Particle swarm optimization based proportional-derivative parameters for unmanned tilt-rotor flight control and trajectory tracking

This paper presents the dynamic modelling and control technique for a tilt-rotor aerial vehicle operating in bi-rotor mode. This kind of aircraft combines two flight envelopes, making it ideal for scenarios that require hovering, vertical take-off/landing and fixed-wing capabilities. In this work, a detailed mathematical model is derived using Newton–Euler formalism. Based on the obtained model, a new control scheme that incorporates six Proportional-Derivative (PD) controllers is proposed for the attitudes (roll (φ), pitch (θ), yaw (ψ)) and the positions (x, y, z) of the aircraft. Then, intelligent Particle Swarm Optimization (PSO) and conventional Reference Model (RM) techniques are applied for optimal tuning of the controllers\u27 parameters. The stability analysis is developed using the Lyapunov approach and its application to the tilt-rotor system in the case of intelligent and conventional PD controllers. Numerical results of two scenarios prove the efficiency of the controllers tuned using the PSO method. Indeed, its ability to track the desired trajectories is demonstrated through 3D path tracking simulations, even in the presence of wind disturbances. Finally, experimental tests of stabilization and trajectory tracking are carried out on our prototype. These testing showed that our tilt-rotor was stable and suitably follows the imposed trajectories

A novel improved elephant herding optimization for path planning of a mobile robot

Swarm intelligence algorithms have been in recent years one of the most used tools for planning the trajectory of a mobile robot. Researchers are applying those algorithms to find the optimal path, which reduces the time required to perform a task by the mobile robot. In this paper, we propose a new method based on the grey wolf optimizer algorithm (GWO) and the improved elephant herding optimization algorithm (IEHO) for planning the optimal trajectory of a mobile robot. The proposed solution consists of developing an IEHO algorithm by improving the basic EHO algorithm and then hybridizing it with the GWO algorithm to take advantage of the exploration and exploitation capabilities of both algorithms. The comparison of the IEHO-GWO hybrid proposed in this work with the GWO, EHO, and cuckoo-search (CS) algorithms via simulation shows its effectiveness in finding an optimal trajectory by avoiding obstacles around the mobile robot

Helicopter gearbox vibration fault classification using order tracking method and genetic algorithm

In this paper, we implemented a diagnostic system for vibration faults that occur on the PUMA helicopter gearbox. We used an approach based on the joint use of the Order Tracking signal analysis and the Genetic Algorithm. To achieve this goal, we first collected a database of vibration signals measured during periodic inspections. The available vibration signals are acquired under a time-varying operating conditions. Therefore, we used the Order Tracking method, which is more accurate in extracting faults features. This technique was performed by resampling the vibration data and then applying the Short Time Fourier Transform. To enable efficient and continuous monitoring of gearbox vibration faults from features, we used Genetic Algorithm to build a rules-based diagnostic model. Genetic operators have been adapted to the specificity of the problem to optimize the parameters of this model. This approach is successfully applied to the diagnosis of vibration defects of helicopter gearboxes. The results have been validated effectively with test data. The diagnostic model can therefore be implemented on helicopter computers to detect faults in flight or on the ground. This approach has been used for the first time in the field of helicopter gearbox vibration fault diagnosis

Dynamic Fuzzy c-Means (dFCM) Clustering and its Application to Calorimetric Data Reconstruction in High Energy Physics

In high energy physics experiments, calorimetric data reconstruction requires a suitable clustering technique in order to obtain accurate information about the shower characteristics such as position of the shower and energy deposition. Fuzzy clustering techniques have high potential in this regard, as they assign data points to more than one cluster,thereby acting as a tool to distinguish between overlapping clusters. Fuzzy c-means (FCM) is one such clustering technique that can be applied to calorimetric data reconstruction. However, it has a drawback: it cannot easily identify and distinguish clusters that are not uniformly spread. A version of the FCM algorithm called dynamic fuzzy c-means (dFCM) allows clusters to be generated and eliminated as required, with the ability to resolve non-uniformly distributed clusters. Both the FCM and dFCM algorithms have been studied and successfully applied to simulated data of a sampling tungsten-silicon calorimeter. It is seen that the FCM technique works reasonably well, and at the same time, the use of the dFCM technique improves the performance.Comment: 15 pages, 10 figures. It is accepted for publication in NIM

Bulk Majorons at Colliders

Lepton number violation may arise via the spontaneous breakdown of a global symmetry. In extra dimensions, spontaneous lepton number violation in the bulk implies the existence of a Goldstone boson, the majoron J^(0), as well as an accompanying tower of Kaluza-Klein (KK) excitations, J^(n). Even if the zero-mode majoron is very weakly interacting, so that detection in low-energy processes is difficult, the sum over the tower of KK modes may partially compensate in processes of relevance at high-energy colliders. Here we consider the inclusive differential and total cross sections for e^- e^- --> W^- W^- J, where J represents a sum over KK modes. We show that allowed parameter choices exist for which this process may be accessible to a TeV-scale electron collider.Comment: 11 pages LaTeX, 3 eps figures (references added

Turbidity diagrams of polyanion/polycation complexes in solution as a potential tool to predict the occurrence of polyelectrolyte multilayer deposition.

Surface functionalization with polyelectrolyte multilayer films (PEM films) has become very popular owing to its simplicity and versatility. However, even if some research is already available, this field of surface chemistry lacks a systematic knowledge of how the polyelectrolyte structure and solution conditions influence the growth of PEM films. In this investigation, we focus on the possible relationship between turbidity of polycation and polyanion mixtures in solution, and the buildup of PEM films made from the same polyelectrolytes in the same physicochemical conditions, namely pH, temperature and ionic strength. It comes out that for six different polycation/polyanion combinations there is a clear correlation between the turbidity evolution of polycation/polyanion complexes with the salt concentration and the evolution of the film deposition with the same parameter. In this investigation, the complexes in solution were prepared in conditions where the ratio between the number of cationic to anionic groups was close to unity. Even if there is a correlation between turbidity in solution and PEM film deposition, we found some exceptions in the low salt concentration regime. This work is an extension of the preliminary works of Cohen Stuart (D. Kovačević et al. Langmuir 18 (2002) 5607-5612) and Sukishvili et al. (S.A. Sukhishvili, E. Kharlampieva and V. Izumrudov, Macromolecules 39 (2006) 8873-8881).journal articleresearch support, non-u.s. gov't2010 Jun 012010 02 21importe

Intrinsic versus shape anisotropy in micro-structured magnetostrictive thin films for magnetic surface acoustic wave sensors

International audienceThis work aims at studying the interaction between surface acoustic waves (SAW) and micro-structured magnetostrictive layers under a magnetic field with a perspective to develop magnetic field sensors. The impact of the competition between the strong intrinsic magnetic anisotropy of the magnetic material and the shape anisotropy of the interdigitated transducer (IDT) fingers introduced by the micro-structuration is investigated. Therefore, the macroscopic and microscopic magnetic properties of the IDT and their influence on the magneto-acoustic response are studied. A SAW resonator with the IDTs made of the magnetostrictive thin film was elaborated and the magnetic surface acoustic wave (MSAW) response under a magnetic field was performed and discussed. Depending on the energy balance, the anisotropy gets modified and a correlation with the MSAW sensitivity to an externally applied magnetic field is made

Research on Urbanization in the Developing World: New Directions

--

A Profile Likelihood Analysis of the Constrained MSSM with Genetic Algorithms

The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely-studied supersymmetric extensions to the standard model of particle physics. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning supersymmetric parameter spaces, optimised for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing collider and cosmological data in our global fit. We compare our method to the MultiNest algorithm, an efficient Bayesian technique, paying particular attention to the best-fit points and implications for particle masses at the LHC and dark matter searches. Our global best-fit point lies in the focus point region. We find many high-likelihood points in both the stau co-annihilation and focus point regions, including a previously neglected section of the co-annihilation region at large m_0. We show that there are many high-likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques, especially at high masses. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans.Comment: 47 pages, 8 figures; Fig. 8, Table 7 and more discussions added to Sec. 3.4.2 in response to referee's comments; accepted for publication in JHE