Improving the Dynamic Performance of Five-Axis CNC Machine Tool by using the Software-in-the-Loop (SIL) Platform

The paper presents the development and implementation of a Software-in-the-loop (SIL) platform allowing the real-time simulation of the hybrid model of five-axis CNC machine tool which is implemented in SIMULINK. The interfacing between dSPACE software and the feed drives models in SIMULINK is explined. The values for the simulated positioning errors between the position demand and simulated position of orthogonal trimming head for the gantry axis are in the order of microns so proposed SIL model is validated. The accurate SIL platform could be used to build and optimise the machining process models including CNC machine tools under cutting conditions and improve machines’ dynamic performance

Anytime system level verification via parallel random exhaustive hardware in the loop simulation

System level verification of cyber-physical systems has the goal of verifying that the whole (i.e., software + hardware) system meets the given specifications. Model checkers for hybrid systems cannot handle system level verification of actual systems. Thus, Hardware In the Loop Simulation (HILS) is currently the main workhorse for system level verification. By using model checking driven exhaustive HILS, System Level Formal Verification (SLFV) can be effectively carried out for actual systems. We present a parallel random exhaustive HILS based model checker for hybrid systems that, by simulating all operational scenarios exactly once in a uniform random order, is able to provide, at any time during the verification process, an upper bound to the probability that the System Under Verification exhibits an error in a yet-to-be-simulated scenario (Omission Probability). We show effectiveness of the proposed approach by presenting experimental results on SLFV of the Inverted Pendulum on a Cart and the Fuel Control System examples in the Simulink distribution. To the best of our knowledge, no previously published model checker can exhaustively verify hybrid systems of such a size and provide at any time an upper bound to the Omission Probability

MODEL PREDICTIVE CONTROL DESIGN FOR LINEAR MULTIVARIABLE SYSTEMS UNDER CONTROL VALVE STICTION

Product quality and production costs are dependent on optimal control of the process. Product variability and oscillation of the process would indicate poor control. Such is the consequence of nonlinearity in the response of the control valves towards controller instructions. The most common cause of nonlinearities is static friction (stiction) in the mechanical assembly of the valve. The ability of a hybrid model predictive control (MPC) formulation to compensate for stiction was to be tested. The formulation was previously shown to be able to compensate for backlash by solving a mixed integer quadratic programming (MIQP) problem. Simulation studies were conducted using a model of a paper machine headbox model in Simulink. The hybrid MPC formulation was updated to run on current software versions and the Choudhury stiction model was integrated into the system. Due to errors in the simulation, the ability of hybrid MPC to compensate for stiction finally could not be determined. The errors encountered are documented as well as recommendations to overcome the shortcomings of the simulation

Development of a hybrid simulation framework for the production planning process in the atlantic salmon supply chain

The farmed salmon supply chain has a highly complex and integrated structure, where activities occur both in the sea and on land. Due to this complexity, the supply chain needs appropriate decision-support tools to aid the production planning process, which capture the material flows, information flows and behaviours of the decision makers in the chain. This paper proposes a hybrid simulation framework for production planning using the case of the Norwegian Atlantic salmon supply chain. This hybrid simulation comprises agent-based modelling (ABM) to capture the autonomous and interacting decision making behaviour of the supply chain actors, while discrete-event simulation (DES) is employed to model the various production processes within the chain. The simulation is implemented using AnyLogic™ version 8.0 simulation software, using a case study from the Norwegian farmed salmon sector. The proposed modelling framework provides a deeper understanding of the activities in the salmon supply chain, thereby enabling improved decision making.publishedVersio

Modeling, Simulation, and Flight Test for Automatic Flight Control of the Condor Hybrid-Electric Remote Piloted Aircraft

This thesis describes the modeling and verification process for the stability and control analysis of the Condor hybrid-electric Remote-Piloted Aircraft (HE-RPA). Due to the high-aspect ratio, sailplane-like geometry of the aircraft, both longitudinal and lateral/directional aerodynamic moments and effects are investigated. The aircraft is modeled using both digital DATCOM as well as the JET5 Excel-based design tool. Static model data is used to create a detailed assessment of predictive flight characteristics and PID autopilot gains that are verified with autonomous flight test. PID gain values were determined using a six degree of freedom linear simulation with the Matlab/SIMULINK software. Flight testing revealed an over-prediction of the short period poles natural frequency, and a prediction to within 0.5% error of the long-period pole frequency. Flight test results show the tuned model PID gains produced a 21.7% and 44.1% reduction in the altitude and roll angle error, respectively. This research effort was successful in providing an analytic and simulation model for the hybrid-electric RPA, supporting first-ever flight test of parallel hybrid-electric propulsion system on a small RPA

SIMULATION OF ELECTRIC AND HYBRID VEHICLES IN A VEHICLE SIMULATOR BASED ON A DETAILED PHYSICAL MODEL, FOR THE PURPOSE OF HMI EVALUATION

In this article, we propose a software solution to study HMI of electric and hybrid electric vehicles in vehicle simulators. We will start with the description of a development process of a physical model for HEV simulation in IGNITE software and equation-based language Modelica. A short introduction to the language, its possibilities, and explanation, why it is more suitable for the development of such models (vehicle powertrain), are presented in the first part of the article. A fusion mechanism of the physical engine with the model by means of FMU (Functional Mock-up Interface) is also described in this part The second part is dedicated to the description of the model constructed in third party software IGNITE. This model has a detailed calculation of energy consumption and energy flow based on the selected control strategy. The last part of the article describes a possible experiment methodology

Simulation Based Optimisation of Ground Crews: Case of a Regional Airport

Paper presents the simulation models built within an airport ground crew scheduling automatization project at a regional airport. Our goal was to develop robust ground crew task scheduling and shift generation algorithms that would improve on existing heuristic rules. We have utilized simulation modeling to develop and validate the algorithms, starting with a model of the existing scheduling process coded and visualized in spreadsheet software and ending with a hybrid Discrete Event and Agent Based model used for the visualization and verification of the optimized processes. Explicit and tacit expert knowledge was recorded through meetings with airport personnel managers and observation of the ground crew processes. Gathered knowledge was combined with business rules, contractual limitations and labor legislation to develop the final version of the algorithms

The innovation network as a complex adaptive system: flexible multi-agent based modeling, simulation and evolutionary decision making

The literature rarely considers an innovation network as a complex adaptive system. In this paper, theories of complex adaptive systems research are employed to model and analyze intra-organization networks, inter-organization networks as well as their interaction mechanisms in the whole innovation context, with a conceptual framework proposed and presented. Flexible multi-agent based modeling, smart simulation, self-survival and adaptive intelligent software agents, expert systems, analytic hierarchy process, hybrid decision support approach, and statistical methods are integrated to deal with the innovation network problem and support evolutionary decision making in the open and dynamic environments