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Parameter influence on passive dynamic walking of a robot with flat feet

Xiangze Lin, Haibo Du, Shihua Li (2013)

Kybernetika

The biped robot with flat feet and fixed ankles walking down a slope is a typical impulsive dynamic system. Steady passive gaits for such mechanism can be induced on certain shallow slopes without actuation. The steady gaits can be described by using stable non-smooth limit cycles in phase plane. In this paper, it is shown that the robot gaits are affected by three parameters, namely the ground slope, the length of the foot, and the mass ratio of the robot. As the ground slope is gradually increased,...

Parametrization and geometric analysis of coordination controllers for multi-agent systems

Xiaoli Wang, Yiguang Hong (2009)

Kybernetika

In this paper, we address distributed control structures for multi-agent systems with linear controlled agent dynamics. We consider the parametrization and related geometric structures of the coordination controllers for multi-agent systems with fixed topologies. Necessary and sufficient conditions to characterize stabilizing consensus controllers are obtained. Then we consider the consensus for the multi-agent systems with switching interaction topologies based on control parametrization.

Past, Present and Future of Brain Stimulation

J. Modolo, R. Edwards, J. Campagnaud, B. Bhattacharya, A. Beuter (2010)

Mathematical Modelling of Natural Phenomena

Recent technological advances including brain imaging (higher resolution in space and time), miniaturization of integrated circuits (nanotechnologies), and acceleration of computation speed (Moore’s Law), combined with interpenetration between neuroscience, mathematics, and physics have led to the development of more biologically plausible computational models and novel therapeutic strategies. Today, mathematical models of irreversible medical conditions...

Performance analysis of least squares algorithm for multivariable stochastic systems

Ziming Wang, Yiming Xing, Xinghua Zhu (2023)

Kybernetika

In this paper, we consider the parameter estimation problem for the multivariable system. A recursive least squares algorithm is studied by minimizing the accumulative prediction error. By employing the stochastic Lyapunov function and the martingale estimate methods, we provide the weakest possible data conditions for convergence analysis. The upper bound of accumulative regret is also provided. Various simulation examples are given, and the results demonstrate that the convergence rate of the...

Periodic coordination in hierarchical air defence systems

Piotr Arabas, Krzysztof Malinowski (2001)

International Journal of Applied Mathematics and Computer Science

The subject of this work is the defence planning of a point target against an air attack. The defence system is decomposed into a number of sectors. A direct method of coordination is used at the upper level, while the sectors use a discrete-time event-based model and the description of uncertainty by multiple scenarios of an attack. The resulting problems are solved using linear programming. A comparison of two coordination strategies for realistic attack scenarios and an analysis of effectiveness...

Periodic systems largely system equivalent to periodic discrete-time processes

Osvaldo Maria Grasselli, Sauro Longhi, Antonio Tornambè (2001)

Kybernetika

In this paper, the problem of obtaining a periodic model in state-space form of a linear process that can be modeled by linear difference equations with periodic coefficients is considered. Such a problem was already studied and solved in [r71] on the basis of the notion of system equivalence, but under the assumption that the process has no null characteristic multiplier. In this paper such an assumption is removed in order to generalize the results in [r71] to linear periodic processes with possibly...

Planning identification experiments for cell signaling pathways: An NFκB case study

Krzysztof Fujarewicz (2010)

International Journal of Applied Mathematics and Computer Science

Mathematical modeling of cell signaling pathways has become a very important and challenging problem in recent years. The importance comes from possible applications of obtained models. It may help us to understand phenomena appearing in single cells and cell populations on a molecular level. Furthermore, it may help us with the discovery of new drug therapies. Mathematical models of cell signaling pathways take different forms. The most popular way of mathematical modeling is to use a set of nonlinear...

Plant Growth and Development - Basic Knowledge and Current Views

V. Brukhin, N. Morozova (2010)

Mathematical Modelling of Natural Phenomena

One of the most intriguing questions in life science is how living organisms develop and maintain their predominant form and shape via the cascade of the processes of differentiation starting from the single cell. Mathematical modeling of these developmental processes could be a very important tool to properly describe the complex processes of evolution and geometry of morphogenesis in time and space. Here, we summarize the most important biological knowledge on plant development, exploring the...

Positive and Negative Feedback in Engineering and Biology

E. S. Zeron (2008)

Mathematical Modelling of Natural Phenomena

No other concepts have shaken so deeply the bases of engineering like those of positive and negative feedback. They have played a most prominent role in engineering since the beginning of the previous century. The birth certificate of positive feedback can be traced back to a pair of patents by Edwin H. Armstrong in 1914 and 1922, whereas that of negative feedback is already lost in time. We present in this paper a short review on the feedback's origins in the fields of engineering and biology....

Predictive control for trajectory tracking and decentralized navigation of multi-agent formations

Ionela Prodan, Sorin Olaru, Cristina Stoica, Silviu-Iulian Niculescu (2013)

International Journal of Applied Mathematics and Computer Science

This paper addresses a predictive control strategy for a particular class of multi-agent formations with a time-varying topology. The goal is to guarantee tracking capabilities with respect to a reference trajectory which is pre-specified for an agent designed as the leader. Then, the remaining agents, designed as followers, track the position and orientation of the leader. In real-time, a predictive control strategy enhanced with the potential field methodology is used in order to derive a feedback...

Prescribed performance control of underactuated surface vessels' trajectory using a neural network and integral time-delay sliding mode

Yun Chen, Hua Chen (2023)

Kybernetika

To tackle the underactuated surface vessel (USV) trajectory tracking challenge with input delays and composite disturbances, an integral time-delay sliding mode controller based on backstepping is discussed. First, the law of virtual velocity control is established by coordinate transformation and the position error is caused to converge utilizing the performance function. At the same time, based on the estimation of velocity vector by the high-gain observer (HGO), radial basis function (RBF) neural...

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