Implementation Of Dynamic System Research Articles

Design and Development of an Optimal Control Model in System Dynamics through State-Space Representation

Control engineering and state-space representation are valuable tools in the analysis and design of dynamic systems. In this research, a methodology is proposed that uses these approaches to transform a system-dynamics simulation model into a mathematical model. This is achieved by expressing input, output and state variables as input, output and state vectors, respectively, allowing the representation of the model in matrix form. The resulting model is linear and time-invariant, facilitating its analysis and design. Through the use of this methodology, the system transfer matrix is obtained, which allows the analysis and design of the optimal control of the simulation model. The Ackermann gain-control technique is used to determine the optimal control of the system, which results in a shorter settlement time. This research proposal seeks to mathematically strengthen simulation models and provide an analytical alternative through modern control engineering in SD simulation models. This would allow more informed and effective decisions in the implementation of dynamic systems.

Controlling Bifurcation in Electronic Implementation of Dynamical Systems

In the theoretical and experimental studies of bifurcations in dynamical systems, the adjustments of the parameter values play a key role. The reason is because small variations in these values may result in topological changes in the behavior of the flow of the system. Taking this into account, in this paper, a new design for controlling bifurcation, suitable for electronic implementations of chaotic systems, is presented. The variation of the bifurcation parameter is performed by means of an Arduino UNO micro-controller and a digital controlled potentiometer. In this way, the variation of the electronic components is performed in an automated manner, avoiding the intrinsic problems of a manual variation of the circuit parameters. As a particular example, a scaled Rössler system is considered. One of the advantages of the controlled automated bifurcation is that it is useful for analyzing the robustness of the different limiting behaviors of the system against parameter mismatches.

The Localization Method of Active Olfaction Robot and Experimental Study

An active olfaction implementation scheme based on zigzag search algorithm using a wheeled mobile robot and the experimental verification are put forward. Firstly, the hardware structure of the active olfaction robot is setup. Secondly, the Zigzag-based robot active olfaction dynamic system implementation procedure in the simulated environment is presented, including plume finding, plume tracking and odor source declaration, and simulation results validate the proposed search scheme. The entire system was used under steady wind condition to locate the ethanol odor source. Choice 15m as the start distance, and after 10 times locating, the error is less than 5% and the experimental results prove that the system recognition is accuracy.

ANN Application Techniques for Power System Stability Estimation

The implementation of artificial neural networks (ANN) as a power system stability monitoring tool is a viable option, introducing dynamic and intelligent solution to utility operators. This paper examines the performance of two nonlinear multilayer ANN models which are similar in structural topology and training emphasis but different by way of the utilization of their net or basis function. The performance of both models were compared for the estimation of stability index to gauge the stability of a power system network. Although tests were conducted in a simulated environment, loading patterns analyzed in this case study were realistically generated, and hence test results realistically accentuates the potential of ANN for practical on-line dynamic system implementation.

Branching-time logic programming: the language Cactus and its applications

Temporal programming languages provide a powerful means for the description and implementation of dynamic systems. However, most temporal languages are based on linear time, a fact that renders them unsuitable for certain types of applications (such as expressing properties of non-deterministic programs). In this paper we introduce the new temporal logic programming language Cactus, which is based on a branching notion of time. In Cactus, the truth value of a predicate depends on a hidden time parameter which varies over a tree-like structure. As a result, Cactus can be used to express in a natural way non-deterministic computations or generally algorithms that involve the manipulation of tree data structures. Moreover, Cactus appears to be appropriate as the target language for compilers or program transformers. Cactus programs can be executed using BSLD-resolution, a proof procedure based on the notion of canonical temporal atoms/clauses.