Newton Maruyama

Intelligent UUVs: Some issues on ROV dynamic positioning

Intelligent unmanned underwater vehicles (UUVs) fall under two main group categories: the remotely operated vehicles (ROVs), which are characterized by remote operation and presence of a tether cable; and the autonomous underwater vehicles (AUVs), which are characterized by their autonomous behavior and absence of a tether cable. One fundamental issue of the UUV design is the dynamic position control system. This system plays a crucial role together with the sensor architecture in the degree of system autonomy that can be achieved. This paper is concerned with a few issues when dynamically positioning remotely operated underwater vehicles (ROVs). By restricting the operating regime of ROVs to slow velocity requirements the paper investigates the implementation of a few decentralized control strategies and compare their performance measures, which are assessed by simulating a nonlinear ROV system model for each control strategy. Issues concerning input tracking, disturbance rejection, and plant variations are discussed. The evaluations consider the use of linear PID feedback and feedforward variants, and a robust nonlinear control strategies applied to a full order, fully coupled, and nonlinear vehicle model. These evaluations consider a vehicle undertaking standard mission activities where the tether cable dynamics, with load estimates obtained from a lumped mass cable model, and the vehicle actuator system are present. The paper shows that much of the performance deterioration may be attributed mainly due to cable inertia. The authors also verify that the nonlinear robust control strategy does not necessarily allow for better performance over the linear feedback control strategies implemented when vehicle motions are confined to slow velocity profiles. These and other partial results will aid the design of the control system for an underwater vehicle currently under construction

Modeling and Identification of an Open-frame Underwater Vehicle: The Yaw Motion Dynamics

A semi-autonomous unmanned underwater vehicle (UUV), named LAURS, is being developed at the Laboratory of Sensors and Actuators at the University of Sao Paulo. The vehicle has been designed to provide inspection and intervention capabilities in specific missions of deep water oil fields. In this work, a method of modeling and identification of yaw motion dynamic system model of an open-frame underwater vehicle is presented. Using an on-board low cost magnetic compass sensor the method is based on the utilization of an uncoupled 1-DOF (degree of freedom) dynamic system equation and the application of the integral method which is the classical least squares algorithm applied to the integral form of the dynamic system equations. Experimental trials with the actual vehicle have been performed in a test tank and diving pool. During these experiments, thrusters responsible for yaw motion are driven by sinusoidal voltage signal profiles. An assessment of the feasibility of the method reveals that estimated dynamic system models are more reliable when considering slow and small sinusoidal voltage signal profiles, i.e. with larger periods and with relatively small amplitude and offset.

Petri Net approach for modelling system integration in intelligent buildings

In this paper, a Petri Net approach is introduced for modelling and simulation of control strategies in Intelligent Building. In this context, it is claimed that integration with other building systems can be achieved in a more systematic way considering a mechatronic approach (i.e. multidisciplinary concepts applied to the development of systems). The case study is the Ambulatory Building of Medical School Hospital of University of Sao Paulo. Particularly, the developed methodology is applied to the elevator system and to the HVAC (Heating, Ventilation and Air Conditioning) system. It is shown that using this approach, the control systems could be integrated, improving performance.

Sensor Fusion with Low-Grade Inertial Sensors and Odometer to Estimate Geodetic Coordinates in Environments without GPS Signal

This paper presents a sensor fusion algorithm based on a Kalman Filter to estimate geodetic coordinates and reconstruct a car test trajectory in environments where there is no GPS signal. The sensor fusion algorithm is based on low-grade strapdown inertial sensors (i.e. accelerometers and gyroscopes) and an incremental odometer, from which, velocity measurements is obtained. Since the dynamic system is non linear, an Extended Kalman Filter (EKF) is used to estimate the states (i.e. latitude, longitude and altitude) and reconstruct the test trajectory. The relevance of this work is given by the fact that, in the current literature, much has been published about the merger Inertial Sensors and GPS, however, currently no literature that addresses the form of sensor fusion proposed here is available. Another aspect that could be emphasized is that the proposed algorithm has potential to be applied in environments where GPS signals are not available, such as Pipeline Inspection Gauge (PIG) as depicted below in figure 2. The inertial navigation system developed and tested, shows that only with inertial sensors measurements, a closed tested trajectory can not be reconstructed satisfactorily, however when it uses the sensor fusion, the trajectory can be reconstructed with relative success. On preliminary experiments, it was possible reconstruct a closed trajectory of approximately 2800m, attaining a final error of 13m.

Estimation of trajectories of pipeline PIGs using inertial measurements and non linear sensor fusion

This paper presents a nonlinear sensor fusion algorithm for inertial navigation designed to reconstruct trajectories of a Pipeline Inspection Gauge. Outputs of a strapdown inertial measurement unit are combined with non inertial measurements provided by an incremental odometer and a set of cartographic landmarks. The navigation system is modeled as a nonlinear dynamic system and the extended Kalman filter is used to estimate the system state. On preliminary experiments, it was possible to reconstruct a closed test trajectory with 2,800 m of extension, attaining a final error of 1.7 m.

Modeling of hybrid supervisory systems using UML and Petri nets

In this work, a new approach for the design of supervisory systems is introduced. It focuses on how supervisory systems can improve global system performance through the use of efficient local controller switching configuration policies. For this purpose, a modeling approach is developed that can represent the integration of different hierarchical levels of the control architecture and different dynamic behavior. UML, Petri nets and differential equation systems are merged in order to provide a framework with flexibility for representing the abstractions that emerge when considering supervisory system design.

Virtual Enterprise Planning System using time windows and capacity constraint concepts

In a global market, the trend for geographical dispersion of manufacturing plants has been observed. This dispersion is motivated by the opportunity to exploit local advantages under different viewpoints. This structure also allows for more intense interaction between plants of different productive enterprises. In this sense, the concept of Virtual Enterprise (VE) is fundamental to explore new business strategies such as “focus on core competencies”, “maximal customer orientation” and “distributed production”. However, in this new productive structure, there are new requirements for planning and for establishing the delivery date of the orders. To address these new requirements, this work introduces a Virtual Enterprise Planning System (VEPS) based on “time windows” and “capacity constraints”. These two concepts have been used extensively in the literature related to conventional planning systems: however, not in the VE context. In this approach, “time windows” delimit the allocation interval of the tasks in the production systems (PSs) involved, while “capacity constraint” makes the time windows feasible considering the importance of the due date.

Developing an ROV software control architecture: A formal specification approach

The software development of control architectures for Remotely Operated Vehicles (ROVs) is a complex task. The use of formal specifications for critical systems can improve both correctness and completeness of specifications and implementations. In this work, a new method for developing control architectures based on formal specifications is introduced. The chosen formal specification language is the CSP-OZ, a combination of the CSP language for behavioral model and the Object-Z language for data model. At first, the CSP parts of specifications are verified using the FDR2 model checker. Then, CSP-OZ model specifications are coded using the ADA language. More specifically, the ADA language profile Ravenscar for concurrency and the SPARK language with its annotations for data modelling are used. The SPARK annotations give support for the Object-Z specifications. Later, the SPARK examiner can be used to statically check the code against the annotations. In order to illustrate the application of the method, the development of the software control architecture of the LAURS ROV is introduced. The embedded system is based on a PC104 Intel x86 running the real time operating system Vxworks.

Hydrodynamic parameter estimation of an open frame unmanned underwater vehicle

Abstract A semi-autonomous unmanned underwater vehicle (UUV), named VSOR, is being developed at the Laboratory of Sensors and Actuators at the University of Sao Paulo. The vehicle has been designed to provide inspection and intervention capabilities in specific missions in deep water oil fields. This work presents a methodology to identify the drag coefficients and virtual mass/inertia of an open-frame underwater vehicle using the system identification approach. Trials with the vehicle in a test tank have been performed. Using the vehicle onboard sensor information, the methodology is based on the utilisation of an uncoupled 1-DOF (degree of freedom) dynamic system equation of an underwater vehicle and the application of the integral method, which is the classical least squares algorithm, applied to the integral form of the system dynamic equations. An assessment of the feasibility of the method is presented.

Time-energy Optimal Trajectory Planning over a Fixed Path for a Wheeled Mobile Robot.

In this paper a method for time-energy optimal velocity profile planning for a nonholonomic wheeled mobile robot (WMR) is proposed. Instead of relying on a nonlinear programming algorithm, the method utilizes a nonlinear change of variables that can transform the nonlinear optimization problem into a convex optimization problem. The equations are then discretized and later formulated as a second order cone programming that can be solved by the Matlab CVX toolbox. The formulation of the objective function has two components: the total energy and the traversal time that is weighted by a parameter named penalty coefficient. With the use of the penalty coefficient one can easily establish a trade-off between the optimization of total energy and traversal time. If the penalty coefficient is increased then minimization of time is more prioritized than the total energy and vice versa. The formulation gives rise to a Pareto optimality condition from which it is not possible to diminish the traversal time without increasing the total energy and vice versa.