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

aVsIs: An Analytical-Solution-Based Solver for Model-Predictive Control With Hexagonal Constraints in Voltage-Source Inverter Applications

The theory of a new analytical-solution-based algorithm for calculating the optimal solution in model-predictive control applications with hexagonal constraints is discussed in this article. Three-phase voltage-source inverters for power electronic and electric motor drive applications are the target of the proposed method. The indirect model-predictive control requires a constrained quadratic programming (QP) solver to calculate the optimal solution. Most of the QP solvers use numerical algorithms, which may result in unbearable computational burdens. However, the optimal constrained solution can be calculated in an analytical way when the control horizon is limited to the first step. A computationally efficient algorithm with a certain maximum number of operations is proposed in this article. A thorough mathematical description of the solver in both the stationary and rotating reference frames is provided. Experimental results on real test rigs featuring either an electricmotor or a resistive-inductive load are reported to demonstrate the feasibility of the proposed solver, thus smoothing theway for its implementation in industrial applications. The name of the proposed solver is aVsIs, which is released under Apache License 2.0 in GitHub, and a free example is available in Code Ocean

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

Restless Legs Syndrome: Known Knowns and Known Unknowns

Although restless legs syndrome (RLS) is a common neurological disorder, it remains poorly understood from both clinical and pathophysiological perspectives. RLS is classified among sleep-related movement disorders, namely, conditions characterized by simple, often stereotyped movements occurring during sleep. However, several clinical, neurophysiological and neuroimaging observations question this view. The aim of the present review is to summarize and query some of the current concepts (known knowns) and to identify open questions (known unknowns) on RLS pathophysiology. Based on several lines of evidence, we propose that RLS should be viewed as a disorder of sensorimotor interaction with a typical circadian pattern of occurrence, possibly arising from neurochemical dysfunction and abnormal excitability in different brain structures

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

Non-invasive brain stimulation for dystonia: therapeutic implications

Dystonia is characterized by excessive muscle contractions giving rise to abnormal posture and involuntary twisting movements. Although dystonia syndromes are a heterogeneous group of disorders, certain pathophysiological mechanisms have been consistently identified across different forms. These pathophysiological mechanisms have subsequently been exploited for the development of non‐invasive brain stimulation (NIBS) techniques able to modulate neural activity in one or more nodes of the putative network that is altered in dystonia, and the therapeutic role of NIBS has hence been suggested. Here all studies that applied such techniques as a therapeutic intervention in any forms of dystonia, including the few works performed in children, are reviewed and emerging concepts and pitfalls of NIBS are discussed