in order to assure the levels of precision, reliability, robustness demanded from systems. The control design methodology employed in the present case is based on robust H∞ optimization techniques, where robust stability properties are guaranteed in presence of unaccountable dynamics and other destabilizing factors. The effectiveness of the proposed control approach is tested on the demonstrative tractor realized from the CNH Agriculture at Modena plants, in all real conditions.

In the present study, an adaptive sliding mode control method was employed to control a fish robotic system using hardware in the loop methodology. Up to now, few researches have focused on autonomous control of fish robot in dynamic environments which may be the result of difficulties in modeling of hydrodynamic effects on fish robot. Therefore, following the introduction of the nonlinear model for the robot, elongated body theory, suggested by Lighthill, was used to analyze fish movements. Then, kinematics control to track desired trajectories was designed for under-actuated model of robot. Adaptive sliding mode controller, capable of adapting according to changes and uncertainties, was designed and implemented. Using a fabricated stand, experimental tests were performed using hardware in the loop simulation. Computer simulations accompanied by experimental results verify that the presented adaptive controller has two main advantages: first, they make a robot versatile and capable of moving in unknown environments because of system robustness under changes and uncertainties of parameters. Second, they leave out the need for expensive and time consuming experiments to recognize system model and reduce operations for final tuning of controller.

This paper presents an application of the Bees Algorithm (BA) to the optimisation of weights within neural networks for wood defect detection. This novel population-based search algorithm mimics the natural foraging behaviour of swarms of bees. In its basic version, the algorithm performs a kind of neighbourhood search combined with random search. Following a brief description of the algorithm, the paper gives the results obtained for the wood defect identification problem demonstrating the efficiency and robustness of the new algorithm.

A finite difference lattice Boltzmann method (FDLBM) is employed to simulate the compressible inviscid/viscous flows. The robustness of the employed approach is tested for the shock tube or Riemann problem in some distinct cases including strong pressure shock, the stationary contact discontinuity and the weak acoustic wave. The Results are compared with the exact solutions, as well as other classical finite volume CFD techniques (Steger-Warming, Roe and AUSM flux). The validity of the employed LBM approach is studied. This research reveals some of the challenges involved in simulating the compressible flows using FDLBM.

This paper presents a novel structural optimization algorithm based on group hunting of animals such as lions, wolves, and dolphins. Although these hunters have differences in the way of hunting but they are common in that all of them look for a prey in a group. The hunters encircle the prey and gradually tighten the ring of siege until they catch the prey. In addition, each member of the group corrects its position based on its own position and the position of other members. If the prey escapes from the ring, the hunters reorganize the group to siege the prey again. A benchmark numerical optimization problems is presented to show how the algorithm works. Three benchmark structural optimization problems are also presented to demonstrate the effectiveness and robustness of the proposed Hunting Search (HuS) algorithm for structural optimization. The objective in these problems is to minimize the weight of bar trusses. Both sizing and layout optimization variables are included, too. The proposed algorithm is compared with other global optimization methods such as CMLPSA (Corrected Multi-Level & Multi-Point Simulated Annealing) and HS (Harmony Search). The results indicate that the proposed method is a powerful search and optimization technique. It yields comparable and in some cases, better solutions compared to those obtained using current algorithms when applied to structural optimization problems.

In this study, the robustness of five different commercial type wheelchairs under direct frontal impact loadings were modeled, examined and compared. Wheelchairs were modeled, simulated and analyzed under direct frontal impact process using ANSYS/LS-DYNA software. The stresses, strains and displacements of deformed shapes were obtained and compared. The results showed that, “Wheelchair Chassis 4” is the most economic and robust design. Finally the chosen wheelchair design was modified and developed and its robustness was examined.

A distributed approach is proposed for planning a cooperative tracking task for a team of unmanned aerial vehicles (UAVs). In the scenario of interest UAVs are required to autonomously track, using their onboard sensors, a moving target in a known urban environment. The solution methodology involves finding visibility regions, from which a UAV can maintain a line of sight to the target during the scenario; and restricted regions, in which a UAV can not fly, due to the presence of buildings or other airspace limitations. A co-evolution genetic algorithm is derived for searching, in realtime, monotonically improving solutions. In the proposed distributed search method every UAV iteratively manipulates its own population of chromosomes, each encoding its control inputs in the calculated horizon. Team performance is attained by assigning fitness to each solution in the population based on the cooperative performance when using it together with preceding iteration tracking information obtained from teammates. Important attributes of the proposed solution approach are its scalability and robustness; and consequently it can be applied to large sized problems and adapt to the loss of UAV team members. The distributed nature of the algorithm also reduces the computation and communication loads. The performance of the algorithm is studied using a high fidelity simulation test-bed incorporating a visual database of the city of Tel-Aviv, Israel.

In the field of geometrical product specification and verification, one of the main problems is classification and segmentation of 3D shapes. Shape recognition and segmentation is a widespread research area with different application fields (image processing, shape searching, pattern recognition, reverse engineering, etc.). Many methodologies and algorithms have been developed within such different fields, each one exhibiting optimized performances with respect to the set of objects and targets in each application [1, 11, 12]. Nevertheless, for manufactured parts a unique description of shape during the whole product lifecycle is still envisaged, and GPS (“Geometrical Product Specification and Verification”) project seems to be the most promising approach, but it should be stated that the partitioning process is still to be improved both theoretically and operationally. The ISO Technical Committee 213 (TC213), entrusted to develop the GPS project, founded the partitioning process on the classification of shapes based on symmetrical properties of surfaces [5, 6]. The aim of this paper is to describe the method proposed by Gelfand and Guibas [4] and analyze its performances on sampled surfaces by varying parameters of the method that basically affect its efficiency. In fact, the ISO research is currently devoted to identify a segmentation method characterized by efficiency, reliability, robustness and applicability with the aim to standardize the methodology for the verification phase of the manufacturing process. In this paper, a DOE analysis has been performed, in order to search an optimal parameter configuration, necessary to consider the method as a standard for shape partitioning.

In this paper the problem of eigenvalue assignment in active vibration control by the receptance method using single-input state feedback is considered. The poles of the system and their sensitivities are assigned using measured vibration data from the open-loop system in the form of receptances, there being no need to evaluate or to know the system matrices M , C , K . The perturbation method is applied to a characteristic equation resulting in expressions for the derivatives of the pole eigenvalues with respect to the control gains. These sensitivities are expressed as a linear combination of the feedback control gains. The control effort necessary to assign the poles may be reduced by increasing the sensitivity of the poles. In addition, the uncontrolled poles in the system may be rendered insensitive for stability robustness. It is demonstrated that chosen eigenvalues may be rendered insensitive to all the control gain terms by choice of the distribution vector b . Numerical examples are provided to demonstrate how the technique works.

The dynamic modelling and identification of a small-scale bridge is addressed in this paper. Two finite element models with linear elastic stiffness and different damping modelling has been tried. They correspond to a linear viscous damping and a nonlinear elasto-slip one. Both models were fitted to the available experimental data by a novel adaptive sampling technique that was repeated several times. In all the runs the technique yielded consistent results, which confirms its robustness. The elasto-slip model gave excellent fitting to the experimental data, while the results of the linear viscous one were poor.