Magnetic Modelling of Synchronous Reluctance and Internal Permanent Magnet Motors Using Radial Basis Function Networks

The general trend toward more intelligent energy-aware ac drives is driving the development of new motor topologies and advanced model-based control techniques. Among the candidates, pure reluctance and anisotropic permanent magnet motors are gaining popularity, despite their complex structure. The availability of accurate mathematical models that describe these motors is essential to the design of any model-based advanced control. This paper focuses on the relations between currents and flux linkages, which are obtained through innovative radial basis function neural networks. These special drive-oriented neural networks take as inputs the motor voltages and currents, returning as output the motor flux linkages, inclusive of any nonlinearity and cross-coupling effect. The theoretical foundations of the radial basis function networks, the design hints, and a commented series of experimental results on a real laboratory prototype are included in this paper. The simple structure of the neural network fits for implementation on standard drives. The online training and tracking will be the next steps in field programmable gate array based control systems

Sensory-motor integration in focal dystonia.

Traditional definitions of focal dystonia point to its motor component, mainly affecting planning and execution of voluntary movements. However, focal dystonia is tightly linked also to sensory dysfunction. Accurate motor control requires an optimal processing of afferent inputs from different sensory systems, in particular visual and somatosensory (e.g., touch and proprioception). Several experimental studies indicate that sensory-motor integration - the process through which sensory information is used to plan, execute, and monitor movements - is impaired in focal dystonia. The neural degenerations associated with these alterations affect not only the basal ganglia-thalamic-frontal cortex loop, but also the parietal cortex and cerebellum. The present review outlines the experimental studies describing impaired sensory-motor integration in focal dystonia, establishes their relationship with changes in specific neural mechanisms, and provides new insight towards the implementation of novel intervention protocols. Based on the reviewed state-of-the-art evidence, the theoretical framework summarized in the present article will not only result in a better understanding of the pathophysiology of dystonia, but it will also lead to the development of new rehabilitation strategies

Energy-efficient autonomous solar water-pumping system for permanent-magnet synchronous motors

This paper presents a novel stand–alone solar– powered water pumping system, especially suited for usage in rural or remote areas. The system is primarily designed to reduce both cost and complexity, while simultaneously guaranteeing opti¬mal utilisation of the photovoltaic generator. The use of standard hardware and control architectures ensures ease of installation, service and maintenance. The proposed solution consists of a water pump driven by a permanent magnet synchronous motor (PMSM), controlled by a conventional field oriented control scheme. The photovoltaic array is directly connected to the DC bus of the inverter, with no intermediate power conversion stages. A perturbation based extremum–seeking controller adjusts the motor speed reference to attain the maximum power point opera-tion of the photovoltaic array. Both simulations and experimental results on a full-scale prototype support the effectiveness of the proposed system

Motor Parameter-Free Predictive Current Control of Synchronous Motors by Recursive Least-Square Self-Commissioning Model

This article deals with a finite-set model predictive current control in synchronous motor drives. The peculiarity is that it does not require the knowledge of any motor parameter. The inherent advantage of this method is that the control is self-adapting to any synchronous motor, thus easing the matching between motor and inverter coming from different manufacturers. Overcoming the flaws of the existing lookup table based parameter-free techniques, the article elaborates the past current measurements by a recursive least-square algorithm to estimate the future behavior of the current in response to a finite set of voltage vectors. The article goes through the mathematical basis of the algorithm till a complete set of experiments that prove the feasibility and the advantages of the proposed technique

An Effective Model-Free Predictive Current Control for Synchronous Reluctance Motor Drives

The performances of a model predictive control algorithm largely depend on the knowledge of the system model. A model-free predictive control approach skips all the effects of parameters variations or mismatches, as well as of model nonlinearity and uncertainties. A finite-set model-free current predictive control is proposed in this paper. The current variations predictions induced by the eight base inverter voltage vectors are estimated by means of the previous measurements stored into lookup tables. To keep the current variations information up to date, the three current measurements due to the three most recent feeding voltages are combined together to reconstruct all the others. The reconstruction is performed by taking advantage of the relationships between the three different base voltage vectors involved in the process. In particular, 210 possible combinations of three-state voltage vectors can be found, but they can be gathered together in six different groups. A light and computationally fast algorithm for the group identification is proposed in this paper. Finally, the current reconstruction for the prediction of future steps is thoroughly analyzed. A compensation of the motor rotation effect on the input voltages is proposed, too. The control scheme is evaluated by means of both simulation and experimental evidences on two different synchronous reluctance motors

How to understand it: Neuropsychological testing

Neuropsychological testing is a key diagnostic tool for assessing people with dementia and mild cognitive impairment, but can also help in other neurological conditions such as Parkinson’s disease, stroke, multiple sclerosis, traumatic brain injury and epilepsy. While cognitive screening tests offer gross information, detailed neuropsychological evaluation can provide data on different cognitive domains (visuospatial function, memory, attention, executive function, language and praxis) as well as neuropsychiatric and behavioural features. We should regard neuropsychological testing as an extension of the neurological examination applied to higher order cortical function, since each cognitive domain has an anatomical substrate. Ideally, neurologists should discuss the indications and results of neuropsychological assessment with a clinical neuropsychologist. This paper summarises the rationale, indications, main features, most common tests and pitfalls in neuropsychological evaluation

Impaired temporal processing of tactile and proprioceptive stimuli in cerebellar degeneration.

Performance of timed motor sequences relies on the cerebellum and basal ganglia, which integrate proprioceptive information during the motor task and set internal timing mechanisms. Accordingly, these structures are also involved in other temporal processes, such as the discrimination of the different afferent information in the domain of time. In the present study we tested temporal processing of proprioceptive and tactile stimuli in 20 patients with neurodegenerative cerebellar ataxia and 20 age- and sex-matched healthy subjects. Tactile temporal discrimination threshold was defined as the value at which subjects recognized the two stimuli as asynchronous. Temporal discrimination movement threshold of the first dorsal interosseous and flexor carpi radialis was defined as the shortest interval between two paired electrical stimuli in which the subjects blindfolded perceived two separate index finger abductions and wrist flexions. Both tactile and movement temporal discrimination thresholds were higher in patients with cerebellar ataxia. No correlation was found with disease duration and severity. Our study demonstrates that temporal processing of tactile and proprioceptive stimuli is impaired in patients with cerebellar neurodegeneration and highlights the involvement of cerebellum in temporal processing of somatosensory stimuli of different type