A Quantitative Measure, Mechanism and Attractor for Self-Organization in Networked Complex Systems
نویسنده
چکیده
Quantity of organization in complex networks here is measured as the inverse of the average sum of physical actions of all elements per unit motion multiplied by the Planck’s constant. The meaning of quantity of organization is the number of quanta of action per one unit motion of an element. This definition can be applied to the organization of any complex system. Systems self-organize to decrease the average action per element per unit motion. This lowest action state is the attractor for the continuous selforganization and evolution of a dynamical complex system. Constraints increase this average action and constraint minimization by the elements is a basic mechanism for action minimization. Increase of quantity of elements in a network, leads to faster constraint minimization through grouping, decrease of average action per element and motion and therefore accelerated rate of selforganization. Progressive development, as self-organization, is a process of minimization of action.
منابع مشابه
Modelling and Compensation of uncertain time-delays in networked control systems with plant uncertainty using an Improved RMPC Method
Control systems with digital communication between sensors, controllers and actuators are called as Networked Control Systems (NCSs). In general, NCSs encounter with some problems such as packet dropouts and network induced delays. When plant uncertainty is added to the aforementioned problems, the design of the robust controller that is able to guarantee the stability, becomes more complex. In...
متن کاملDesigninga Neuro-Sliding Mode Controller for Networked Control Systems with Packet Dropout
This paper addresses control design in networked control system by considering stochastic packet dropouts in the forward path of the control loop. The packet dropouts are modelled by mutually independent stochastic variables satisfying Bernoulli binary distribution. A sliding mode controller is utilized to overcome the adverse influences of stochastic packet dropouts in networked control system...
متن کاملModel Based Method for Determining the Minimum Embedding Dimension from Solar Activity Chaotic Time Series
Predicting future behavior of chaotic time series system is a challenging area in the literature of nonlinear systems. The prediction's accuracy of chaotic time series is extremely dependent on the model and the learning algorithm. On the other hand the cyclic solar activity as one of the natural chaotic systems has significant effects on earth, climate, satellites and space missions. Several m...
متن کاملTime Delay and Data Dropout Compensation in Networked Control Systems Using Extended Kalman Filter
In networked control systems, time delay and data dropout can degrade the performance of the control system and even destabilize the system. In the present paper, the Extended Kalman filter is employed to compensate the effects of time delay and data dropout in feedforward and feedback paths of networked control systems. In the proposed method, the extended Kalman filter is used as an observer ...
متن کاملStabilization of Networked Control Systems with Variable Delays and Saturating Inputs
In this paper, improved conditions for the synthesis of static state-feedback controller are derived to stabilize networked control systems (NCSs) subject to actuator saturation. Both of the data packet latency and dropout which deteriorate the performance of the closed-loop system are considered in the NCS model via variable delays. Two different techniques are employed to incorporate actuator...
متن کامل