Showing papers presented at "Mediterranean Conference on Control and Automation in 2007"

A novel binary particle swarm optimization

Abstract: Particle swarm optimization (PSO) as a novel computational intelligence technique, has succeeded in many continuous problems. But in discrete or binary version there are still some difficulties. In this paper a novel binary PSO is proposed. This algorithm proposes a new definition for the velocity vector of binary PSO. It will be shown that this algorithm is a better interpretation of continuous PSO into discrete PSO than the older versions. Also a number of benchmark optimization problems are solved using this concept and quite satisfactory results are obtained.

A revised look at numerical differentiation with an application to nonlinear feedback control

Abstract: We are presenting new and efficient methods for numerical differentiation, i.e., for estimating derivatives of a noisy time signal. They are illustrated, via convincing numerical simulations, by the analysis of an academic signal and by the feedback control of a nonlinear system.

Unmanned ground vehicle swarm formation control using potential fields

Abstract: A novel technique is presented for organizing swarms of robots into formation utilizing artificial potential fields generated from normal and sigmoid functions. These functions construct the surface swarm members travel on, controlling the overall swarm geometry and the individual member spacing. Limiting functions are defined to provide tighter swarm control by modifying and adjusting a set of control variables forcing the swarm to behave according to set constraints, formation and member spacing. The swarm function and limiting functions are combined to control swarm formation, orientation, and swarm movement as a whole. Parameters are chosen based on desired formation as well as user defined constraints. This approach compared to others, is simple, computationally efficient, scales well to different swarm sizes, to heterogeneous systems, and to both centralized and decentralized swarm models. Simulation results are presented for a swarm of four and ten particles following circle, ellipse and wedge formations. Experimental results are also included with four unmanned ground vehicles (UGV).

Statistical profile generation for traffic monitoring using real-time UAV based video data

Abstract: The eye-in-the-sky alternative to collecting real-time temporal/spatial data using small unmanned helicopters is proposed to: monitor traffic, evaluate and assess traffic patterns and provide accurate vehicle counts. Collected real-time visual data are converted to traffic statistical profiles and used as continuously updated inputs to existing traffic simulation models improving calibration, accuracy (in terms of variable parameter values) and future traffic predictions. Functionality of simulation models is enhanced, and reliability is improved The proposed approach offers significant advantages over conventional methods where historical and outdated data is used to run poorly calibrated traffic simulation models.

Training ANFIS structure with modified PSO algorithm

Abstract: This paper introduces a new approach for training the adaptive network based fuzzy inference system (ANFIS). The previous works emphasized on gradient base method or least square (LS) based method. In this study we apply one of the swarm intelligent branches, named particle swarm optimization (PSO) with some modification in it to the training of all parameters of ANFIS structure. These modifications are inspired by natural evolutions. Finally the method is applied to the identification of nonlinear dynamical system and is compared with basic PSO and showed quite satisfactory results.

Positive observation problem for linear time-delay positive systems

Abstract: This paper deals with the problem of positive observation for linear time-delay systems for which the states take nonnegative values whenever the initial conditions are nonnegative. We focus on the design of positive observers (possibly with time-delay) which guarantee nonnegative estimates of the current states. We derive necessary and sufficient conditions for the existence of a positive observer (extended Luemberger-type) and show that the solvability of the problem can be decided via standard linear programming techniques. Moreover, on the negative side, it is shown that one cannot stabilize any unstable positive time-delay system by using extended Luenberger type positive observers. In other words, the separation principle does not hold.

A model predictive control approach for combined braking and steering in autonomous vehicles

Abstract: In this paper we present a Model Predictive Control (MPC) approach for combined braking and steering systems in autonomous vehicles. We start from the result presented in F. Borrelli et al. (2005) and P. Falcone et al. (2006), where a Model Predictive Controller (MPC) for autonomous steering systems has been presented. We formulate a predictive control problem in order to best follow a given path by controlling the front steering angle and the brakes at the four wheels independently, while fulfilling various physical and design constraints.

A particle filtering-based framework for real-time fault diagnosis and failure prognosis in a turbine engine

Abstract: This paper presents the implementation of an online particle-filtering-based framework for fault diagnosis and failure prognosis in a turbine engine. The methodology considers two autonomous modules, and assumes the existence of fault indicators (for monitoring purposes) and the availability of real-time measurements. A fault detection and identification (FDI) module uses a hybrid state-space model of the plant, and a particle filtering algorithm to calculate the probability of a crack in one of the blades of the turbine; simultaneously computing the state probability density function (pdf) estimates that will be used as initial conditions in the prognosis module. The failure prognosis module, on the other hand, computes the remaining useful life (RUL) pdf of the faulty subsystem in real-time, using a particle-filtering-based algorithm that consecutively updates the current state estimate for a nonlinear state-space model (with unknown time-varying parameters), and predicts the evolution in time of the probability distribution for the crack length. The outcome of the prognosis module provides information about precision and accuracy of long-term predictions, RUL expectations and 95% confidence intervals for the failure condition under study. Data from a seeded fault test is used to validate the proposed approaches.

Robust low altitude behavior control of a quadrotor rotorcraft through sliding modes

Abstract: This paper gives the full dynamical model of a commercially available quadrotor rotorcraft and presents its behavior control at low altitudes through sliding mode control. The control law is very well known for its robustness against disturbances and invariance during the sliding regime. The plant, on the other hand, is a nonlinear one with state variables are tightly coupled. The simulations have shown that the algorithm successfully drives the system towards the desired trajectory with bounded control signals.

Occupancy grid mapping: An empirical evaluation

Abstract: In this paper a quantitative analysis of robotic mapping utilising the fields dominant paradigm, the occupancy grid, is presented. The aim of this work is to determine which approach to the robotic mapping problem imbues a mobile robot with the greatest ability to create an accurate representation of its operating environment. We accomplish this by analysing the performance of several established mapping techniques using identical test data. Through evaluating the maps generated by these paradigms using an extensible benchmarking suite that our group has developed we outline which paradigm yields the greatest representational ability.

Unmanned helicopter waypoint trajectory tracking using model predictive control

Abstract: A Model Predictive Control Based Trajectory Tracking (MPCTT) system for small unmanned helicopters is presented. A linear model predictive controller is used to take advantage of the fast algorithms available to solve convex optimization problems. The proposed MPCTT system is compared with a velocity tracking and a position tracking system implemented with classical PIDs from previous research work. Obtained simulation results demonstrate the superiority of the proposed MPCTT approach, generating a substantially less control effort in order to track waypoint trajectories. The unmanned helicopter used for the proposed MPCTT system is considered as a (linearized) linear state-space model obtained for hovering and slow motion; however, as shown, the MPCTT is robust enough to perform trajectory tracking under a cruise flight mode, too.

Design of sliding mode unknown input observer for uncertain Takagi-Sugeno model

Abstract: This paper addresses the analysis and design of a sliding mode observer on the basis of a Takagi-Sugeno (T-S) model subject both to unknown inputs and uncertainties. The main contribution of the paper is the development of a robust observer with respect to the uncertainties as well as the synthesis of sufficient stability conditions of this observer. The stabilization of the observer is performed by the search of suitable Lyapunov matrices. It is shown how to determine the gains of the local observers, these gains being solutions of a set of linear matrix inequalities (LMI). The validity of the proposed methodology is illustrated by an academic example.

An impulsive observer that estimates the exact state of a linear continuous-time system in predetermined finite time

Abstract: This paper presents a new observer for the class of linear continuous-time systems. In contrast to many well-established observers, which normally estimate the system state in an asymptotic fashion, the proposed observer estimates the exact system state in predetermined finite time. The finite convergence time of the proposed observer is achieved by updating the observer state based on current observer data at a definite time instant. Simulation results are presented to illustrate the convergence behavior of the proposed observer.

Load frequency control in interconnected power system using modified dynamic neural networks

Abstract: This paper present power system load frequency control by modified dynamic neural networks controller. The controller has dynamic neurons in hidden layer and conventional neurons in other layers. For considering the sensitivity of power system model, the neural network emulator used to identify the model simultaneously with control process. To have validation of proposed structure of neural network controller the results of simulation demonstrated that the proposed controller offers better performance than conventional neural network controller.

Temporal Occupancy Grid for mobile robot dynamic environment mapping

Abstract: Mapping dynamic environments is an open issue in the field of robotics. In this paper, we extend the well known Occupancy Grid structure to address the problem of generating valid maps for dynamic indoor environments. We propose a spatiotemporal access method to store all sensor values (instead of preserving only one value for each cell as in the common occupancy grid case). By searching for similar time series, we can detect moving objects that appear only in a limited number of possible configurations (e.g. doors or chairs). Simulated experiments demonstrate the potentialities of the proposed system.

NN-ANARX structure based dynamic output feedback linearization for control of nonlinear MIMO systems

Abstract: An application of Neural Networks based Additive Nonlinear Autoregressive Exogenous (NN-ANARX) structure for modeling and control of nonlinear MIMO systems is presented in the paper. A subclass of NN-ANARX structure is proposed to simplify the calculation of controls by ANARX-based control technique. The problem of the inverse function calculation in the control algorithm is solved. After that the ANARX-based dynamic output feedback linearization control algorithm is applied for control of nonlinear MIMO systems. The effectiveness of the approach proposed in the paper is demonstrated on examples.

High speed solenoid valves in pneumatic servo applications

Abstract: Pneumatic driving systems are mainly used in industrial applications where the moving parts are usually fixed by the mechanical stops. For flexible and precise positioning tasks of pneumatic drives relatively expensive proportional valves have been implemented. In order to develop cheaper pneumatic servo systems, the employment of low-cost on/off solenoid valves have received considerable attention. But, the traditional technologies used in on/off solenoid valves manifest different problems caused by the electric and thermal effects, inertial forces of their mechanical parts and friction phenomenon. However, it seems that innovative technology used in fast switching solenoid valves gives better possibilities in control of pneumatic systems due to their negligible internal friction and modular architecture. In this paper a control method based on pulse-width-modulation algorithm for position control of a pneumatic actuator with high-speed solenoid valve is considered and experimentally verified.

Trajectory planning algorithm based on the continuity of jerk

Abstract: This paper presents a trajectory planning method that provides a continuity of position, velocity, acceleration and jerk. The method combines fifth-order and fourth-order polynomials in order to satisfy the continuity of jerk and give smooth accelerations on all segments of the planned trajectory. The proposed method was tested for movements of the three-axes planar articulated robot. The method includes limits of the velocities, accelerations, and jerks of each robot joint. Simulation results are presented and compared with the results obtained by the original Ho and Cook spline-interpolation method.

One-Step procedure for robust output h8 fuzzy control

Abstract: This paper addresses robust observer based Hinfin control problem for Takagi-Sugeno fuzzy systems with time-varying norm bounded uncertainties. Sufficient relaxed conditions for synthesis of a fuzzy observer and a fuzzy controller for T-S fuzzy systems are derived in terms of a set of linear matrix inequalities (LMIs). In comparison with the existing techniques in literature, the proposed approach considerably simplifies the design procedure and gives in only one step the controller and the observer gains. The observer and controller designed are capable to reject the disturbance assumed known but norm bounded. In order to highlight the performance of the proposed control algorithm, numerical simulations are performed.

A nonlinear PID control scheme for hard disk drive servosystems

Abstract: The aim of this paper is to put forward a novel design of a nonlinear PID controller type based on carefully choosing nonlinear gains to enable reducing the settling time, minimizing the overshoot and improving the required control effort during the functions of the read/write (R/W) head positioning servomechanism in hard disk drives. The controller is capable of adjusting a driving force, a damping effect and an integral action according to the position of the actual system output with respect to the desired output. This is carried out by utilizing the three actions of the PID controller which are tuned by different nonlinear functions to provide the system with the needed level of a driving force, a damping and a steady-state error correction action. Simulation results, including step function response, control signal history, and a disturbance rejection capability are presented to show the efficiency of the proposed controller.

Aggressive maneuvers on loose surfaces: Data analysis and input parametrization

Abstract: In this work we initiate a mathematical analysis of rally racing techniques An empirical description of trail-braking (TB) and pendulum-turn (PT) cornering, two of the most common rally racing maneuvers, is provided via analysis of data collected during execution of these maneuvers by an expert rally driver Trail-Braking and Pendulum-Turn maneuvering techniques are reproduced using numerical optimization as special cases of the minimum time cornering problem with specific boundary conditions We show that a simple parametrization of the control inputs can be used to reproduce these maneuvers using a high fidelity full-car model

Localization of an underwater vehicle using an IMU and a laser-based vision system

Abstract: This paper describes the development of a position tracking system designed for a remotely operated vehicle (ROV). The sensor package consists of an inertial measurement unit (IMU) and a laser-based vision system (LVS). The LVS consists of two undewater laser pointers and a single CCD camera mounted on the ROV. The LVS fuses data deriving from the projection of the laser pointers on the image plane while it tracks a target at the same plane using computer vision algorithms. The LVS calculates the position vector of the vehicle at a low frequency, with respect to the center of the tracked object. The IMU measures the accelerations and angular velocities of the vehicle at a high frequency. The fusion of the two sensors is based on a multisensor Kalman filter where the measured acceleration and angular velocity of the IMU is fed directly to the filter. The result is the calculation of the position vector at a high frequency, which can be used for a smooth closed loop steering control of the vehicle. The integration of the system was proved successful through an extensive experimental procedure.

Lateral vehicle velocity estimation using fuzzy sliding mode observer

Abstract: This paper presents a robust method for estimation the lateral velocity of vehicle. The proposed observer describes a simple structure that contains a sliding mode term which turns out to be robust against output noises and parameters variations as well as sustained disturbances The given nonlinear model of the vehicle is then represented by an uncertain Takagi-Sugeno fuzzy model when the road adhesion conditions change and the sideslip angle is unavailable for measurement. After giving the nonlinear model of the vehicle, its representation by a T-S uncertain fuzzy model is discussed. Stability conditions of such observers are expressed in terms of linear matrix inequalities (LMI). To illustrate the effectiveness of the proposed design observer, a numerical simulation is given.

Observer-based quantized output feedback control of nonlinear systems

Abstract: This paper addresses the problem of stabilizing a nonlinear system by means of quantized output feedback. A framework is presented in which the control input is generated by an observer-based feedback controller acting on quantized output measurements. A stabilization result is established under the assumption that this observer-based controller possesses robustness with respect to output measurement errors in an input-to-state stability (ISS) sense. Designing such observers and controllers is a largely open problem, some partial results on which are discussed. The main goal of the paper is to encourage further work on this important topic.

Rapid prototyping of control systems using embedded target for TI C2000 DSP

Abstract: The paper presents a digital control application, in which a tuning method is proposed for DC motors, using DSP from Texas Instruments (TI). Experimental application for the DC motor illustrates the effectiveness and the simplicity of the proposed method for controller design. The control algorithm for the drive application runs on a TMS320F2812 DSP. Once the desired functionality has been captured and simulated, using MATLAB/Simulink/Embedded Target for TI C2000 DSP environment can be generated code for the DSP. All task assignments to processor are automatically made by the software. The DC Motor is driven by pulse width modulated (PWM) signals generated by the DSP.

Stator fault detection in induction machines by parameter estimation, using adaptive kalman filter

Abstract: In this paper first a parametric low differential order model, suitable for mathematical analysis is introduced for induction machines with faulty stator. Second, an adaptive Kalman filter is proposed for recursively estimating the states and parameters of continuous-time model with discrete measurements for fault detection ends. Typical motor faults as inter-turn short circuit and increased winding resistance are taken into account.

Design of IEC 61131-3 function blocks using SysML

Abstract: UML is almost inevitable when dealing with software designing and intends to be extended to cover many different disciplines. At the same time, control and automation designers integrate further object oriented concepts in their traditional programming behaviors in particular with function blocks. Whereas UML was not adapted to model these IEC 61131 compliant items, an important extension called SysML has been proposed. This paper deals with evaluating the new modeling abilities of this language according to programmable logical controllers specific programming rules.

Challenges in implementation of human-automation interaction models

Abstract: This paper presents the practical experience gained in the process of implementing the human-centered automation design methodology to an electric power utility management automation function, along with the analytical discussions on the implementation challenges This report of implementation challenges and the discussions made on the methods devised to conquer those challenges lead to an alternative approach to the original approach to the well-known human-centered automation design model in the literature

Performance analysis of field-oriented control and direct torque control for sensorless induction motor drives

Abstract: This paper presents a contribution for detailed comparison between two sensorless control techniques for high performance induction motor drives: Field-oriented control (FOC) and direct torque control (DTC). The main characteristics of field-oriented control and direct torque control schemes are studied by simulation emphasizing their advantages and disadvantages. The performances of the two control schemes are evaluated in terms of torque and current ripples, and transient responses to load toque variation. We can nevertheless say that the two control schemes provide in their basic configuration, comparable performances regarding the torque control and parameter sensitivity. We can note a slight advance of DTC scheme compared to FOC scheme regarding the dynamic flux control performance and the implementation complexity. The choice of one or the other scheme will depend mainly on specific requirements of the application.

A disturbance decoupling nonlinear control law for variable speed wind turbines

Abstract: This paper describes a nonlinear control law for controlling variable speed wind turbines using feedback linearization. The novel aspect of the control law is its ability to decouple the effect of wind fluctuations. Furthermore, the transformation to feedback linearizable coordinates is chosen intelligently so that the majority of the system structure is invariant under the transformation. Consequently the physical interpretation is preserved. The method assumes that the effective wind speed and acceleration are estimated from measurements on the wind turbine. The performance of the control is compared to that of a LQG controller using a specific wind turbine and wind model.