Hybrid Multicarrier Random Space Vector PWM for the Mitigation the Acoustic Noise

The pulse width modulation (PWM) inverter is obvious for any industrial and power sector application. Particularly industrial drives are very keen on the industrial standards. Many modulations approached such a drives objects of DC-link consumption, harmonics suppression in lower and higher order spectrum and noise reduction. The still random PWM is a best candidate for reducing the noises on the PWM operated AC drives. There are various Random PWM (RPWM) methods has been developed and investigated for the PWM inverter fed drive noise reductions, still the shortcomings are existence on these method items of their less randomness and complex digital circuitry. These PWM dealt the spreading harmonics there by decreasing harmonic effects on the system. However, these techniques overlook the effect of acoustic noise and DC -link utilizations Therefore, in this paper mainly deals with to combined RPWM principle in space vector PWM (SVPWM) to generate random PWM generation using asymmetric frequency multi carrier called multicarrier random space vector PWM (MCRSVPWM). The SVM agreements with multicarrier (different fixed frequencies as carrier waves) which are chosen with the aid of a random binary bit generator. The proposed RSVM generated pulses with a randomized triangular carrier (4 ± 1.5 kHz), while the conventional RPWM method contains of the random pulse position with a fixed frequency triangular carrier. The simulation study is performed through MATLAB/Simulink for 3 HP asynchronous induction motor drive. The Experimental validation of proposed MCRSVPWM is tested with 2kW six switch (Power MOSFET – SCH2080KE) inverter power module fed induction motor drive.publishedVersio

Online security assessment with load and renewable generation uncertainty: The iTesla project approach

The secure integration of renewable generation into modern power systems requires an appropriate assessment of the security of the system in real-time. The uncertainty associated with renewable power makes it impossible to tackle this problem via a brute-force approach, i.e. it is not possible to run detailed online static or dynamic simulations for all possible security problems and realizations of load and renewable power. Intelligent approaches for online security assessment with forecast uncertainty modeling are being sought to better handle contingency events. This paper reports the platform developed within the iTesla project for online static and dynamic security assessment. This innovative and open-source computational platform is composed of several modules such as detailed static and dynamic simulation, machine learning, forecast uncertainty representation and optimization tools to not only filter contingencies but also to provide the best control actions to avoid possible unsecure situations. Based on High Performance Computing (HPC), the iTesla platform was tested in the French network for a specific security problem: overload of transmission circuits. The results obtained show that forecast uncertainty representation is of the utmost importance, since from apparently secure forecast network states, it is possible to obtain unsecure situations that need to be tackled in advance by the system operator

An Approach to Improve Multi objective Path Planning for Mobile Robot Navigation using the Novel Quadrant Selection Method

Currently, automated and semi-automated industries need multiple objective path planning algorithms for mobile robot applications. The multi-objective optimisation algorithm takes more computational effort to provide optimal solutions. The proposed grid-based multi-objective global path planning algorithm [Quadrant selection algorithm (QSA)] plans the path by considering the direction of movements from starting position to the target position with minimum computational effort. Primarily, in this algorithm, the direction of movements is classified into quadrants. Based on the selection of the quadrant, the optimal paths are identified. In obstacle avoidance, the generated feasible paths are evaluated by the cumulative path distance travelled, and the cumulative angle turned to attain an optimal path. Finally, to ease the robot’s navigation, the obtained optimal path is further smoothed to avoid sharp turns and reduce the distance. The proposed QSA in total reduces the unnecessary search for paths in other quadrants. The developed algorithm is tested in different environments and compared with the existing algorithms based on the number of cells examined to obtain the optimal path. Unlike other algorithms, the proposed QSA provides an optimal path by dramatically reducing the number of cells examined. The experimental verification of the proposed QSA shows that the solution is practically implementable

Autonomous Simultaneous Localization and Mapping driven by Monte Carlo uncertainty maps-based navigation

This paper addresses the problem of implementing a Simultaneous Localization and Mapping (SLAM) algorithm combined with a non-reactive controller (such as trajectory following or path following). A general study showing the advantages of using predictors to avoid mapping inconsistences in autonomous SLAM architectures is presented. In addition, this paper presents a priority-based uncertainty map construction method of the environment by a mobile robot when executing a SLAM algorithm. The SLAM algorithm is implemented with an extended Kalman filter (EKF) and extracts corners (convex and concave) and lines (associated with walls) from the surrounding environment. A navigation approach directs the robot motion to the regions of the environment with the higher uncertainty and the higher priority. The uncertainty of a region is specified by a probability characterization computed at the corresponding representative points. These points are obtained by a Monte Carlo experiment and their probability is estimated by the sum of Gaussians method, avoiding the time-consuming map-gridding procedure. The priority is determined by the frame in which the uncertainty region was detected (either local or global to the vehicle's pose). The mobile robot has a non-reactive trajectory following controller implemented on it to drive the vehicle to the uncertainty points. SLAM real-time experiments in real environment, navigation examples, uncertainty maps constructions along with algorithm strategies and architectures are also included in this work.Fil: Auat Cheein, Fernando Alfredo. Universidad Técnica Federico Santa María; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pereira, Fernando M. Lobo. Universidad de Porto; PortugalFil: Di Sciascio, Fernando Agustín. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Carelli Albarracin, Ricardo Oscar. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentin

Simultaneous Real-Time Detection of Motor Imagery and Error-Related Potentials for Improved BCI Accuracy

Brain-computer interfaces (BCIs), as any other interaction modality based on physiological signals and body channels (e.g., muscular activity, speech and gestures), are prone to errors in the recognition of subject's intent. An elegant approach to improve the accuracy of BCIs consists of a verification procedure directly based on the presence of error-related potentials (ErrP) in the EEG recorded right after the occurrence of an error. Two healthy volunteer subjects with little prior BCI experience participated in a real-time human-robot interaction experiment where they were asked to mentally move a cursor towards a target that can be reached within a few steps using motor imagery. These experiments confirm the previously reported presence of a new kind of ErrP. These Interaction ErrP exhibit a first sharp negative peak followed by a positive peak and a second broader negative peak ( 270,  330 and  430 ms after the feedback, respectively). The objective of the present study was to simultaneously detect erroneous responses of the interface and classifying motor imagery at the level of single trials in a real-time system. We have achieved online an average recognition rate of correct and erroneous single trials of 84.7% and 78.8%, respectively. The off-line post-analysis showed that the BCI error rate without the integration of ErrP detection is around 30% for both subjects. However, when integrating ErrP detection, the average online error rate drops to 7%, multiplying the bit rate by more than 3. These results show that it's possible to simultaneously extract in real-time useful information for mental control to operate a brain-actuated device as well as correlates of cognitive states such as error-related potentials to improve the quality of the brain-computer interaction

Parametric Analysis of Flexible Logic Control Model

Based on deep analysis about the essential relation between two input variables of normal two-dimensional fuzzy controller, we used universal combinatorial operation model to describe the logic relationship and gave a flexible logic control method to realize the effective control for complex system. In practical control application, how to determine the general correlation coefficient of flexible logic control model is a problem for further studies. First, the conventional universal combinatorial operation model has been limited in the interval [0,1]. Consequently, this paper studies a kind of universal combinatorial operation model based on the interval [a,b]. And some important theorems are given and proved, which provide a foundation for the flexible logic control method. For dealing reasonably with the complex relations of every factor in complex system, a kind of universal combinatorial operation model with unequal weights is put forward. Then, this paper has carried out the parametric analysis of flexible logic control model. And some research results have been given, which have important directive to determine the values of the general correlation coefficients in practical control application

Towards an Enhanced Wide Area Control System for Damping Out Low Frequency Oscillations in Power Grid

This thesis presents enhanced methodologies in a wide area control system to damp out low frequency oscillations. The primary motivation behind this work is to design a wide area controller to avoid power system blackouts by damping out low frequency oscillations which are existing for longer time duration. The wide area controller can be designed in two ways: state feedback control and output feedback control. From the input point of view, the state feedback controller requires the information about all system states and are not possible to observe all system states in real-time. From the output point of view, the output signals of the controller can be given to the AVR/excitation system of all generators in both control techniques which will increase the cost of the communication network. Moreover, the time delay due to the communication network will affect the wide are controller performance. Therefore, to overcome these problems, in particular, this work addresses the design of a wide area controller with limited measurements to resolve the input side problems. The problems associated with the output side can be overcome by employing a reduced- scale wide area controller design. In addition, the time delay effects can be resolved by using bi-layer wide area control architecture with the incorporation of the practical supplementary controller. The important contributions of this work are as follows. 1. Designing a wide area controller to damp out inter-area oscillations by consid- ering limited measurements with unknown load composition. 2. Designing a reduced-scale architecture of the wide area control system by means of modal sensitivity analysis. 3. Designing a practical supplementary controller design for the bi-layer wide area control architecture through structurally constrained H2-norm optimization. The contribution of the first work is to design a wide area controller with limited measurements without knowing load composition. The primary objective of this work is to design a state feedback controller to damp out the inter-area oscillations in the power system network with limited wide area measurements. The conventional state feedback controller designed through LQR optimization requires all the state variables as input. However, the dynamics of a power system is governed by a large number of state variables. Therefore, it is, practically, not possible to place sensors everywhere for monitoring the complete system state in real-time. To address the particular issue, an optimized state feedback controller is proposed, which can be implemented with the limited number of state inputs. The structurally constrained H2-norm optimization technique is employed to perform the proposed state feedback controller design. The reference frame requirement for defining the rotor angles of generators under the scenario of limited state observability is also investigated. The performance of the wide area controller with limited state inputs is verified through a case study on the New England 39-bus system under different scenarios of state unobservability. Since the WAC design requires a full system description, appropriate load modeling may be critical in the WAC design. Therefore, a mathematical framework is developed to carry out WAC design in the presence of multiple types of load. Both static and dynamic loads are considered. In order to exempt the dynamic load states from the input of WAC, the structurally constrained H2-norm optimized WAC design is performed. By recognizing the practical difficulty of obtaining the precise information about actual load composition, this work further investigates the suitability of representing all the loads as constant power loads in the WAC design. Detailed case studies are performed on the IEEE 39-bus system. The contribution of the second work is to develop an efficient scheme for the proper selection of entities in the wide area control (WAC) loop so as to yield a cost-effective and simplified WAC architecture without compromising with its damping performance. The methodology proposed is based upon a concept of mode-path susceptibility matrix that is obtained by means of the modal sensitivity analysis. Inspecific, the significance of a feedback path to change mode shapes is determined by evaluating the sensitivities of different modes to the respective elements of the feedback gain matrix. This is unlike the traditional controllability and observability based approaches. A generalized utility ranking of potential source and sink points of the wide area damping controller is further carried out based upon the mode- path susceptibility matrix. Both the state feedback and the output feedback are taken into account in the methodology proposed for the scale reduction of a WAC architecture. Detailed case studies are performed to verify the effectiveness of the proposed reduced-scale WAC architecture through both off-line simulations and real- time experimentations. The contribution of the third work is to develop a suitable methodology for the practical realization of the bi-layer wide area control (WAC) architecture. The bi-layer WAC system retains the capability to overcome the communication related problems to a great extent through the deployment of a supplementary wide area damping controller (WADC) along with the conventional WADC. The supplementary WADC was envisaged as a controller that may not have any communication requirements to deliver control signals. It is, therefore, essential to design the supplementary WADC in a way so that the same can be practically implemented without the requirement of any communication network. The precise concern of the present work is to address the proper design of the aforementioned supplementary WADC. The design of the supplementary WADC is carried out through a structurally constrained H2-norm optimization calculation. The solution procedure of the particular H2-norm optimization problem is established. Detailed simulation studies are performed to evaluate the performance of the proposed supplementary WADC in the standalone mode. The usefulness of the bi-layer WAC architecture to improve the damping of inter-area oscillations under the proposed controller design is thoroughly validated through real-time experimentations