Essameddin Badreddin

Using Computer Simulation in Operating Room Management: Impacts on Process Engineering and Performance

Operating rooms are regarded as the most costly hospital facilities. Due to rising costs and decreasing reimbursements, it is necessary to optimize the efficiency of the operating room suite. In this context several strategies have been proposed that optimize patient throughput by redesigning perioperative processes. The successful deployment of effective practices for continuous process improvements in operating rooms can require that operating room management sets targets and monitors improvements throughout all phases of process engineering. Simulation can be used to study the effects of process improvements through novel facilities, technologies and/or strategies. In this paper, we propose a conceptual framework to use computer simulations in different stages of business process management (BPM) lifecycle for operating room management. Additionally, we conduct simulation studies in different stages of the BPM lifecycle. The results of our studies provide evidence that simulation can provide effective decision support to drive performance in operating rooms in several phases of the BPM lifecycle

Dynamic Modeling of a Simple Reverse Osmosis Desalination Plant for Advanced Control Purposes

Reverse osmosis (RO) has become an important process for desalting water. It requires an efficient control system to maintain costs at acceptable level and therefore dynamic models are essential. Although it is possible to find in the literature steady-state models and some dynamic models obtained by parameter identification, there are no reports about lumped parameter dynamic models for control purposes obtained by application of physical laws. Such models are useful not only to design model-based control systems but also for the implementation of fault tolerant systems based on fault detection and isolation (FDI) methods, as well as to analyze transient characteristics of the plant. In this paper, models from the literature are shortly analyzed and a simple lumped parameter model for control purposes, which is derived from physical laws, is proposed. Moreover, a block-oriented library for MATLAB/SIMULINKtrade is presented, so that different plant configurations can be implemented as block diagram to simulate the system and to test control algorithms.

Multi-objective Optimal Control: An Overview

Optimization techniques have been a crucial tool for designing control systems and for tuning controllers. The always increasing quality requirements for new products and consequently the natural advance in control system design have lead to the introduction of more than one design criterion, which will require in turn more sophisticated techniques to solve such Multi-Objective Optimization (MOO) problems. Thus, many examples of using MOO techniques in control have appeared in the literature. In this paper, several optimal control design problems are analyzed from the MOO point of view. Moreover, some suggestions about how standard control design techniques can be extended to introduce multi-objective optimization are given.

Application of hybrid modeling and control techniques to desalination plants

One of the most recent and most intense efforts in control theory deals with handling systems whose behavior of interest is determined by interacting continuous and discrete dynamics. This approach can be applied not only to intrinsic hybrid processes but also to other systems as for example continuous processes with supervisory logic, multi-model control systems, switching control, etc. In this paper, hybrid systems are briefly introduced and possible applications to desalination plants are given by means of illustrative examples.

Optimal control of a reverse osmosis desalination plant using multi-objective optimization

In this contribution, the control of a reverse osmosis desalination plant by using an optimal multi-loop approach is presented. Controllers are assumed to be players of a cooperative game, whose solution is obtained by multi-objective optimization (MOO). The MOO problem is solved by applying a genetic algorithm and the final solution is found from this Pareto set. For the reverse osmosis plant a control scheme consisting of two PI control loops are proposed. Simulation results show that in some cases, as for example this desalination plant, multi-loop control with several controllers, which have been obtained by join multi-objective optimization, perform as good as more complex controllers but with less implementation effort.

A New Approach to Design Multi-loop Control Systems with Multiple Controllers

In this contribution, a new method to design multi-loop control systems with several controllers is proposed. Controllers are assumed to be players of a cooperative dynamic game, whose solution is obtained by multi-objective optimization (MOO). The MOO problem is solved by applying a genetic algorithm and the final solution is found from an optimal Pareto set. As illustrative example, the control system design of a reverse osmosis desalination plant is used. Simulation results are satisfactory and show that in many cases, as for example this desalination plant, multi-loop control with several controllers, which have been obtained by join multi-objective optimization, perform as good as more complex controllers but with less implementation effort

Application of model predictive control for fault tolerant system using dynamic safety margin

Model predictive control (MPC) has the ability to cope with hard constraints on control and state. It has, therefore, been widely applied in most industries specially, petrochemical industries. Dynamic safety margin (DSM) is a performance index used to measure the distance between a predefined safety boundary, described by a set of inequality constraints, in state space and system trajectory as it evolves. Designing MPC based on DSM is especially important for safety critical system to maintain a predefined margin of safety during transient and steady state. In this work, MPC based on DSM is used in fault tolerant control (FTC) design. The proposed method of FTC is suitable for single and multi-model system according to the fault type and fault information. It can compensate missed information about the fault and uncertainties in the faulty model

Cascaded Kalman and particle filters for photogrammetry based gyroscope drift and robot attitude estimation

Based on a cascaded Kalman-Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model. Nonlinear attitude kinematics, drift and robot angular movement dynamics each in 3 dimensions result in a nonlinear high dimensional system. To reduce the complexity, we propose a decomposition of system to cascaded subsystems and then design separate cascaded observers. This design leads to an easier tuning and more precise debugging from the perspective of programming and such a setting is well suited for a cooperative modular system with noticeably reduced computation time. Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement. The estimated angular velocity is utilized as input of the second Particle Filtering (PF) based observer in two scenarios of stochastic and deterministic inputs. Simulation results are provided to show the efficiency of the proposed method. Moreover, the experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method.

Dynamic safety margin principle and application in control of safety critical systems

Control systems are designed in general to meet a given performance requirement. Dynamic safety margin (DSM) is a new performance index used to measure the distance between a predefined safety boundary in the state space and the system trajectory as it evolves. Controller design based on DSM is especially important for safety-critical systems to maintain a predefined margin of safety during the transient and in the presence of large disturbances. In this paper, the idea of DSM is explained and applied in controller design for fluid level in two-tank system. Simulation examples and results of a real-time implementation on the actual process demonstrate the fruitfulness of this design.

A Comparative Study of Collision Avoidance Techniques for Unmanned Aerial Vehicles

In this paper three collision avoidance methods for an unmanned aerial vehicle (UAV) are tested and compared to one another. The quadrocopter dynamic model with attitude and velocity controller, a trajectory generator and a selection of collision avoidance approaches were implemented. The first collision avoidance method is based on a geometric approach which computes a direction of avoidance from the flight direction and simple geometric equations. The second technique uses virtual repulsive force fields causing the UAV to be repelled by obstacles. The last method is a grid-based online path re-planning algorithm with A* search that finds a collision free path during flight. Various flight scenarios were defined including static and dynamic obstacles.