Feedforward Control of Shape Memory Alloy Actuators Using Fuzzy-Based Inverse Preisach Model

This brief investigates a possible application of the inverse Preisach model in combination with the feedforward and feedback control strategies to control shape memory alloy actuators. In the feedforward control design, a fuzzy-based inverse Preisach model is used to compensate for the hysteresis nonlinearity effect. An extrema input history and a fuzzy inference is utilized to replace the inverse classical Preisach model. This work allows for a reduction in the number of experimental parameters and computation time for the inversion of the classical Preisach model. A proportional-integral-derivative (PID) controller is used as a feedback controller to regulate the error between the desired output and the system output. To demonstrate the effectiveness of the proposed controller, real-time control experiment results are presented.

Stability Analysis and Implementation of a Decentralized Formation Control Strategy for Unmanned Vehicles

This paper presents a new methodology for solving the multi-vehicle formation control problem. It employs a unique extension-decomposition-aggregation scheme to transform the overall complex formation control problem into a group of subproblems, which work via boundary interactions or disturbances. Thus, it is proved that the overall formation system is exponentially stable in the sense of Lyapunov, if all the individual augmented subsystems (IASs) are stable. Linear matrix inequality-based H8 control methodology is employed to design the decentralized formation controllers to reject the impact of the formation changes being treated as boundary disturbances and guarantee the stability of all the IASs, consequently maintaining the stability of the overall formation system. Simulation studies are performed to verify the stability, performance, and effectiveness of the proposed strategy.

Modelling and Control of a Variable-Speed Switched Reluctance Generator based Wind Turbine

This paper studies the system modelling and control aspects of switched reluctance generator (SRG) based variable speed wind turbines. A control system is implemented to provide proper operation of the SRG as well as power tracking capabilities for varying wind speeds. The control system for the grid side inverter that will allow the SRG to properly generate power to the system is also presented. Studies are presented of both the SRG and inverter control systems capabilities during a balanced three-phase fault. The paper will demonstrate that the SRG based wind turbine presents a feasible variable wind speed solution with good fault response capabilities.

Using Graphs to Visualise and Detect Anomalies in Access Control System Transactions

Physical Access Control Systems are commonly used to secure doors in buildings such as airports, hospitals, government buildings and offices. These systems are designed primarily to provide an authentication mechanism, but they also log each door access as a transaction in a database. Unsupervised learning techniques can be used to detect inconsistencies or anomalies in the mobility data, such as a cloned or forged Access Badge, or unusual behaviour by staff members. In this paper, we present an overview of our method of inferring directed graphs to represent a physical building network and the flows of mobility within it. We demonstrate how the graphs can be used for Visual Data Exploration, and outline how to apply algorithms based on Information Theory to the graph data in order to detect inconsistent or abnormal behaviour.

Automatic extruder for processing recycled polymers with ultrasound and temperature control system

Melt viscosity is one of the main factors affecting product quality in extrusion processes particularly with regard to recycled polymers. However, due to wide variability in the physical properties of recycled feedstock, it is difficult to maintain the melt viscosity during extrusion of polymer blends and obtain good quality product without generating scrap. This research investigates the application of ultrasound and temperature control in an automatic extruder controller, which has ability to maintain constant melt viscosity from variable recycled polymer feedstock during extrusion processing. An ultrasonic modulation system has been developed and fitted to the extruder prior to the die to convey ultrasonic energy from a high power ultrasonic generator to the polymer melt. Two separate control loops have been developed to run simultaneously in one controller: the first loop controls the ultrasonic energy or temperature to maintain constant die pressure, the second loop is used to control extruder screw speed to maintain constant throughput at the extruder die. Time response and energy consumption of the control methods in real-time experiments are also investigated and reported this paper.

Free-roaming dogs control activities in one Italian province (2000-2013): Is the implemented approach effective?

In Italy, standards for the management of free-roaming dogs (FRDs) are defined by regional norms, generating a high variability of approaches around the country. Despite efforts carried out by the competent authorities, FRDs are still a reality impacting upon animal health and welfare and public costs. A similar scenario can be found in many other Mediterranean and Balkan counties. Here we present 14 years of data (2000–2013) retrieved from the admission dog registry of a public shelter (PS) responsible for the collection of stray dogs from one Italian province. The aim of this retrospective study was to describe the local FRD population, identifying its source and to evaluate the effectiveness of the actions implemented by the local authorities. In the investigated period, 7,475 dogs were admitted to the PS. Despite the intense sterilisation plan (mean 381.7 sterilisations per year), the overall number of dogs entering PS did not decrease consistently across the years. Results highlighted a lack of responsibility of owners by failing to sterilise and identify their dogs and allowing intact animals to roam free, therefore producing uncontrolled and unwanted litters. The current dog population management strategy, based on both sheltering and capture-neuter-release programmes, is insufficient to tackle the straying phenomenon. Educational and sterilisation programmes should be an integral part of a successfully implemented FRD control plan. Our results provide further insight on free-roaming dog population dynamics and control systems, and may have important implications for many other local contexts across Europe trying to overcome the straying phenomenon.

A Constrained Optimization Approach to Dynamic State Estimation for Power Systems Including PMU and Missing Measurements.

In this brief, a hybrid filter algorithm is developed to deal with the state estimation (SE) problem for power systems by taking into account the impact from the phasor measurement units (PMUs). Our aim is to include PMU measurements when designing the dynamic state estimators for power systems with traditional measurements. Also, as data dropouts inevitably occur in the transmission channels of traditional measurements from the meters to the control center, the missing measurement phenomenon is also tackled in the state estimator design. In the framework of extended Kalman filter (EKF) algorithm, the PMU measurements are treated as inequality constraints on the states with the aid of the statistical criterion, and then the addressed SE problem becomes a constrained optimization one based on the probability-maximization method. The resulting constrained optimization problem is then solved using the particle swarm optimization algorithm together with the penalty function approach. The proposed algorithm is applied to estimate the states of the power systems with both traditional and PMU measurements in the presence of probabilistic data missing phenomenon. Extensive simulations are carried out on the IEEE 14-bus test system and it is shown that the proposed algorithm gives much improved estimation performances over the traditional EKF method.

Dependable wireless real-time communications for open environments

Wireless communication technologies have become widely adopted, appearing in heterogeneous applications ranging from tracking victims, responders and equipments in disaster scenarios to machine health monitoring in networked manufacturing systems. Very often, applications demand a strictly bounded timing response, which, in distributed systems, is generally highly dependent on the performance of the underlying communication technology. These systems are said to have real-time timeliness requirements since data communication must be conducted within predefined temporal bounds, whose unfulfillment may compromise the correct behavior of the system and cause economic losses or endanger human lives. The potential adoption of wireless technologies for an increasingly broad range of application scenarios has made the operational requirements more complex and heterogeneous than before for wired technologies. On par with this trend, there is an increasing demand for the provision of cost-effective distributed systems with improved deployment, maintenance and adaptation features. These systems tend to require operational flexibility, which can only be ensured if the underlying communication technology provides both time and event triggered data transmission services while supporting on-line, on-the-fly parameter modification. Generally, wireless enabled applications have deployment requirements that can only be addressed through the use of batteries and/or energy harvesting mechanisms for power supply. These applications usually have stringent autonomy requirements and demand a small form factor, which hinders the use of large batteries. As the communication support may represent a significant part of the energy requirements of a station, the use of power-hungry technologies is not adequate. Hence, in such applications, low-range technologies have been widely adopted. In fact, although low range technologies provide smaller data rates, they spend just a fraction of the energy of their higher-power counterparts. The timeliness requirements of data communications, in general, can be met by ensuring the availability of the medium for any station initiating a transmission. In controlled (close) environments this can be guaranteed, as there is a strict regulation of which stations are installed in the area and for which purpose. Nevertheless, in open environments, this is hard to control because no a priori abstract knowledge is available of which stations and technologies may contend for the medium at any given instant. Hence, the support of wireless real-time communications in unmanaged scenarios is a highly challenging task. Wireless low-power technologies have been the focus of a large research effort, for example, in the Wireless Sensor Network domain. Although bringing extended autonomy to battery powered stations, such technologies are known to be negatively influenced by similar technologies contending for the medium and, especially, by technologies using higher power transmissions over the same frequency bands. A frequency band that is becoming increasingly crowded with competing technologies is the 2.4 GHz Industrial, Scientific and Medical band, encompassing, for example, Bluetooth and ZigBee, two lowpower communication standards which are the base of several real-time protocols. Although these technologies employ mechanisms to improve their coexistence, they are still vulnerable to transmissions from uncoordinated stations with similar technologies or to higher power technologies such as Wi- Fi, which hinders the support of wireless dependable real-time communications in open environments. The Wireless Flexible Time-Triggered Protocol (WFTT) is a master/multi-slave protocol that builds on the flexibility and timeliness provided by the FTT paradigm and on the deterministic medium capture and maintenance provided by the bandjacking technique. This dissertation presents the WFTT protocol and argues that it allows supporting wireless real-time communication services with high dependability requirements in open environments where multiple contention-based technologies may dispute the medium access. Besides, it claims that it is feasible to provide flexible and timely wireless communications at the same time in open environments. The WFTT protocol was inspired on the FTT paradigm, from which higher layer services such as, for example, admission control has been ported. After realizing that bandjacking was an effective technique to ensure the medium access and maintenance in open environments crowded with contention-based communication technologies, it was recognized that the mechanism could be used to devise a wireless medium access protocol that could bring the features offered by the FTT paradigm to the wireless domain. The performance of the WFTT protocol is reported in this dissertation with a description of the implemented devices, the test-bed and a discussion of the obtained results.

Genetic programming and bacterial algorithm for neural networks and fuzzy systems design

In the field of control systems it is common to use techniques based on model adaptation to carry out control for plants for which mathematical analysis may be intricate. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this line, this paper gives a perspective on the quality of results given by two different biologically connected learning algorithms for the design of B-spline neural networks (BNN) and fuzzy systems (FS). One approach used is the Genetic Programming (GP) for BNN design and the other is the Bacterial Evolutionary Algorithm (BEA) applied for fuzzy rule extraction. Also, the facility to incorporate a multi-objective approach to the GP algorithm is outlined, enabling the designer to obtain models more adequate for their intended use.

An overview of nonlinear identification and control with neural networks.

The aim of this chapter is to introduce background concepts in nonlinear systems identification and control with artificial neural networks. As this chapter is just an overview, with a limited page space, only the basic ideas will be explained here. The reader is encouraged, for a more detailed explanation of a specific topic of interest, to consult the references given throughout the text. Additionally, as general books in the field of neural networks, the books by Haykin [1] and Principe et al. [2] are suggested. Regarding nonlinear systems identification, covering both classical and neural and neuro-fuzzy methodologies, Reference 3 is recommended. References 4 and 5 should be used in the context of B-spline networks.

Temperature, pH, and conductivity control of the nutrient solution of an hydroponic greenhouse

One of the aspects of modern agriculture is characterised by a culture without soil (hydroponic cultures). These culture techniques are identified by possessing automatic control systems to control the nutrient solution. In first hydroponic cultures this control was accomplished by “on- off” analog controllers that applied a single control law implemented in hardware. Therefore, the changes of the control law resulted in the change of all interface electronics. In digital control implemented by micro-controllers the alteration of such control law is easily performed by changing only a computer program, leaving untouched all the interface hardware. In this way, the use and substitution of the control strategy is improved, as well, the use of advanced control strategies.

Adaptive generalized predictive control algorithm implemented over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Improving quality-of-service in wireless sensor networks by mitigating “Hidden-Node Collisions”

Wireless sensor networks (WSNs) emerge as underlying infrastructures for new classes of large-scale networked embedded systems. However, WSNs system designers must fulfill the quality-of-service (QoS) requirements imposed by the applications (and users). Very harsh and dynamic physical environments and extremely limited energy/computing/memory/communication node resources are major obstacles for satisfying QoS metrics such as reliability, timeliness, and system lifetime. The limited communication range of WSN nodes, link asymmetry, and the characteristics of the physical environment lead to a major source of QoS degradation in WSNs-the ldquohidden node problem.rdquo In wireless contention-based medium access control (MAC) protocols, when two nodes that are not visible to each other transmit to a third node that is visible to the former, there will be a collision-called hidden-node or blind collision. This problem greatly impacts network throughput, energy-efficiency and message transfer delays, and the problem dramatically increases with the number of nodes. This paper proposes H-NAMe, a very simple yet extremely efficient hidden-node avoidance mechanism for WSNs. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes that scales to multiple clusters via a cluster grouping strategy that guarantees no interference between overlapping clusters. Importantly, H-NAMe is instantiated in IEEE 802.15.4/ZigBee, which currently are the most widespread communication technologies for WSNs, with only minor add-ons and ensuring backward compatibility with their protocols standards. H-NAMe was implemented and exhaustively tested using an experimental test-bed based on ldquooff-the-shelfrdquo technology, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. H-NAMe effectiveness was also demonstrated in a target tracking application with mobile robots - over a WSN deployment.