Changing Input Conditions Research Articles

Modified nondominated sorting genetic algorithm-based multiobjective optimization of a cross-coupled nonlinear PID controller for a Twin Rotor System

This paper presents an innovative nonlinear PID control scheme based on a modified nondominated sorting genetic algorithm validated using a laboratory helicopter model called the Twin Rotor System. The concepts of controlled elitism and dynamic crowding distance are incorporated into the proposed algorithm to progress towards the best solution from the entire population in order to solve the multiobjective optimization problem with good convergence characteristics. The addition of nonlinear functions to the cross-coupled PID controller structure initiates better error tracking and facilitates smooth output under changing input conditions. The design objective is to implement an optimal nonlinear PID control scheme for the angular displacements of the twin-rotor system, with integral square error and control energy taken as the multiobjective problems. The statistical performance of the controller is analyzed by considering the best, worst, mean, and standard deviations of ISE. In this work, simultaneous control of pitch and yaw angles is considered to get rid of the coupling effect between the two rotors. The results indicate the advantage of the MNGSA-based tuning for the two degrees of freedom MIMO control with standard reference trajectories as per the TRMS330-10 model.

Performance evaluation of a non linear PID controller using chaotic gravitational search algorithm for a twin rotor system

AbstractA novel strategy using a chaotic gravitational search algorithm (CGSA) based nonlinear PID control scheme, which is validated through a laboratory helicopter model called the twin rotor system, is presented in this paper. In this work, CGSA is used as a stochastic based global optimization algorithm for controller design in the twin rotor system adopted. The fine chaotic search process used in CGSA obtains the optimal solution in the iterative process based on the current best solution. The goal of the controller design in this paper is to stabilize the twin rotor system with considerable cross couplings to reach the selected position and follow the desired trajectory effectively. The addition of nonlinear functions to the PID controller structure initiates better error tracking and facilitates smooth output under changing input conditions. The design objective is to implement a nonlinear PID control scheme for the angular displacements of the twin rotor system with minimization of the integral square error (ISE) as the fitness function in the algorithm. The statistical performance of the controller is analyzed by considering the best, worst, mean, and standard deviations of ISE. In this work, simultaneous control of pitch and yaw angles is considered to get rid of the coupling effect between the two rotors. From the simulation results it is observed that the proposed work shows better performance than the other evolutionary computation techniques. The results also indicate the advantage of the proposed CGSA based tuning for the two degree of freedom MIMO control with standard reference trajectories as per the TRMS330‐10 model.

Studying the effect of changing Input conditions on MMF using MGDM technique

The mode group diversity multiplexing (MGDM) multicast technology uses optical multiple input and output (O-MIMO) technology to provide greater capacity and the ability to transmit information over multi-mode fiber (MMF). The MGDM system has a benefit in terms of capacity expansion, which led to interest in its use in most optical communications. The MGDM exploits the optical fiber bandwidth by inserting spatial light detection, which increases the capacity of the MMF. This research aims to study the optical systems used for the MGDM technology, and to identify the methods of their analysis and design of O-MIMO systems to increase the amplitude of this signal. The conditions of light entry into the optical fiber such as typical spot size, radial displacements, angle, wavelength, and radius of the detectors sections are improved. Numerical MATLAB simulation is used to improve the amplitude of graded index multimode fiber (GI-MMF) and compared to the existing aggregation systems. Moreover, this method was simulated to improve the input and detection conditions to increase the O-MIMO capacity using the MGDM technique. Finally, the capacity of the MGDM system was studied and compared with different channels, and it is noticed that the capacity of the system increases with increasing the number of channels.

Representational dynamics preceding conscious access

Our senses are continuously bombarded with more information than our brain can process up to the level of awareness. The present study aimed to enhance understanding on how attentional selection shapes conscious access under conditions of rapidly changing input. Using an attention task, EEG, and multivariate decoding of individual target- and distractor-defining features, we specifically examined dynamic changes in the representation of targets and distractors as a function of conscious access and the task-relevance (target or distractor) of the preceding item in the RSVP stream. At the behavioral level, replicating previous work and suggestive of a flexible gating mechanism, we found a significant impairment in conscious access to targets (T2) that were preceded by a target (T1) followed by one or two distractors (i.e., the attentional blink), but striking facilitation of conscious access to targets shown directly after another target (i.e., lag-1 sparing and blink reversal). At the neural level, conscious access to T2 was associated with enhanced early- and late-stage T1 representations and enhanced late-stage D1 representations, and interestingly, could be predicted based on the pattern of EEG activation well before T1 was presented. Yet, across task conditions, we did not find convincing evidence for the notion that conscious access is affected by rapid top-down selection-related modulations of the strength of early sensory representations induced by the preceding visual event. These results cannot easily be explained by existing accounts of how attentional selection shapes conscious access under rapidly changing input conditions, and have important implications for theories of the attentional blink and consciousness more generally.

Имитационная модель фотодизельной системы электроснабжения с интеллектуальным управлением в Matlab/Simulink

In this article, a simulation model of an autonomous PVdiesel power supply (PDPS) system with direct current is considered. The autonomous PDPS is implemented in the Simulink programming environment of the Matlab software package. The system includes: a photovoltaic power station (PPS), a diesel generator (DG), an energy storage system (ESS), a remote consumer as well as auxiliary converters. The PDPS model makes it possible to analyze the energy balance between generation, consumption, and the energy exchange available from the ESS connected via a DC bus (DCB). With the help of the proposed model, it is possible to analyze and optimize the technical and economic indicators of DC power plants with the priority of the PPS contribution: reducing the consumption of diesel fuel and carbonation of the air reducing the cost of 1 kWh for the remote consumer and controlling the switching in the power plants as per logical conditions. The obtained technical and economic indicators of the PDPS using direct current are superior to similar systems based on alternating current due to an increase in the contribution of the PPS to the energy balance. As a result of experiments with changing input conditions, i.e. annual changes in insolation and temperature at different latitudes, the authors justify technical, economic, and environmental criteria for the effectiveness of decision-making and recommendations for the design and operation of PDPS power plants. Intelligent algorithms for effective control of PV-diesel power systems based on DC are developed and suggested

CAPSA Based Control for Power Quality Correction in PV Array Integrated EVCS Operating in Standalone and Grid Connected Modes

In this article, a solar photo voltaic (PV) array and a storage battery integrated three phase electric vehicle charging station (EVCS) is presented, which uses a convex combined affine projection sign algorithm (APSA) for improving the power quality at the grid. This algorithm convexly combines the output of two APSA with large step size and small step size. Therefore, this algorithm achieves fast convergence and low steady-state error in abruptly changing input conditions. Therefore, this algorithm is suitable for an EVCS, where the charging current of EV changes frequently. The EVCS provides both ac and dc charging to EVs. In the daytime, the CS operates in standalone mode to charge the EV connected at the point of common interconnection (PCI). However, the EV requiring dc power can take power from the dc link through a bidirectional dc-dc converter. Whereas, in the absence of PV array generation, the CS takes power from the grid. Moreover, while connecting the CS to the grid, the PCI voltage is synchronized to the grid voltage for achieving the seamless mode transition. Various steady-state and dynamic condition results have been taken on the experimental prototype developed in the laboratory for demonstrating its satisfactory behavior.

A novel adaptive fuzzy-based sliding mode control for channel state estimation in cognitive radio for reduction of interference

Research in spectrum availability and its effective utilisation is becoming an epicentre of research in recent times with the increasing scarcity of radio spectrum. An effective solution is in the form of cognitive radios (CRs) which are quite intelligent to effectively utilise the scarcely available spectrum in an efficient and economic manner. Apart from being intelligent, they represent reconfigurable wireless communication systems, which are self-aware of their environment and learn to adapt it for dynamic changes. They are characteristic of efficient spectrum utilisation. This research paper defines the objective of determining the channel state information through sliding model control-based intelligent adaptive fuzzy algorithm. The CR has ability to operate in a particular radio configuration based on device status and environmental aspects including interference noise. The proposed adaptive fuzzy SMC-based channel state estimation has been compared against conventional and recent techniques and outputs established in terms of bit error rate and mean squared error. The proposed sliding rule method is quite an ideal choice for the proposed scenario characterised by dynamically changing input conditions to the sensing components of the CR network.

Comparison of typical control laws of crushing unit on the example of a jaw crusher

To control the jaw crusher in a constantly changing input conditions, various types of typical regulators are used. It is necessary to take into account the fact that a modern jaw crushing machine is not only an element of the crushing and screening complex, but is also a system per se. Each element of this system has a certain isolation, up to the presence of an independent safety device in each subsystem. Safety devices are, for example, a toggle plate belonging to the protection devices of the mechanical subsystem, or a crusher drive control system based on monitoring the basic parameters of the electric drive belonging to the protection devices of the electrical subsystem. When controlling the mechanical subsystem, the values change proportionally, but in the control system of electric drive parameters their values change according to the type of controller used. When using the P-controller, the amount of correction to the control action is proportional to the deviation. The PI-controller provides a change in the magnitude of the correction to the control action not only in proportion to the magnitude of the deviation, but also depending on the accumulated action of the deviation of the controlled variable. The PID-controller takes into account not only the accumulated value of the controlled variable, but also the rate of its change. The parameters of the regulators were adopted by the method of Ziegler-Nichols. It is shown that each of the model regulators has its drawbacks, which may be insignificant during operation.

Real-Time Simulation of Smart DC Microgrid with Decentralized Control System Under Source Disturbances

Decentralized control of DC microgrid (dcµG) using hybrid renewable energy sources (RES) and battery energy storage system (BESS) which operate with and without grid-connected mode is proposed in this paper. In dcµG integrated with multiple RES and BESS, fluctuating output characteristics of the distributed generations (DGs) due to changing input conditions and the dynamic interactions of the source and load interface converters are main factors which cause stability problem of DC bus voltage. Thus, to solve this problem, the decentralized control scheme which uses bus voltage level as communication link in the control law is proposed in this paper. Accordingly, the control method realizes different operating modes based on the available generations and load demand. Maximum power and constant voltage controls schemes are applied in the DGs interfacing control to regulate the power and voltage variations due to changing input conditions. Furthermore, in the control strategy, the source and battery interfacing converters are controlled autonomously using the bus voltage level without any communication. This maintains the reliability and flexibility of the system. The proposed system model is developed with Matlab/Simulink SimPowerSystem and simulated with real-time simulation using OPAL-RT.

A novel approach to improve the planning of adaptive and interactive sessions for the treatment of Major Depression

Human Computer Interaction (HCI) is a research field which aims to improve the relationship between users and interactive computer systems. A main objective of this research area is to make the user experience more pleasant and efficient, minimizing the barrier between the users' cognition of what they want to accomplish and the computer's understanding of the user's tasks, by means of user-friendly, useful and usable designs. A bad HCI design is one of the main reasons behind user rejection of computer-based applications, which in turn produces loss of productivity and economy in industrial environments.In the eHealth domain, user rejection of computer-based systems is a major barrier to exploiting the maximum benefit from those applications developed to support the treatment of diseases, and in the worst cases a poor design in these systems may cause deterioration in the clinical condition of the patient. Thus, a high level of personalisation of the system according to users' needs is extremely important, making it easy to use and contributing to the system's efficacy, which in turn facilitates the empowerment of the target users. Ideally, the content offered through the interactive sessions in these applications should be continuously assessed and adapted to the changing condition of the patient. A good HCI design and development can improve the acceptance of these applications and contribute to promoting better adherence levels to the treatment, preventing the patient from further relapses.In this work, we present a mechanism to provide personalised and adaptive daily interactive sessions focused on the treatment of patients with Major Depression. These sessions are able to automatically adapt the content and length of the sessions to obtain personalised and varied sessions in order to encourage the continuous and long-term use of the system. The tailored adaptation of session content is supported by decision-making processes based on: (i) clinical requirements; (ii) the patient's historical data; and (iii) current responses from the patient. We have evaluated our system through two different methodologies: the first one performing a set of simulations producing different sessions from changing input conditions, in order to assess different levels of adaptability and variability of the session content offered by the system. The second evaluation process involved a set of patients who used the system for 14-28 days and answered a questionnaire to provide feedback about the perceived level of adaptability and variability produced by the system. The obtained results in both evaluations indicated good levels of adaptability and variability in the content of the sessions according to the input conditions. We present an HCI-based framework for the treatment of patients with Major Depression.The framework provides adaptive and personalised plans of therapeutic-based sessions.The Intelligent framework reacts according to the individual condition of the patient.Its functionality was evaluated using a relevant set of simulations and real patients.The developed framework can be adapted as a CDSS addressing mental health disorders.

Excursion-Free Dynamic Wavelength Switching in Amplified Optical Networks

Dynamic optical networking with rapid wavelength reconfiguration is a promising capability to support the heterogeneous, bursty traffic rapidly growing in metro-area networks. A major obstacle to realizing dynamicity in the optical layer is the channel power excursions that occur due to continuously changing input conditions into gain controlled optical amplifiers. Here we present a technique of distributing an optical signal across multiple wavelengths chosen to reduce or cancel the power dynamics so that excursion-free switching can be achieved in an optically amplified transparent network. The use of variable wavelength dwell times for excursion-free switching using arbitrary wavelength pairs is presented. Spectral efficiency lost in utilizing multiple wavelengths is recovered through time-division multiplexing two signals distributed over the same wavelengths.

Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity.

Winner-Take-All (WTA) networks are recurrently connected populations of excitatory and inhibitory neurons that represent promising candidate microcircuits for implementing cortical computation. WTAs can perform powerful computations, ranging from signal-restoration to state-dependent processing. However, such networks require fine-tuned connectivity parameters to keep the network dynamics within stable operating regimes. In this article, we show how such stability can emerge autonomously through an interaction of biologically plausible plasticity mechanisms that operate simultaneously on all excitatory and inhibitory synapses of the network. A weight-dependent plasticity rule is derived from the triplet spike-timing dependent plasticity model, and its stabilization properties in the mean-field case are analyzed using contraction theory. Our main result provides simple constraints on the plasticity rule parameters, rather than on the weights themselves, which guarantee stable WTA behavior. The plastic network we present is able to adapt to changing input conditions, and to dynamically adjust its gain, therefore exhibiting self-stabilization mechanisms that are crucial for maintaining stable operation in large networks of interconnected subunits. We show how distributed neural assemblies can adjust their parameters for stable WTA function autonomously while respecting anatomical constraints on neural wiring.

Matching of feedback inhibition with excitation ensures fidelity of information flow in the anterior piriform cortex

Odor-evoked responses in mitral cells of the olfactory bulb are characterized by prolonged patterns of action potential (spike) activity. If downstream neurons are to respond to each spike in these patterns, the duration of the excitatory response to one spike should be limited, enabling cells to respond to subsequent spikes. To test for such mechanisms, we performed patch-clamp recordings in slices of the mouse anterior piriform cortex. Mitral cell axons in the lateral olfactory tract (LOT) were stimulated electrically at different intensities and with various frequency patterns to mimic changing input conditions that the piriform cortex likely encounters in vivo. We found with cell-attached measurements that superficial pyramidal (SP) cells in layer 2 consistently responded to LOT stimulation across conditions with a limited number (1–2) of spikes per stimulus pulse. The key synaptic feature accounting for the limited spike number appeared to be somatic inhibition derived from layer 3 fast-spiking cells. This inhibition tracked the timing of the first spike in SP cells across conditions, which naturally limited the spike number to 1–2. These response features to LOT stimulation were, moreover, not unique to SP cells, also occurring in a population of fluorescently labeled interneurons in glutamic acid decarboxylase 65-eGFP mice. That these different cortical cells respond to incoming inputs with 1–2 spikes per stimulus may be especially critical for relaying bulbar information contained in synchronized oscillations at beta (15–30Hz) or gamma (30–80Hz) frequencies.

Auditory plasticity and sensorimotor learning in speech production

Numerous studies have shown the speech motor system to be highly flexible and responsive to changes in sensory input, revealing a central role for both auditory and somatosensory feedback in the acquisition and maintenance of speech motor control. Consistent with these studies, models of speech production have highlighted the role of accurate, stable sensory representations that serve, in part, as the goals of speech movements. A separate (and considerable) body of work has demonstrated that auditory-sensory representations of speech sounds are not perfectly stable, but rather exhibit rapid adaptation to changing input conditions in both children and adults. The plasticity of auditory representations has important implications for the control of speech production, both in early speech motor development and in the sensory-based maintenance of speech accuracy that characterizes adult speech motor control. In this talk, I will describe a series of studies that explore the link between sensory and motor plasticity in the speech motor system. The studies combine the paradigm of sensorimotor adaptation (altering auditory feedback during speech production) with measures and manipulations of auditory-perceptual representations of speech sounds. The results reveal not only that auditory speech targets are flexible under conditions of altered auditory feedback, but that changes in sensory representations can have a direct impact on speech motor learning and performance.

The Supply of Inorganic Fertilizers to Smallholder Farmers in Tanzania: Evidence for Fertilizer Policy Development

Inorganic fertilizer is one of a handful of agricultural technologies that have immense potential for raising the productivity of poor smallholders, enabling them to increase income, accumulate assets, and set themselves economically on a pathway out of poverty. The very low prevalence of fertilizer use by Mozambican farmers — below five percent — is evidence that farmers find it difficult to access fertilizers for their crops at a price that will allow them to obtain sufficient and reliable returns from their investment in fertilizer.This paper presents the results of a broad study of fertilizer supply to smallholder farmers in Mozambique that was done to assess whether the taxes (explicit or implicit) that are applied at various points along the fertilizer importation and marketing chain, or the absence of key public goods and services, reduces the access that smallholder farmers have to fertilizer. The study involved a review of the literature of fertilizer supply, demand, and use; interviews with key participants in fertilizer importation and marketing in Mozambique; and two surveys — one with farmers and the other with input suppliers — in two farming areas where more fertilizer is used than is the norm for the country as a whole.The government of Mozambique has adopted a generally hands-off approach in engaging with efforts to improve farmer access to fertilizer. Private-sector investment decisions drive the development of input markets, with government primarily having somewhat distant oversight. Fertilizer costs are high in Mozambique relative to costs in other coastal countries in Africa. Efforts are being started to strengthen the retail sector of agricultural inputs by better understanding the information and management needs of agricultural input retailers, but much work is still required in this regard.However, given the problematic economics of fertilizer use by smallholders in Mozambique, the prospects for sharp increases in fertilizer use in the future are certainly much murkier there than elsewhere in Africa. Nonetheless, government can take two fertilizer-specific initiatives to accelerate use of fertilizer in Mozambique by smallholders: 1. Overcoming information constraints that smallholder farmers who might use fertilizer face. This includes both information on the proper agronomic use of the appropriate types of fertilizer on specific crops under specific agroecological conditions and information on the proper economic use of fertilizer under changing input and output market conditions so that farmers can derive reliable profits from their use of the technology. 2. Regulatory reform. The fertilizer regulations currently being proposed for Mozambique, if comprehensively implemented, would be a poor fit for the public benefits sought through the regulations. A considerably lighter regulatory regime would allow more fertilizer into Mozambique, resulting in lower costs for farmers. The Ministry of Agriculture should be judicious in its implementation of this legislation. Efforts to assure the quality of fertilizers in open and competitive markets are best achieved through self-regulation processes tied to sufficient information on product quality for farmers and ample choice in suppliers, rather than through heavy regulation and costly enforcement.

Numerical Simulation of a 4-Day Early Spring Storm Period in the Black Hills

This paper illustrates the potential for mesoscale models to depict the distribution of precipitation in orographic situations. The study covers a 4-day time period in April 1995. The domain of the numerical model covers much of western South Dakota and some of eastern Wyoming and is centered on the Black Hills of South Dakota. The 4-day storm period is characterized by changing atmospheric conditions, from primarily rain generation to snowfall production. Observations and climatic data of precipitation are analyzed to compare with model predictions. The model demonstrated the ability to respond appropriately to changing input conditions and produced reasonably accurate simulations of observed precipitation patterns. The model performed well for sufficiently cold, strongly forced conditions but seemed overly sensitive to the accuracy of model assumptions regarding ice initiation for warmer, weakly forced situations.

A low-cost digital signal processor-based ear-muff with adaptive active noise control

This paper presents the design and implementation of a digital signal processor (DSP)-based feed-forward narrow-band noise canceling system using the Analog Devices ADSP-2181 EZ-KIT Lite developer's kit. The theory of adaptive noise control (ANC) is applied to an ear-muff so that the entire system combines both passive and active techniques to reduce the harmful acoustic noise emitted by machinery and engines. The ANC developed uses a 100-tap finite impulse response (FIR) filter which encompasses the least mean square (LMS) and normalised LMS (NLMS) algorithms to adaptively `track' changing input conditions. The hardware and software aspects for real-time implementation, the signal conditioning circuits and the software developed for stereo multiplexing in the EZ-KIT Lite environment are presented. Performance results show significant improvements in noise attenuation levels when compared to use of a purely passive technique.

Polyphase adaptive filter banks for fingerprintimagecompression

A perfect reconstruction polyphase filter bank structure is presented in which the filters adapt to the changing input conditions. The use of such a filter bank leads to higher compression results for images containing sharp edges such as fingerprint images.

Real-Time Physiconeural Solutions for MOCVD

This paper presents an integrated physiconeural network approach for the modeling and optimization of a vertical MOCVD reactor. The basic concept is to utilize the solutions obtained from a physical model to build an accurate neural network (NN) model The resulting model has the attractive features of self-adaptiveness and speed of prediction and is an ideal starting tool for process optimization and control. Following this approach, a first-principles physical model for the reactor was solved numerically using the Fluid Dynamics Analysis Package (FIDAP). This transient model included property variation and thermodiffusion effects. Using software developed in house, neural networks were then trained using FIDAP simulations for combinations of process parameters determined by the statistical Design of Experiments (DOE) methodology. The outputs were the average and local deposition rates. It is shown that the trained NN model predicts the behavior of the reactor accurately. Optimum process conditions to obtain a uniform thickness of the deposited film were determined and tested using the physical model. The results demonstrate the power and robustness of NNs for obtaining fast responses to changing input conditions. A procedure for developing equipment models based on physiconeural network models is also described.

Interaction Between Concurrent Transactions in the Design of Distributed Databases

ABSTRACTA distributed database system allows concurrent execution of transactions from multiple users at multiple locations. This paper presents a general scheme of including the effect of interaction between such transactions in the design process of distributed databases. This scheme allows the decision maker to choose the most appropriate design for a distributed database. The interaction effect is a consequence of concurrency control procedures and contention for system resources. Prior research has not included all components of the interaction effect in the design process. A separate module, called an interaction module, was built to measure the interaction effect using a comprehensive simulation model of a general purpose relational distributed database management system (DBMS). The interaction module can be interfaced with any distributed database design system as an add‐on module so that the interaction effect can be included in the design process. A detailed example demonstrates the use of the interaction module in the decision‐making process. Experiments conducted using the module show that the interaction effect can be significant and that it can affect the choice of the design. Experiments were also conducted to measure the sensitivity of design choices under changing input conditions.