Peak-to-Peak Output Current Ripple Analysis in Multiphase and Multilevel Inverters

Analysis of the peak-to-peak output current ripple amplitude for multiphase and multilevel inverters is presented in this PhD thesis. The current ripple is calculated on the basis of the alternating voltage component, and peak-to-peak value is defined by the current slopes and application times of the voltage levels in a switching period. Detailed analytical expressions of peak-to-peak current ripple distribution over a fundamental period are given as function of the modulation index. For all the cases, reference is made to centered and symmetrical switching patterns, generated either by carrier-based or space vector PWM. Starting from the definition and the analysis of the output current ripple in three-phase two-level inverters, the theoretical developments have been extended to the case of multiphase inverters, with emphasis on the five- and seven-phase inverters. The instantaneous current ripple is introduced for a generic balanced multiphase loads consisting of series RL impedance and ac back emf (RLE). Simplified and effective expressions to account for the maximum of the output current ripple have been defined. The peak-to-peak current ripple diagrams are presented and discussed. The analysis of the output current ripple has been extended also to multilevel inverters, specifically three-phase three-level inverters. Also in this case, the current ripple analysis is carried out for a balanced three-phase system consisting of series RL impedance and ac back emf (RLE), representing both motor loads and grid-connected applications. The peak-to-peak current ripple diagrams are presented and discussed. In addition, simulation and experimental results are carried out to prove the validity of the analytical developments in all the cases. The cases with different phase numbers and with different number of levels are compared among them, and some useful conclusions have been pointed out. Furthermore, some application examples are given.

Induction of Hebbian associative plasticity through paired non-invasive brain stimulation of premotor-motor areas to elucidate the network's functional role

The ventral premotor cortex (PMv) is believed to play a pivotal role in a multitude of visuomotor behaviors, such as sensory-guided goal-directed visuomotor transformations, arbitrary visuomotor mapping, and hyper-learnt visuomotor associations underlying automatic imitative tendencies. All these functions are likely carried out through the copious projections connecting PMv to the primary motor cortex (M1). Yet, causal evidence investigating the functional relevance of the PMv-M1 network remains elusive and scarce. In the studies reported in this thesis we addressed this issue using a transcranial magnetic stimulation (TMS) protocol called cortico-cortical paired associative stimulation (ccPAS), which relies on multisite stimulation to induce Hebbian spike-timing dependent plasticity (STDP) by repeatedly stimulating the pathway connecting two target areas to manipulate their connectivity. Firstly, we show that ccPAS protocols informed by both short- and long-latency PMv-M1 interactions effectively modulate connectivity between the two nodes. Then, by pre-activating the network to apply ccPAS in a state-dependent manner, we were able to selectively target specific functional visuo-motor pathways, demonstrating the relevance of PMv-M1 connectivity to arbitrary visuomotor mapping. Subsequently, we addressed the PMv-to-M1 role in automatic imitation, and demonstrated that its connectivity manipulation has a corresponding impact on automatic imitative tendencies. Finally, by combining dual-coil TMS connectivity assessments and ccPAS in young and elderly individuals, we traced effective connectivity of premotor-motor networks and tested their plasticity and relevance to manual dexterity and force in healthy ageing. Our findings provide unprecedent causal evidence of the functional role of the PMv-to-M1 network in young and elderly individuals. The studies presented in this thesis suggest that ccPAS can effectively modulate the strength of connectivity between targeted areas, and coherently manipulate a networks’ behavioral output. Results open new research prospects into the causal role of cortico-cortical connectivity, and provide necessary information to the development of clinical interventions based on connectivity manipulation.