Showing papers presented at "Mediterranean Conference on Control and Automation in 2008"

Intelligent PID controllers

Abstract: Intelligent PID controllers, or i-PID controllers, are PID controllers where the unknown parts of the plant, which might be highly nonlinear and/or time-varying, are taken into account without any modeling procedure. Our main tool is an online numerical differentiator, which is based on easily implementable fast estimation and identification techniques. Several numerical experiments demonstrate the efficiency of our method when compared to more classic PID regulators.

Trajectory planning for a quadrotor helicopter

Abstract: A simple direct method able to generate time-optimal trajectories for a micro quadrotor helicopter is presented. It is based on modeling the quadrotor trajectory as a composition of a parametric function P(lambda) defining the quadrotor path, and a monotonically increasing function lambda(t), specifying the motion on this path. The optimal evolutions of P(lambda) and lambda(t), which are approximated using B-spline functions, are found using a nonlinear optimization technique. The proposed method accounts for the most important constraints inherent to the system behavior, such as underactuation, obstacles avoidance and limits on actuator torques and speeds.

Constrained state estimation using the Unscented Kalman Filter

Abstract: A simple procedure to include state inequality constraints in the unscented Kalman filter is proposed. With this procedure, the information of active state constraints influences the state covariance matrix, resulting in better estimates. In a numerical example, the approach outperforms the extended Kalman filter implemented with constraint handling via ldquoclippingrdquo.

Robust nonlinear filtering for INS/GPS UAV localization

Abstract: Unmanned aerial vehicles (UAVs) are increasingly used in military and scientific research. UAVs rely on accurate location information for a variety of purposes including navigation, motion planning and control, and mission completion. UAV INS/GPS localization is generally used based on navigation filter. Extended Kalman filter is largely used to solve the problem of data fusion and localization, however, EKF suffers from the initialization problem and the linearization errors which severely degrade the performance of the UAV localization estimates. In this paper we propose another innovative alternative, which is based on the Hinfin nonlinear filtering to avoid issues linked with classical filtering techniques and getting a significant robustness. This filtering approach is based on the Hinfin robust control theory, results, comparison with the EKF filter and validation on a simulation of a 3D flight scenario are presented.

UAV formation flight using 3D potential field

Abstract: The paper presents a solution for formation flight and formation reconfiguration of unmanned aerial vehicles (UAVs). Based on a virtual leader approach, combined with an extended local potential field, it is universal applicable by driving the vehiclepsilas auto pilot. The solution is verified, using a group of UAVs based on a simplified small-scale helicopter, which is simulated in MATLABtrade/Simulinktrade. As necessary for helicopters, the potential field approach is realized in 3D including obstacle and collision avoidance. The collision avoidance strategy could be used separately for the sense and avoid problem.

Prescribed performance adaptive control of SISO feedback linearizable systems with disturbances

Abstract: We consider the adaptive control problem for a class of SISO unknown nonlinear systems in the presence of additive input disturbances, with guaranteed prescribed performance. By prescribed performance we mean that the tracking error should converge to an arbitrarily predefined small residual set, with convergence rate no less than a prespecified value, exhibiting a maximum overshoot less than a sufficiently small prespecified constant. A novel output error transformation is introduced to transform the original "constrained" (in the sense of the output error restrictions) system into an equivalent "unconstrained" one. It is proven that stabilization of the "unconstrained" system is sufficient to solve the problem. The proposed robust adaptive controller is smooth and guarantees a uniform ultimate boundedness property for the transformed output error, plus the boundedness of all other signals in the closed loop. A simulation study on a Van der Pol system clarifies and verifies the approach.

Evaluating the risk of unmanned aircraft ground impacts

Abstract: Currently many countries are developing regulation to allow unmanned aircraft systems (UAS) operations in their National Airspace System (NAS). Successful integration requires UAS to achieve, at a minimum, an equivalent level of safety to that of manned aviation. Safety is primarily defined in terms of the risk to human life, although potential collateral damages to property can also be taken into account. This paper presents a novel, general, quite conservative and rather simple method that calculates the probability of fatalities and the fatality rates associated with a ground impact. Spatial analysis results are presented that indicate where unmanned aircraft may fly based on obtained reliability and safety levels and provide a coherent comparison of reliability requirements between unmanned aircraft of different families.

A multi-observer switching strategy for fault-tolerant control of a quadrotor helicopter

Abstract: This paper deals with fault tolerant control of the attitude of a four-rotor helicopter (quadrotor). A set of non-linear estimators/observers is implemented to estimate the attitude of the quadrotor. Each estimator has been designed in order to be sensitive to faults in all sensors but one. The attitude estimate that exhibits the smaller error when compared to the attitude computed from the mechanical model is selected to feed the controller. Thus the strategy proposed selects, at each instant, the estimator/observer that minimizes a suitable switching criterion. Simulations of the controlled system, under various scenarios, illustrate that the proposed switching strategy is able to maintain performance levels and to preserve stability under the occurrence of sensor failures.

Fault detection and isolation with robust principal component analysis

Abstract: Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance matrix of the data is very sensitive to outliers in the training data set. Usually robust principal component analysis was applied to remove the effect of outliers on the PCA model. In this paper, a fast two-step algorithm is proposed. First, the objective was to find a robust PCA model that could be used for outliers detection and isolation. Hence a scale-M estimator (R.A. Maronna, 2005) is used to determine a robust model. This estimator is computed using an iterative re-weighted least squares (IRWLS) procedure. This algorithm is initialized from a very simple estimate derived from a one-step weighted variance-covariance estimate (A. Ruiz-Gazen, 1996). Second, structured residuals are used for multiple fault detection and isolation. These structured residuals are based on the reconstruction principle and the existence condition of such residuals is used to determine the detectable faults and the isolable faults. The proposed scheme avoids the combinatorial explosion of faulty scenarios related to multiple faults to consider. Then, this procedure for outliers detection and isolation is successfully applied to an example with multiple faults.

Rolling element bearing feature extraction and anomaly detection based on vibration monitoring

Abstract: In this paper, an anomaly detection structure, in which different types of anomaly detection routines can be applied, is proposed. Bearing fault modes and their effects on the bearing vibration are discussed. Based on this, a feature extraction method is developed to overcome the limitation of time domain features. Experimental data from bearings under different operating conditions are used to verify the proposed method. The results show that the extracted feature has a monotonic decrease trend as the dimension of fault increases. The feature also has the ability to compensate the variation of rotating speed. The proposed structure are verified with three different detection routines, pdf-based, k-nearest neighbor, and particle-filter-based approaches.

Design and control of a manipulator arm driven by pneumatic muscle actuators

Abstract: It seems that the pneumatic artificial muscles (PAMs) have a very great potential in industrial applications for the actuation of new types of robots and manipulators. Their properties such as compactness, high strength, high power-to-weight ratio, inherent safety and simplicity are worthy features in advanced robotics. In this paper we describe the design, construction and experimental testing of a single-joint manipulator arm actuated by pneumatic muscle actuators. An antagonistic muscle pair is used in a linear translational sense to produce a force or in a rotational sense to produce a required torque on the pulley. The concept, operating principle and elementary properties of pneumatic muscle actuators are explained. A nonlinear mathematical model of the manipulator arm driven by pneumatic artificial muscles and controlled with proportional control valve is derived, which is used in a numerical simulation program. The experiments were carried out on practically realized manipulator actuated by pair of muscle actuators set into antagonism configuration.

Fault detection and isolation using sliding mode observer for uncertain Takagi-Sugeno fuzzy model

Abstract: This paper addresses fault detection and isolation (FDI) problem using a sliding mode fuzzy observer on the basis of a uncertain Takagi-Sugeno (T-S) fuzzy model. First, a robust fuzzy observer with respect to the uncertainties is designed. The convergence of the fuzzy observer is performed by the search of suitable Lyapunov matrices. It is shown how to synthesis observers using a set of linear matrix inequalities (LMI) conditions. Once the fuzzy observer is designed, FDI problem for nonlinear systems described by T-S fuzzy systems using the fuzzy observer is presented. A bank of fuzzy observer is then designed in order to investigate fault diagnosis problems. The validity of the proposed methodology is illustrated on a dynamic vehicle model.

UAV collision avoidance using cooperative predictive control

Abstract: This article describes the use of predictive control for the decentralized cooperative control of unmanned aerial vehicles in an unfamiliar three-dimensional environment. It is assumed that each vehicle is equipped with an autopilot and a trajectory control unit. The autopilot insures the stability of the vehicle. The setpoints of the autopilot are calculated by the trajectory control unit, thus forming a cascade control structure. The trajectory control unit relies on a predictive control algorithm to calculate the optimal commands (autopilot setpoints) such that the vehicle will reach fixed targets at known positions while avoiding static obstacles that are detected en route. The advantage in using predictive control is that it offers great flexibility in the objective function to optimize while respecting constraints such as command limits, limits on the displacement that a vehicle can carry out, and the constraints that allow obstacle avoidance. The principle proposed in order to avoid static obstacles (that are assumed ellipsoid) is to verify that the predicted vehicle trajectory does not intersect these obstacles. With the objective to increase performance, cooperation between vehicles must also be privileged. Thus, if some vehicles are within the communication range, they can share the position and shape of the obstacles they have detected. Simulations illustrate the method and higlight the benefits of cooperation.

A reasoning-based framework for car driver’s stress prediction

Abstract: In this work, we present a novel methodology based on a dynamic Bayesian network for the estimation of car drivers stress produced due to specific driving events. the proposed methodology monitors driverpsilas stress using selected biosignals and provides a probabilistic framework in order to infer the driving events resulting in stress level increase. We conducted a series of experiments under real driving conditions. The extracted results indicate a strong correlation between the level of the stress as reported by the driver and the outcome of our model.

Model predictive control in urban traffic network management

Abstract: The paper investigates a model predictive control (MPC) strategy specialized in urban traffic management in order to relieve traffic congestion, reduce travel time and improve homogenous traffic flow. Over the theory the realization of the control method is also presented. To validate the effectiveness of the controller a busy traffic network was chosen for test field. The MPC strategy was implemented into the test network control system (hardware in loop simulation). The applied environment is a microscopic traffic simulator with mathematical software and proper computational applications for the evaluation. The simulation results prove the effectiveness of the designed MPC based traffic control strategy. The system is able to improve the network efficiency and reduce travel time, creating optimal flow in the network subjected to control input constraints.

Control of an experimental mini quad-rotor UAV

Abstract: The design and the initial realization of control on an experimental in-door unmanned autonomous quadrotor helicopter is presented. This is a hierarchical embedded model-based control scheme that is built upon the concept of back-stepping, and is applied on an electric motor-driven quadrotor UAV hardware that is equipped with an embedded on-board computer, inertial sensor unit, as well as facilities that make it suitable to be involved in an in-door positioning system, and wireless digital communication network. This realization forms an important step in the development process of a more advanced realization of an UAV suitable for practical applications; it aims clarification of the control principles, acquiring experience in solving control tasks, and getting skills for the development of further realizations.

Mechatronic design and position control of a novel ball and plate system

Abstract: The mechatronic design of a novel mechanism for ball and plate system is discussed. A webcam provides the system with feedback of the ball's position. A heuristic technique for image processing is introduced. The kinematics and dynamics of the system are also described. Supervisory fuzzy control and sliding control techniques are proposed to perform position control for the system. Experimental results corroborate the validity of the controllers.

State estimation under nonlinear state inequality constraints. A tracking application

Abstract: This paper proposes a general method for dealing with state estimation under nonlinear state soft inequality constraints. This method is based on the projection approach, and then has the advantage to be compatible with any kind of state estimator. In order to be taken into account, the nonlinear constraints are linearized about the constrained state using an iterated approach. The proposed algorithm is tested on a three- dimension tracking application with nonlinear constraints on the moving body acceleration. The results are compared with those of an unconstrained Kalman filter.

Damping inter-area modes of oscillation using an adaptive fuzzy power system stabilizer

Abstract: This paper introduces an indirect variable-structure adaptive fuzzy controller as a power system stabilizer (IDVSFPSS) used to damp inter-area modes of oscillation following disturbances in power systems. In contrast to IEEE standard multi-band power system stabilizer (MB-PSS) , indirect adaptive fuzzy-based stabilizer are more efficient because they cope with oscillations at different operating points. A nominal model of the power system is identified on-line using a variable structure identifier. A feedback linearization-based control law is implemented using the identified model. The gains of the controller are tuned via a particle swarm optimization routine to ensure system stability and minimum sum of the squares of the speed deviations. A benchmark problem of a 4-machine 2-area power system is used to demonstrate the performance of the proposed controller and to show its superiority over other conventional stabilizers used in the literature.

Localization of pallets in warehouses using Wireless Sensor Networks

Abstract: The intra-logistics is constantly subject to technological developments and changes. In the field of warehousing in former times, articles were identified over bar code. Nowadays with the growing requirements for mobility and reliability increasingly radio technologies are employed to request information. Wireless sensor networks simplify the stock accounting through a decentralization of the data storage and establish a basis for localization. On the basis of this networks the position of pallets can be transmitted over radio with the benefit to expedite the work flow. This paper analysis the applications of a special sensor network (nanoLOC system) for operations within the warehouse management. This radio positioning systems affords the determination of position based on measuring the signal propagation delay between two devices. Referring to the localization of goods with the method of the extended Kalman filter, measurements are realized and are presented as well as evaluated below.

An error analysis in the algebraic estimation of a noisy sinusoidal signal

Abstract: The classic example of a noisy sinusoidal signal permits for the first time to derive an error analysis for a new algebraic and non-asymptotic estimation technique. This approach yields a selection of suitable parameters in the estimation procedure, in order to minimize the noise corruption.

On the fragility of PI controllers for time-delay SISO systems

Abstract: This paper focuses on the fragility analysis of PI-controllers for single-input-single-output (SISO) systems subject to input (or output) delays. Using a geometric approach, we present a simple and user-friendly approach not only to analyze the fragility of PI controllers, but also to provide practical guidelines for the design of non-fragile PI controllers. The proposed methodology is illustrated by analyzing several examples encountered in the control literature.

Solving dynamic fault trees using a new Hybrid Bayesian Network inference algorithm

Abstract: We present a hybrid Bayesian network (HBN) framework to analyse dynamic fault trees. By incorporating a new approximate inference algorithm for HBNs involving dynamically discretising the domain of all continuous variables, accurate approximations for the failure distribution of both static and dynamic fault tree constructs are obtained. Unlike in other approaches no numerical integration techniques or simulation methods are required. Moreover, no exact expression for the posterior marginal is needed and no conditional probability tables need to be completed. Sensitivity analysis, uncertainty, diagnosis, common cause failure analysis, can all be easily performed within this framework. Posterior estimates of parameterised marginal failure distributions can also be obtained using available raw failure data together with prior information from expert judgement.

Navigation of an autonomous mobile robot using EKF-SLAM and FastSLAM

Abstract: This paper presents a navigation of an autonomous robot using simultaneous localization and mapping (SLAM) in outdoor environments. SLAM is a method in which localization and mapping are done simultaneously in an unknown environment without an access to a priori map. This paper introduces a probabilistic approach to a SLAM problem under Gaussian and non-Gaussian conditions and offers alternative solutions. First, an extended Kalman filter algorithm for the SLAM problem under Gaussian condition will be shown. Also, an alternative way of dealing with SLAM problem with assumption of non-Gaussian and called FastSLAM will be analyzed. FastSLAM is an algorithm that using Rao-Blackwellised method for particle filtering, estimates the path of robot while the landmarks positions which are mutually independent and with no correlation, can be estimated by EKF. This is done using a factorization that fits very well into SLAM problem based on a Bayesian network. In this paper, a real outdoor autonomous robot is presented and several experiments have been performed based on both methods. The experimental results are discussed and compared.

Step by step robust nonlinear PI for attitude stabilisation of a four-rotor mini-aircraft

Abstract: Based on the Euler angles parameterization, a new approach for the attitude control of a vertical take-off and landing (VTOL) quadrotor aircraft is proposed. It rests on the combination of the backstepping technique and a nonlinear robust PI controller. The integral action gain is nonlinear and based on a switching function that ensures a robust behaviour for the overall control law. One of the strengths of the proposed approach is its robustness with respect to plant parameters uncertainties. The proposed approach has been tested in simulation and shows good performance.

Observers for Lipschitz nonlinear descriptor systems: Application to unknown inputs systems

Abstract: This paper deals with the design of reduced order observers for a class of nonlinear descriptor systems. The order of these observer is qlesn , where n is the dimension of the semi state. A new method is presented, the conditions for the existence of these observers are given and sufficient conditions for their stability are derived using linear matrix inequalities (LMIs) formulation. A numerical example is presented to demonstrate the effectiveness of the developed method.

Robust sliding mode control of a DFIG variable speed wind turbine for power production optimization

Abstract: A cascaded nonlinear sliding mode controller is proposed for power production optimization of a variable speed wind turbine equipped with a Doubly Fed Induction Generator (DFIG). The inner loop controller ensures a robust tracking of both generator torque and rotor flux, while the outer loop controller achieves a robust tracking of the optimal blade rotor speed to optimize wind energy capture. The global controller is firstly tested with a simplified mathematical model of the aeroturbine and DFIG for a high-turbulence wind speed profile. Secondly, the aeroturbine controller is validated upon a flexible wind turbine simulator. The obtained results show better performance in comparison with the existing controllers in presence of parameters variations.

Realization problem for positive fractional continuous-time systems

Abstract: The realization problem for positive fractional continuous-time linear systems is addressed. Sufficient conditions for the existence of positive realizations for continuous-time linear systems are established. Procedures for computation of positive fractional realizations for SISO and MIMO continuous-time linear systems are proposed and illustrated by numerical examples.

Wave prediction and fuzzy logic control of wave energy converters in irregular waves

Abstract: This paper presents a short comparison of different existing and proposed wave prediction models, which in turn are used to control wave energy converters (WEC) in irregular waves. The objective of the control action is to increase the energy conversion. The prediction models are compared based on the contribution to the prediction of the individual filter weights, in an effort to reduce the filter order. The controller is based on adjusting the short term stiffness and damping of the power take off (PTO) of the WEC. The control action, which is a fuzzy logic (FL) based design, is supported by utilizing nominal damping and stiffness values determined for the given sea state and instantaneous wave using a simple genetic algorithm (GA). The WEC chosen is comprised of a spherical buoy and is modeled using the bond-graph technique. The simulation carried out indicates the proposed algorithm increases the energy conversion of WEC in irregular waves compared to the no control case.

Output feedback stabilization of positive switching linear discrete-time systems

Abstract: The problem of stabilizing positive switching discrete-time systems by output feedback is studied and solved in this paper. First, necessary and sufficient conditions for the existence of such controllers are presented for non-switching positive systems, which are then extended to positive switching systems. The proposed conditions, formulated as LMIs, can be directly used for controller synthesis. An example made up of three subsystems is studied to show the applicability of the proposed technique.