Linear-like policy iteration based optimal control for continuous-time nonlinear systems

We propose a novel strategy to construct optimal controllers for continuous-time nonlinear systems by means of linear-like techniques, provided that the optimal value function is differentiable and quadratic-like . This assumption covers a wide range of cases and holds locally around an equilibrium under mild assumptions. The proposed strategy does not require solving the Hamilton-Jacobi-Bellman equation, that is a nonlinear partial differential equation, which is known to be hard or impossible to solve. Instead, the Hamilton-Jacobi-Bellman equation is replaced with an easy-solvable state-dependent Lyapunov matrix equation. We exploit a linear-like factorization of the underlying nonlinear system and a policy-iteration algorithm to yield a linear-like policy-iteration for nonlinear systems. The proposed control strategy solves optimal nonlinear control problems in an asymptotically exact, yet still linear-like manner. We prove optimality of the resulting solution and illustrate the results via four examples

Heterogeneous network flow and Petri nets characterize multilayer complex networks

Interacting subsystems are commonly described by networks, where multimodal behaviour found in most natural or engineered systems found recent extension in form of multilayer networks. Since multimodal interaction is often not dictated by network topology alone and may manifest in form of cross-layer information exchange, multilayer network flow becomes of relevant further interest. Rationale can be found in most interacting subsystems, where a form of multimodal flow across layers can be observed in e.g., chemical processes, energy networks, logistics, finance, or any other form of conversion process relying on the laws of conservation. To this end, the formal notion of heterogeneous network flow is proposed, as a multilayer flow function aligned with the theory of network flow. Furthermore, dynamic equivalence is established with the framework of Petri nets, as the baseline model of concurrent event systems. Application of the resulting multilayer Laplacian flow and flow centrality is presented, along with graph learning based inference of multilayer relationships over multimodal data. On synthetic data the proposed framework demonstrates benefits of multimodal flow derivation in critical component identification. It also displays applicability in relationship inference (learning based function approximation) on multimodal time series. On real-world data the proposed framework provides, among others, multimodal flow interpretation of U.S. economic activity, uncovering underlying empirical steady state probability distribution, as well as inherent network (economic) robustness

Risk-sensitive motion planning for MAVs based on mission-related fault-tolerant analysis

Multirotor Aerial Vehicles may be fault-tolerant by design when rotor-failure is possible to measure or identify, especially when a large number of rotors are used. For instance, an octocopter can be capable to complete some missions even when a double-rotor fault occurs during the execution. In this paper, we study how a rotor-failure reduces the vehicle control admissible set and its importance with respect to the selected mission, i.e. we perform mission-related fault-tolerant analysis. Furthermore, we propose a risk-sensitive motion-planning algorithm capable to take into account the risks during the planning stage by means of mission-related fault-tolerant analysis. We show that the proposed approach is much less conservative in terms of selected performance measures than a conservative risk planner that assumes that the considered fault will certainly occur during the mission execution. As expected, the proposed risk-sensitive motion planner is also readier for accepting failures during the mission execution than the risk-insensitive approach that assumes no failure will occur

Biatrial Remodeling in Patients with Cystic Fibrosis

BACKGROUND: Previous studies have focused on left and right ventricular remodeling in cystic fibrosis (CF), whereas atrial function has not been assessed in detail so far. We sought to investigate left and right atrial (LA and RA) function in patients with CF. METHODS: This retrospective investigation included 82 CF patients (64 survivors and 18 non-survivors) who were referred to CF department over the period of four years, as well as 32 control subjects matched by age and gender. All participants underwent an echocardiographic examination including a strain analysis, which was performed offline and blinded for groups. RESULTS: LA and RA volume indexes were significantly higher in CF patients than in controls and were particularly high in CF non-survivors. LA conduit and reservoir functions were significantly worse in CF survivors and non-survivors, compared with control subjects. RA phasic function was not different between controls, CF survivors and non-survivors. The parameters of lung function (forced vital capacity (FVC) and forced expiratory volume in the first second (FEV1)) and the LA and RA volume indexes were predictors of mortality in CF patients. However, in a multivariate analysis, only FVC was an independent predictor of mortality in CF patients. CONCLUSIONS: Our results suggest that both atria are enlarged, but only LA function is impaired in CF patients. LA reservoir and conduit function is particularly deteriorated in CF patients. Though statistical significance was not reached due to our limited sample size, there was a trend of deterioration of LA and RA function from controls across CF survivors to CF non-survivors. LA and RA enlargement represented predictors of mortality in CF patients

Towards the Implementation of a MPC-based Planner on an Autonomous All-Terrain Vehicle

Planning and control for a wheeled mobile robot are challenging problems when poorly traversable terrains, including dynamic obstacles, are considered. To accomplish a mission, the control system should firstly guarantee the vehicle integrity, for example with respect to possible roll-over/tip-over phenomena. A fundamental contribution to achieve this goal, however, comes from the planner as well. In fact, computing a path that takes into account the terrain traversability, the kinematic and dynamic vehicle constraints, and the presence of dynamic obstacles, is a first and crucial step towards ensuring the vehicle integrity. The present paper addresses some of the aforementioned issues, describing the hardware/software architecture of the planning and control system of an autonomous All-Terrain Mobile Robot and the implementation of a real-time path planner

Teachers’ Perception of Aggressive Behaviour in Children: Case of Bosnia and Herzegovina

Aggressive behaviour in children and youth is a widespread phenomenon. Antisocial behaviour that includes certain kind of aggressive behaviour can occur and disappear again during a child’s development. However, from a psychological perspective aggression can be one of the problematic types of behaviour in children with long-lasting negative consequences.The aim of this research is to examine teachers’ perceptions of the types of aggressive behaviour as well as to find out the causes for the development of aggressiveness in school-age children in Bosnia and Herzegovina (BiH) from teacher’s point of view. In order to define and classify the types of aggressive behavior in school age children in BiH, descriptive method was used. For understanding phenomena of aggression and identification of its cause(s), explanatory method was used. In order to examine teachers’ perceptions of the types of aggressive behaviour as well as the causes for the development of aggressiveness, assessment scales for teachers’ perceptions were used.The research findings indicate that proactive, reactive, and relational types of aggression are most often seen in school-age children from teachers’ perceptions. The causes of aggressive behaviour range widely: Aggressive behaviour occurs as a combination of internal impulses and external stimuli or triggers that indicate possible aggression so temperament as well as environmental factors can influence the development of aggressiveness; aggressive behaviour is acquired through learning   by observing and imitating model; the role of parents and their way of disciplining a child is  another important cause; the mass media is seen as important cause of aggressive behaviour

Earliest Memories, Positive Emotional Memories of Warmth and Safeness, and Attachment Style in Adolescent

Research has shown that early childhood experiences, especially those related to feelings of threat or safeness play a key role in subsequent emotional and social development. The aims of the study are to explore the relationship between early memories of warmth and safeness and attachment style in adolescents (1) and to define specificities of earliest memories with regard to the current attachment style(2). In order to explore relationships between earliest memories, emotional memories of warmth and safeness, and current attachment style of adolescents, a convenient sample of 167 public secondary school students with average age of 17,22 years of whom 63.47% females, was included in the research. The questionnaire included Early Memories of Warmth and Safeness Scale (EMWSS; Richter, Gilbert & McEwan, 2009), Memory Characteristics Questionnaire (Johnson, Suenghas, Foley & Raye, 1988) and Adult Attachment Questionnaire (Hazan & Shaver, 1990). Research findings proved that emotional content of adolescents` earliest memories is predominantly of joy (41.7%), fear (23.3%), sadness (8.6%), surprise (8%), anger (7.4%), etc. which is in line with previous research using same or similar methodology. Approximation of the first memory is at 4.7 years of age, with no significant difference between males and females. However, females described their first memory in significantly more words than males (t=-3.77, p0,05). Research findings are discussed in light of current research in the field, and recommendations for future studies are given

Long-term dynamics of aberrant neuronal activity in awake Alzheimer's disease transgenic mice

Alzheimer's disease (AD) is associated with aberrant neuronal activity, which is believed to critically determine disease symptoms. How these activity alterations emerge, how stable they are over time, and whether cellular activity dynamics are affected by the amyloid plaque pathology remains incompletely understood. We here repeatedly recorded the activity from identified neurons in cortex of awake APPPS1 transgenic mice over four weeks during the early phase of plaque deposition using in vivo two-photon calcium imaging. We found that aberrant activity during this stage largely persisted over the observation time. Novel highly active neurons slowly emerged from former intermediately active neurons. Furthermore, activity fluctuations were independent of plaque proximity, but aberrant activity was more likely to persist close to plaques. These results support the notion that neuronal network pathology observed in models of cerebral amyloidosis is the consequence of persistent single cell aberrant neuronal activity, a finding of potential diagnostic and therapeutic relevance for AD