Judging Time Intevals using a model of perceptuo-motor control

Estimating a time interval and temporally coordinating movements in space are fundamental skills, but the relationships between these different forms of timing, and the neural processes that they incur, are not well understood. While different theories have been proposed to account for time perception, time estimation, and the temporal patterns of coordination, there are no general mechanisms which unify these various timing skills. This study considers whether a model of perceptuo-motor timing, the tau(GUIDE), can also describe how certain judgements of elapsed time are made. To evaluate this, an equation for determining interval estimates was derived from the tau(GUIDE) model and tested in a task where participants had to throw a ball and estimate when it would hit the floor. The results showed that in accordance with the model, very accurate judgements could be made without vision (mean timing error -19.24 msec), and the model was a good predictor of skilled participants' estimate timing. It was concluded that since the tau(GUIDE) principle provides temporal information in a generic form, it could be a unitary process that links different forms of timing.

Detecting motor abnormalities in preterm infants

As a consequence of the fragility of various neural structures, preterm infants born at a low gestation and/or birthweight are at an increased risk of developing motor abnormalities. The lack of a reliable means of assessing motor integrity prevents early therapeutic intervention. In this paper, we propose a new method of assessing neonatal motor performance, namely the recording and subsequent analysis of intraoral sucking pressures generated when feeding nutritively. By measuring the infant's control of sucking in terms of a new development of tau theory, normal patterns of intraoral motor control were established for term infants. Using this same measure, the present study revealed irregularities in sucking control of preterm infants. When these findings were compared to a physiotherapist's assessment six months later, the preterm infants who sucked irregularly were found to be delayed in their motor development. Perhaps a goal-directed behaviour such as sucking control that can be measured objectively at a very young age, could be included as part of the neurological assessment of the preterm infant. More accurate classification of a preterm infant's movement abnormalities would allow for early therapeutic interventions to be realised when the infant is still acquiring the most basic of motor functions. (C) Springer-Verlag 2000.

Trajectory Control of Electro Hydraulic Excavator using Fuzzy Self Tuning Algorithm with Neural Network

This paper presents the trajectory control of a 2DOF mini electro-hydraulic excavator by using fuzzy self tuning with neural network algorithm. First, the mathematical model is derived for the 2DOF mini electro-hydraulic excavator. The fuzzy PID and fuzzy self tuning with neural network are designed for circle trajectory following. Its two links are driven by an electric motor controlled pump system. The experimental results demonstrated that the proposed controllers have better control performance than the conventional controller.

Performance assessment of cascade control loopswith non-Gaussian disturbances using entropy information

Cascade control is one of the routinely used control strategies in industrial processes because it can dramatically improve the performance of single-loop control, reducing both the maximum deviation and the integral error of the disturbance response. Currently, many control performance assessment methods of cascade control loops are developed based on the assumption that all the disturbances are subject to Gaussian distribution. However, in the practical condition, several disturbance sources occur in the manipulated variable or the upstream exhibits nonlinear behaviors. In this paper, a general and effective index of the performance assessment of the cascade control system subjected to the unknown disturbance distribution is proposed. Like the minimum variance control (MVC) design, the output variances of the primary and the secondary loops are decomposed into a cascade-invariant and a cascade-dependent term, but the estimated ARMA model for the cascade control loop based on the minimum entropy, instead of the minimum mean squares error, is developed for non-Gaussian disturbances. Unlike the MVC index, an innovative control performance index is given based on the information theory and the minimum entropy criterion. The index is informative and in agreement with the expected control knowledge. To elucidate wide applicability and effectiveness of the minimum entropy cascade control index, a simulation problem and a cascade control case of an oil refinery are applied. The comparison with MVC based cascade control is also included.

Wireless networked control systems with QoS-based sampling

Closing feedback loops using an IEEE 802.11b ad hoc wireless communication network incurs many challenges sensitivity to varying channel conditions and lower physical transmission rates tend to limit the bandwidth of the communication channel. Given that the bandwidth usage and control performance are linked, a method of adapting the sampling interval based on an 'a priori', static sampling policy has been proposed and, more significantly, assuring stability in the mean square sense using discrete-time Markov jump linear system theory. Practical issues including current limitations of the 802.11 b protocol, the sampling policy and stability are highlighted. Simulation results on a cart-mounted inverted pendulum show that closed-loop stability can be improved using sample rate adaptation and that the control design criteria can be met in the presence of channel errors and severe channel contention.

Neuromuscular and biomechanical factors codetermine the solution to motor redundancy in rhythmic multijoint arm movement

How the CNS deals with the issue of motor redundancy remains a central question for motor control research. Here we investigate the means by which neuromuscular and biomechanical factors interact to resolve motor redundancy in rhythmic multijoint arm movements. We used a two-df motorised robot arm to manipulate the dynamics of rhythmic flexion-extension (FE) and supination-pronation (SP) movements at the elbow-joint complex. Participants were required to produce rhythmic FE and SP movements, either in isolation, or in combination (at the phase relationship of their choice), while we recorded the activity of key bi-functional muscles. When performed in combination, most participants spontaneously produced an in-phase pattern of coordination in which flexion is synchronised with supination. The activity of the Biceps Brachii (BB), the strongest arm muscle which also has the largest moment arms in both flexion and supination was significantly higher for FE and SP performed in combination than in isolation, suggesting optimal exploitation of the mechanical advantage of this muscle. In a separate condition, participants were required to produce a rhythmic SP movement while a rhythmic FE movement was imposed by the motorised robot. Simulations based upon a musculoskeletal model of the arm demonstrated that in this context, the most efficient use of the force-velocity relationship of BB requires that an anti-phase pattern of coordination (flexion synchronized with pronation) be produced. In practice, the participants maintained the in-phase behavior, and BB activity was higher than for SP performed in isolation. This finding suggests that the neural organisation underlying the exploitation of bifunctional muscle properties, in the natural context, constrains the system to maintain the

Decoupled-DFIG fault ride-through strategy for enhanced stability performance during grid faults

This paper proposes a decoupled fault ride-through strategy for a doubly fed induction generator (DFIG) to enhance network stability during grid disturbances. The decoupled operation proposes that a DFIG operates as an induction generator (IG) with the converter unit acting as a reactive power source during a fault condition. The transition power characteristics of the DFIG have been analyzed to derive the capability of the proposed strategy under various system conditions. The optimal crowbar resistance is obtained to exploit the maximum power capability from the DFIG during decoupled operation. The methods have been established to ensure proper coordination between the IG mode and reactive power compensation from the grid-side converter during decoupled operation. The viability and benefits of the proposed strategy are demonstrated using different test network structures and different wind penetration levels. Control performance has been benchmarked against existing grid code standards and commercial wind generator systems, based on the optimal network support required (i.e., voltage or frequency) by the system operator from a wind farm installed at a particular location.

Position control of shape memory alloy actuators using self tuning fuzzy PID controller

Shape Memory Alloy (SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

Internal model control for shape memory alloy actuators using fuzzy based Preisach model

This paper investigates a possible application of Preisach model to control shape memory alloy (SMA) actuators using an internal model control strategy. The developed strategy consists in including the Preisach hysteresis model of SMA actuator and the inverse Preisach model within the control structure. In this work, an extrema input hystory and a fuzzy inference is utilized to replace the classical Preisach model. This allows to reduce a large amount of experimental parameters and computation time of the classical Preisach model. To demonstrate the effectiveness of the proposed controller in improving control performance and hysteresis compensation of SMA actuators, experimental results from real time control are presented.

Modelling and Control of Shape Memory Alloy Actuators by using Preisach Model, Genetic Algorithm and Fuzzy Logic

Shapememoryalloy (SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications in aeronautics, surgical tools, robotics and so on. Nonlinearity hysteresis effects existing in SMA actuators present a problem in the motion control of these smart actuators. This paper investigates the control problem of SMA actuators in both simulation and experiment. In the simulation, the numerical Preisachmodel with geometrical interpretation is used for hysteresis modeling of SMA actuators. This model is then incorporated in a closed loop PID control strategy. The optimal values of PID parameters are determined by using geneticalgorithm to minimize the mean squared error between desired output displacement and simulated output. However, the control performance is not good compared with the simulation results when these parameters are applied to the real SMA control since the system is disturbed by unknown factors and changes in the surrounding environment of the system. A further automated readjustment of the PID parameters using fuzzylogic is proposed for compensating the limitation. To demonstrate the effectiveness of the proposed controller, real time control experiment results are presented.

Time to get a move on:Overcoming bradykinetic movement in Parkinson's disease with artificial sensory guidance generated from biological motion

Paradoxical kinesia describes the motor improvement in Parkinson's disease (PD) triggered by the presence of external sensory information relevant for the movement. This phenomenon has been puzzling scientists for over 60 years, both in neurological and motor control research, with the underpinning mechanism still being the subject of fierce debate. In this paper we present novel evidence supporting the idea that the key to understanding paradoxical kinesia lies in both spatial and temporal information conveyed by the cues and the coupling between perception and action. We tested a group of 7 idiopathic PD patients in an upper limb mediolateral movement task. Movements were performed with and without a visual point light display, travelling at 3 different speeds. The dynamic information presented in the visual point light display depicted three different movement speeds of the same amplitude performed by a healthy adult. The displays were tested and validated on a group of neurologically healthy participants before being tested on the PD group. Our data show that the temporal aspects of the movement (kinematics) in PD can be moderated by the prescribed temporal information presented in a dynamic environmental cue. Patients demonstrated a significant improvement in terms of movement time and peak velocity when executing movement in accordance with the information afforded by the point light display, compared to when the movement of the same amplitude and direction was performed without the display. In all patients we observed the effect of paradoxical kinesia, with a strong relationship between the perceptual information prescribed by the biological motion display and the observed motor performance of the patients. © 2013 Elsevier B.V. All rights reserved.

Capability Curve Based Enhanced Reactive Power Control Strategy for Stability Enhancement and Network Voltage Management

Reactive power has become a vital resource in modern electricity networks due to increased penetration of distributed generation. This paper examines the extended reactive power capability of DFIGs to improve network stability and capability to manage network voltage profile during transient faults and dynamic operating conditions. A coordinated reactive power controller is designed by considering the reactive power capabilities of the rotor-side converter (RSC) and the grid-side converter (GSC) of the DFIG in order to maximise the reactive power support from DFIGs. The study has illustrated that, a significant reactive power contribution can be obtained from partially loaded DFIG wind farms for stability enhancement by using the proposed capability curve based reactive power controller; hence DFIG wind farms can function as vital dynamic reactive power resources for power utilities without commissioning additional dynamic reactive power devices. Several network adaptive droop control schemes are also proposed for network voltage management and their performance has been investigated during variable wind conditions. Furthermore, the influence of reactive power capability on network adaptive droop control strategies has been investigated and it has also been shown that enhanced reactive power capability of DFIGs can substantially improve the voltage control performance.

Design and Flux-Weakening Control of an Interior Permanent Magnet Synchronous Motor for Electric Vehicles

Permanent magnet synchronous motors (PMSMs) provide a competitive technology for EV traction drives owing to their high power density and high efficiency. In this paper, three types of interior PMSMs with different PM arrangements are modeled by the finite element method (FEM). For a given amount of permanent magnet materials, the V-shape interior PMSM is found better than the U-shape and the conventional rotor topologies for EV traction drives. Then the V-shape interior PMSM is further analyzed with the effects of stator slot opening and the permanent magnet pole chamfering on cogging torque and output torque performance. A vector-controlled flux-weakening method is developed and simulated in Matlab to expand the motor speed range for EV drive system. The results show good dynamic and steady-state performance with a capability of expanding speed up to four times of the rated. A prototype of the V-shape interior PMSM is also manufactured and tested to validate the numerical models built by the FEM.