Super-twisting sliding mode control for neutral point voltage of three-phase four-wire inverter based on SiC/Si hybrid switch.

The three-phase four-wire voltage source inverter (3P4W VSI) is widely used in applications like uninterrupted power supply (UPS) and bidirectional onboard charger. The increasing power density demand requires higher switching frequency and lower switching loss. To fulfill the conflicting objectives, two-fold methodology is proposed in this paper: 1) SiC/Si hybrid switches (HyS) together with recently reported gate trigger are reported for the first time in the 3P4W VSI; 2) the natural point voltage is controlled to track a sinusoidal voltage with the frequency equal to 3 times of fundamental frequency in order to achieve higher DC-bus voltage utilization rate, and further reduce the switching loss. The traditional PI controller is very hard to achieve desired performance due to both the nonlinearity and the variant reference of the natural point voltage control system. Thereby, the super-twisting sliding mode control (ST-SMC) is proposed in this paper to achieve desired tracking performance and fast dynamic response. The effectiveness and superiority of the system are verified by both simulation and experiment comparison with the existing methods using a 5 kW prototype.

Robust model predictive power control for three-phase VSRs under unbalanced grid.

The unbalanced grid voltage and circuit parameter uncertainty are two main obstacles for three phase voltage source rectifiers (VSRs) to achieve high performance in the practical applications. According to the instantaneous power model of the three-phase VSRs, six power components have to be well-regulated using only four available current manipulated variables, which is a typical underactuated problem. The model predictive control (MPC) provides a unified framework to regulate six power components simultaneously. However, how to balance the six power components control efforts is a challenge task. Meanwhile, the predictive model maybe inaccurate because of circuit parameters uncertainty, which degrades the performance of the MPC as well. In this paper, a robust model predictive power control (RMPPC) method is proposed for the three-phase VSRs to overcome above twice obstacles. The contributions of the work are: (1) The proposed method achieves the balance six power components control of the three-phase VSRs under unbalanced grid by using the off-line optimized weights; (2) a soft robust item with time variant boundary is proposed to achieve robust predictive model to deal with parameter uncertainty. Comparing with the existing voltage oriented control (VOC), direct power control (DPC) and model predictive control (MPC) methods, the proposed method achieves the best power quality in the sense of highest power factor and the lowest power oscillation in experiment, which verify the superiority of the proposed method.

Bi-directional impulse chaos control in crystal growth.

Mono-silicon crystals, free of defects, are essential for the integrated circuit industry. Chaotic swing in the flexible shaft rotating-lifting (FSRL) system of the mono-silicon crystal puller causes harm to the quality of the crystal and must be suppressed in the crystal growth procedure. From the control system viewpoint, the constraints of the FSRL system can be summarized as not having measurable state variables for state feedback control, and only one parameter is available to be manipulated, namely, the rotation speed. From the application side, an additional constraint is that the control should affect the crystallization physical growth process as little as possible. These constraints make the chaos suppression in the FSRL system a challenging task. In this work, the analytical periodic solution of the swing in the FSRL system is derived using perturbation analysis. A bi-directional impulse control method is then proposed for suppressing chaos. This control method does not alter the average rotation speed. It is thus optimum regarding the crystallization process as compared with the single direction impulse control. The effectiveness and the robustness of the proposed chaos control method to parameter uncertainties are validated by the simulations.

Rössler-network with time delay: Univariate impulse pinning synchronization.

Rössler had a brilliant and successful life as a scientist during which he published a benchmark dynamical system by using an electronic circuit interpreting chemical reactions. This is our contribution to honor his splendid erudite career. It is a hot topic to regulate a network behavior using the pinning control with respect to a small set of nodes in the network. Besides pinning to a small number of nodes, small perturbation to the node dynamics is also demanded. In this paper, the pinning synchronization of a coupled Rössler-network with time delay using univariate impulse control is investigated. Using the Lyapunov theory, a theorem is proved for the asymptotic stability of synchronization in the network. Simulation is given to validate the correctness of the analysis and the effectiveness of the proposed univariate impulse pinning controller.

Hyperchaos synchronization using univariate impulse control.

Rössler and Chen systems with time delay are shown to be hyperchaotic, which exhibits a more complex dynamics, including multiple positive Lyapunov exponents and infinite dimension. The hyperchaos has better application potential where hyperchaos synchronization is concerned. Univariate impulse control requires smaller perturbation to the response system, thus promising better performance. However, synchronization of two hyperchaotic systems using this control method is a challenging task due to the difficulty to guarantee synchronization stability using a minimum number of manipulated variables. In this paper, a univariate impulse control method is proposed for the synchronization of two hyperchaotic dynamics generated by time delay. A theorem is developed and proved to provide the sufficient conditions for the synchronization of time delay systems using the univariate impulse control. The upper bound of the impulse interval is proved to guarantee the asymptotic synchronization. Simulation and circuit experiment show the correctness of the analysis and the feasibility of the proposed method.

Spike-burst chimera states in an adaptive exponential integrate-and-fire neuronal network.

Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is composed of coupled adaptive exponential integrate-and-fire neurons that are connected by means of chemical synapses. In our neuronal network, the chimera states exhibit spatial structures both with spike and burst activities. Furthermore, those desynchronized domains not only have either spike or burst activity, but we show that the structures switch between spikes and bursts as the time evolves. Moreover, we verify the existence of multicluster chimera states.

Self-adaptation of chimera states.

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of "intelligence" in achieving robustness through self-adaptation. The behavior can be exploited for the controlled generation of chimera states with their coherent component placed in any desired spatial region of the system.

Understanding Robust Adaptation Dynamics of Gene Regulatory Network.

Robust adaptation is a critical attribute for gene regulatory network (GRN), understanding the relationship between adaptation and the GRN topology, and corresponding parameters is a challenging issue. The work in this paper includes: first, seven constraint multiobjective optimization algorithms are used to find sufficient solutions to get more reliable statistic rules. Meanwhile, the algorithms are compared to facilitate the future algorithm selection; second, a fuzzy c-mean algorithm is used to analyze solutions and to classify the solutions into different groups; third, the histogram analysis for all satisfactory solutions shows the preferred parameter range, i.e., parameter motif. The contributions of this paper includes: 1) Two new adaptation indices i.e., peak time and settle down time, are proposed for the first time to give more accurate description of the robust adaptation. Our conclusion is that some solutions even with satisfactory sensitivity and precision are not practically of robust adaptation because of too long time needed. 2) The relationship between topology, parameter set, and robust adaptation of GRN is discovered in the sense of both preferred topology and parameter motif. Our conclusion is that the robust adaptation depends more on the GRN topology than the model parameter set in two feasible topologies.

Weak connections form an infinite number of patterns in the brain.

Recently, much attention has been paid to interpreting the mechanisms for memory formation in terms of brain connectivity and dynamics. Within the plethora of collective states a complex network can exhibit, we show that the phenomenon of Collective Almost Synchronisation (CAS), which describes a state with an infinite number of patterns emerging in complex networks for weak coupling strengths, deserves special attention. We show that a simulated neuron network with neurons weakly connected does produce CAS patterns, and additionally produces an output that optimally model experimental electroencephalograph (EEG) signals. This work provides strong evidence that the brain operates locally in a CAS regime, allowing it to have an unlimited number of dynamical patterns, a state that could explain the enormous memory capacity of the brain, and that would give support to the idea that local clusters of neurons are sufficiently decorrelated to independently process information locally.

Stevioside induced cytotoxicity in colon cancer cells via reactive oxygen species and mitogen-activated protein kinase signaling pathways-mediated apoptosis.

The role of mitogen-activated protein kinase (MAPK) signaling pathways in cell growth and differentiation has been well established. The present study aimed to investigate the anti-proliferative effect of stevioside on human colon cancer HT-29 cells. Additionally, the effect of stevioside on cell cycle arrest and MAPK signaling pathways in HT-29 cells was explored. Stevioside was observed to significantly inhibit cancer cell growth at a dose of 5 µM at 48 and 72 h. A dose-dependent increase in the apoptosis rate was observed with cell cycle arrest at G2/M phase. In addition, caspase-9 and caspase-3 activity also increased. An increase in reactive oxygen species (ROS) production and a decrease in the mitochondrial membrane potential indicated that the mitochondrial-mediated intrinsic pathway is responsible for apoptotic activity. These results were additionally verified by the elevated expression level of phosphorylated p38 and extracellular signal-regulated kinase mitogen-activated protein kinases (MAPKs). Additionally, by inhibiting ROS production and MAPK activation, the antiproliferative effect of stevioside was suppressed, confirming the hypothesis that ROS and MAPK proteins induce apoptosis in human colon cancer HT-29 cells.

Tumour chemotherapy strategy based on impulse control theory.

Chemotherapy is a widely accepted method for tumour treatment. A medical doctor usually treats patients periodically with an amount of drug according to empirical medicine guides. From the point of view of cybernetics, this procedure is an impulse control system, where the amount and frequency of drug used can be determined analytically using the impulse control theory. In this paper, the stability of a chemotherapy treatment of a tumour is analysed applying the impulse control theory. The globally stable condition for prescription of a periodic oscillatory chemotherapeutic agent is derived. The permanence of the solution of the treatment process is verified using the Lyapunov function and the comparison theorem. Finally, we provide the values for the strength and the time interval that the chemotherapeutic agent needs to be applied such that the proposed impulse chemotherapy can eliminate the tumour cells and preserve the immune cells. The results given in the paper provide an analytical formula to guide medical doctors to choose the theoretical minimum amount of drug to treat the cancer and prevent harming the patients because of over-treating.This article is part of the themed issue 'Horizons of cybernetical physics'.

Chaos-based wireless communication resisting multipath effects.

In additive white Gaussian noise channel, chaos has been shown to be the optimal coherent communication waveform in the sense of using a very simple matched filter to maximize the signal-to-noise ratio. Recently, Lyapunov exponent spectrum of the chaotic signals after being transmitted through a wireless channel has been shown to be unaltered, paving the way for wireless communication using chaos. In wireless communication systems, inter-symbol interference caused by multipath propagation is one of the main obstacles to achieve high bit transmission rate and low bit-error rate (BER). How to resist the multipath effect is a fundamental problem in a chaos-based wireless communication system (CWCS). In this paper, a CWCS is built to transmit chaotic signals generated by a hybrid dynamical system and then to filter the received signals by using the corresponding matched filter to decrease the noise effect and to detect the binary information. We find that the multipath effect can be effectively resisted by regrouping the return map of the received signal and by setting the corresponding threshold based on the available information. We show that the optimal threshold is a function of the channel parameters and of the information symbols. Practically, the channel parameters are time-variant, and the future information symbols are unavailable. In this case, a suboptimal threshold is proposed, and the BER using the suboptimal threshold is derived analytically. Simulation results show that the CWCS achieves a remarkable competitive performance even under inaccurate channel parameters.

Experimental validation of wireless communication with chaos.

The constraints of a wireless physical media, such as multi-path propagation and complex ambient noises, prevent information from being communicated at low bit error rate. Surprisingly, it has only recently been shown that, from a theoretical perspective, chaotic signals are optimal for communication. It maximises the receiver signal-to-noise performance, consequently minimizing the bit error rate. This work demonstrates numerically and experimentally that chaotic systems can in fact be used to create a reliable and efficient wireless communication system. Toward this goal, we propose an impulsive control method to generate chaotic wave signals that encode arbitrary binary information signals and an integration logic together with the match filter capable of decreasing the noise effect over a wireless channel. The experimental validation is conducted by inputting the signals generated by an electronic transmitting circuit to an electronic circuit that emulates a wireless channel, where the signals travel along three different paths. The output signal is decoded by an electronic receiver, after passing through a match filter.

Finding Robust Adaptation Gene Regulatory Networks Using Multi-Objective Genetic Algorithm.

Robust adaptation plays a key role in gene regulatory networks, and it is thought to be an important attribute for the organic or cells to survive in fluctuating conditions. In this paper, a simplified three-node enzyme network is modeled by the Michaelis-Menten rate equations for all possible topologies, and a family of topologies and the corresponding parameter sets of the network with satisfactory adaptation are obtained using the multi-objective genetic algorithm. The proposed approach improves the computation efficiency significantly as compared to the time consuming exhaustive searching method. This approach provides a systemic way for searching the feasible topologies and the corresponding parameter sets to make the gene regulatory networks have robust adaptation. The proposed methodology, owing to its universality and simplicity, can be used to address more complex issues in biological networks.

[Efficacy of compound Xiatianwu tablets in elderly patients with osteoporotic distal radius fractures].

Xiatianwu tablet is based on the theory of traditional Chinese medicine (TCM), combined with modern TCM pharmacology and selected 33 famous traditional Chinese crude drugs to compose. Its recipe helps cure rheumatism, relax tendons, promote blood circulation to relieve pain, et al. Although Xiatianwu tablets are widely applied to clinical remedy such as rheumatic arthritis, lumbar disc hernia, osteoarthritis and so on, there is no report about its application in fracture. This article is to observe the efficacy of compound Xiatianwu tablets in elderly patients with osteoporotic distal radius fractures and its impact on the wrist function and complications. 180 elderly patients with osteoporotic distal radius fractures, from January 2011 to June 2014, were divided into observation group and control group by the method of random number table, each group had 90 cases. The control group were gave Caltrate D after manipulative reduction and plaster immobilization, observation group were treated with compound Xiatianwu tablets in the basis of the control group. Efficacy, wrist function and complication rates were observed in two groups after treatment. The excellent and good rate was 95.56% in observation group better than 77.78% in control group, the difference was statistically significant (χ2 = 4.712, P < 0.05). The complication rate in observation group was significantly lower compared with the control group (P < 0.05). This study shows that compound Xiatianwu tablets can improve the efficacy in elderly patients with osteoporotic distal radius fractures, reduce the incidence of complications and relieve the pain of patients which plays a significant role in improving the quality of life.

Wireless communication with chaos.

The modern world fully relies on wireless communication. Because of intrinsic physical constraints of the wireless physical media (multipath, damping, and filtering), signals carrying information are strongly modified, preventing information from being transmitted with a high bit rate. We show that, though a chaotic signal is strongly modified by the wireless physical media, its Lyapunov exponents remain unaltered, suggesting that the information transmitted is not modified by the channel. For some particular chaotic signals, we have indeed proved that the dynamic description of both the transmitted and the received signals is identical and shown that the capacity of the chaos-based wireless channel is unaffected by the multipath propagation of the physical media. These physical properties of chaotic signals warrant an effective chaos-based wireless communication system.

Collective almost synchronisation in complex networks.

This work introduces the phenomenon of Collective Almost Synchronisation (CAS), which describes a universal way of how patterns can appear in complex networks for small coupling strengths. The CAS phenomenon appears due to the existence of an approximately constant local mean field and is characterised by having nodes with trajectories evolving around periodic stable orbits. Common notion based on statistical knowledge would lead one to interpret the appearance of a local constant mean field as a consequence of the fact that the behaviour of each node is not correlated to the behaviours of the others. Contrary to this common notion, we show that various well known weaker forms of synchronisation (almost, time-lag, phase synchronisation, and generalised synchronisation) appear as a result of the onset of an almost constant local mean field. If the memory is formed in a brain by minimising the coupling strength among neurons and maximising the number of possible patterns, then the CAS phenomenon is a plausible explanation for it.