International Journal of Modeling, Simulation, and Scientific Computing

Formal control design techniques usually rely on the plant model of a desired system. The plant model can be derived from the foundation principles of the system but often includes unidentified parameters. In order to approximate these unknown parameters, experiments are conducted to collect information from the behavior of plant dynamics. Thus, closed-loop feedback control methods can be formulated upon the estimation of an appropriate plant model using simulation techniques. Rapid prototyping techniques support this design paradigm which requires that the rapid prototype operate in real time, interact with real hardware and have supporting control functionality. This paper delivers a study on the modeling and testing of a gait generation method using a rapid prototyping technique. The objective is to develop a method of rapid prototyping to test new walking algorithms on a real-time robotic system. The paper addresses the drawbacks of a non-real-time simulation by evaluating the locomotion of a six-legged robot in terms of tracking errors and signifies the proposed methodology of tuning the gait generation algorithm online through real-time hardware in loop simulation setup. Finally, the paper inspects the improved locomotion of the robot using the proposed methodology and signifies it as a valid prototyping technique for approximating novel gait generation algorithms on real-time robotic systems.

This paper presents a computational model of the dynamics of a human's functional state in relation to task performance and environment. It can be used in intelligent systems that support humans in demanding circumstances. The model takes task demand and situational aspects as input and calculates internal factors related to human functioning, such as the experienced pressure, exhaustion, and motivation, and how they affect performance. Simulation experiments under different parameter settings pointed out that the model is able to produce realistic behavior of humans with different types of personalities. Moreover, by a mathematical analysis the equilibria of the model have been determined, and by automated checking a number of expected properties of the model have been confirmed. In addition to this "internal" validation of the model, an experiment has been designed for the purpose of external validation, addressing the estimation of aspects of the human process that are relevant for its practical application. Output from the experiment, like information about personality characteristics and performance quality, has been used to perform estimation of the parameters of the model. By the parameter estimation, a set of parameter values has been identified by which an adequate representation of a person's functional state when performing a task is achieved.

A component-based simulation framework is a favorable choice for parallel multiscale simulations, which require a dedicated coupling component to support flexible data communication/exchange, computational parallelism, and on-demand dynamic load balancing. In this paper, a coupling component (the Coupler) was designed to support integrated parallel multimodeling. An integrated ecological multimodeling, part of the across trophic level system simulation (ATLSS) for Everglades ecosystem restoration, has been used to demonstrate the advantage of the Coupler for natural resource management applications.

The present study tackles the vibratory behavior of a double panel system by operational modal analysis (OMA) using one of the major techniques of blind source separation (BSS), which is the independent component analysis (ICA). For this purpose, the OMA method and the ICA concept are presented and exploited in order to identify the eigenmodes of a double panel system. Then, results obtained by the OMA technique are presented and compared with those achieved by the modal recombination method. Since a good argument is observed, this approach can be used in conjunction with experimental works.

Dynamic modeling and simulation of underwater robotic vehicles is essential for control. In this paper, systematic dynamic modeling and simulation of a remotely operated vehicle (ROV) is developed and named as ROV Design and Analyses (RDA). For the initial design, hydrodynamic coefficients used in the ROV dynamic model were estimated using computational fluid dynamic software and experiments. The proposed RDA toolbox written in MATLAB™ and Simulink™ platform provides a means to simulate the mathematical models of ROV and the control system design before final hardware implementation. The control simulation using a proportional–integral–derivative controller is able to model the positions and velocities output of the ROV that is highly uncertain and nonlinear.