Ponències/Comunicacions de congressos
http://hdl.handle.net/2117/1126
2016-09-26T07:17:01ZComparison of two non-linear model-based control strategies for autonomous vehicles
http://hdl.handle.net/2117/89595
Comparison of two non-linear model-based control strategies for autonomous vehicles
Alcalá, Eugenio; Sellart, Laura; Puig Cayuela, Vicenç; Quevedo Casín, Joseba Jokin; Saludes Closa, Jordi; Vázquez, David; López, Antonio
This paper presents the comparison of two nonlinear model-based control strategies for autonomous cars. A control oriented model of vehicle based on a bicycle model is used. The two control strategies use a model reference approach. Using this approach, the error dynamics model is developed. Both controllers receive as input the longitudinal, lateral and orientation errors generating as control outputs the steering angle and the velocity of the vehicle. The first
control approach is based on a non-linear control law that is designed by means of the Lyapunov direct approach. The second approach is based on a sliding mode-control that defines a set of sliding surfaces over which the error trajectories will converge. The main advantage of the sliding-control technique is the robustness against non-linearities and parametric uncertainties in the model. However, the main drawback of first ordersliding mode is the chattering, so it has been implemented a high order sliding mode control. To test and compare the proposed control strategies, different path following scenarios are used in simulation.
2016-09-06T09:49:33ZAlcalá, EugenioSellart, LauraPuig Cayuela, VicençQuevedo Casín, Joseba JokinSaludes Closa, JordiVázquez, DavidLópez, AntonioThis paper presents the comparison of two nonlinear model-based control strategies for autonomous cars. A control oriented model of vehicle based on a bicycle model is used. The two control strategies use a model reference approach. Using this approach, the error dynamics model is developed. Both controllers receive as input the longitudinal, lateral and orientation errors generating as control outputs the steering angle and the velocity of the vehicle. The first
control approach is based on a non-linear control law that is designed by means of the Lyapunov direct approach. The second approach is based on a sliding mode-control that defines a set of sliding surfaces over which the error trajectories will converge. The main advantage of the sliding-control technique is the robustness against non-linearities and parametric uncertainties in the model. However, the main drawback of first ordersliding mode is the chattering, so it has been implemented a high order sliding mode control. To test and compare the proposed control strategies, different path following scenarios are used in simulation.Model-based optimal sensor placement approaches to fuel cell stack system fault diagnosis
http://hdl.handle.net/2117/87521
Model-based optimal sensor placement approaches to fuel cell stack system fault diagnosis
Sarrate Estruch, Ramon; Nejjari Akhi-Elarab, Fatiha; Rosich Oliva, Albert
The problem of optimal sensor placement for FDI consists in d
etermining the set of sensors
that minimizes a pre-defined cost function satisfying at the
same time a pre-established set of FDI
specifications for a given set of faults. This paper recalls t
hree model-based optimal sensor location
approaches: an Incremental search, a Heuristic search and a
Binary Integer Linear Programming (BILP)
formulation. The main contribution of this paper is a compar
ative study that addresses efficiency,
flexibility and other issues. The performance of the approac
hes is demonstrated by an application to
a fuel cell stack system.
2016-05-31T08:56:39ZSarrate Estruch, RamonNejjari Akhi-Elarab, FatihaRosich Oliva, AlbertThe problem of optimal sensor placement for FDI consists in d
etermining the set of sensors
that minimizes a pre-defined cost function satisfying at the
same time a pre-established set of FDI
specifications for a given set of faults. This paper recalls t
hree model-based optimal sensor location
approaches: an Incremental search, a Heuristic search and a
Binary Integer Linear Programming (BILP)
formulation. The main contribution of this paper is a compar
ative study that addresses efficiency,
flexibility and other issues. The performance of the approac
hes is demonstrated by an application to
a fuel cell stack system.Sensor placement for fault diagnosis performance maximization under budgetary constraints
http://hdl.handle.net/2117/87519
Sensor placement for fault diagnosis performance maximization under budgetary constraints
Sarrate Estruch, Ramon; Nejjari Akhi-Elarab, Fatiha; Rosich Oliva, Albert
The success of any diagnosis strategy critically depends on the sensors measuring process variables. This paper presents a strategy based on diagnosability maximization for optimally locating sensors in distribution networks. The goal is to characterize and determine the set of sensors that guarantees a maximum degree of diagnosability taking into account a given sensor configuration cardinality constraint. The strategy is based on the structural model of the system under consideration. Structural analysis is a powerful tool for determining diagnosis possibilities and evaluating whether the number and the location of sensors are adequate in order to meet some diagnosis specifications. The proposed approach is successfully applied to leakage detection in a Drinking Water Distribution Network.
2016-05-31T08:34:17ZSarrate Estruch, RamonNejjari Akhi-Elarab, FatihaRosich Oliva, AlbertThe success of any diagnosis strategy critically depends on the sensors measuring process variables. This paper presents a strategy based on diagnosability maximization for optimally locating sensors in distribution networks. The goal is to characterize and determine the set of sensors that guarantees a maximum degree of diagnosability taking into account a given sensor configuration cardinality constraint. The strategy is based on the structural model of the system under consideration. Structural analysis is a powerful tool for determining diagnosis possibilities and evaluating whether the number and the location of sensors are adequate in order to meet some diagnosis specifications. The proposed approach is successfully applied to leakage detection in a Drinking Water Distribution Network.Quasi-LPV modelling and non-linear identification of a twin rotor system
http://hdl.handle.net/2117/87514
Quasi-LPV modelling and non-linear identification of a twin rotor system
Nejjari Akhi-Elarab, Fatiha; Rotondo, Damiano; Puig Cayuela, Vicenç; Innocenti, Mario
This paper describes the experimental identifi-
cation of the parameters of the Twin Rotor MIMO System
(TRMS) non-linear model using data collected from the real lab
set-up. From this non-linear model, a quasi-linear parameter
varying (quasi-LPV) model has also been derived using a state
transformation. This quasi-LPV model is approximated with
a polytopic model using the bounding box approach. Such
a model can later be used for control design. The model
parameters have been calibrated by means of non-linear least-
squares identification approach. Once the calibrated non-linear
model has been obtained, a simulator has been built and
validated against real data showing satisfactory results when
compared to real data.
2016-05-31T08:12:01ZNejjari Akhi-Elarab, FatihaRotondo, DamianoPuig Cayuela, VicençInnocenti, MarioThis paper describes the experimental identifi-
cation of the parameters of the Twin Rotor MIMO System
(TRMS) non-linear model using data collected from the real lab
set-up. From this non-linear model, a quasi-linear parameter
varying (quasi-LPV) model has also been derived using a state
transformation. This quasi-LPV model is approximated with
a polytopic model using the bounding box approach. Such
a model can later be used for control design. The model
parameters have been calibrated by means of non-linear least-
squares identification approach. Once the calibrated non-linear
model has been obtained, a simulator has been built and
validated against real data showing satisfactory results when
compared to real data.Fault estimation and virtual sensor FTC approach for LPV systems
http://hdl.handle.net/2117/87513
Fault estimation and virtual sensor FTC approach for LPV systems
Montes de Oca, Saúl; Rotondo, Damiano; Nejjari Akhi-Elarab, Fatiha; Puig Cayuela, Vicenç
In this paper, a Fault Tolerant Control (FTC) strategy using a virtual sensor for Linear Parameter Varying (LPV) systems is proposed. The main idea of this FTC method is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty sensor is modified adding the virtual sensor block that masks the sensor fault. The suggested strategy is an active FTC strategy that reconfigures the virtual sensor on-line taking into account faults and operating point changes. In order to implement the virtual sensor approach, a fault estimation is required. Here, this fault estimation is provided by formulating it as a parameter estimation problem. Then, a block/batch least square approach is used to estimate additive and multiplicative faults. The LPV virtual sensor is designed using polytopic LPV techniques and Linear Matrix Inequalities (LMIs). To assess the performance of the proposed approach a two degree of freedom helicopter simulator is used.
2016-05-31T07:50:49ZMontes de Oca, SaúlRotondo, DamianoNejjari Akhi-Elarab, FatihaPuig Cayuela, VicençIn this paper, a Fault Tolerant Control (FTC) strategy using a virtual sensor for Linear Parameter Varying (LPV) systems is proposed. The main idea of this FTC method is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty sensor is modified adding the virtual sensor block that masks the sensor fault. The suggested strategy is an active FTC strategy that reconfigures the virtual sensor on-line taking into account faults and operating point changes. In order to implement the virtual sensor approach, a fault estimation is required. Here, this fault estimation is provided by formulating it as a parameter estimation problem. Then, a block/batch least square approach is used to estimate additive and multiplicative faults. The LPV virtual sensor is designed using polytopic LPV techniques and Linear Matrix Inequalities (LMIs). To assess the performance of the proposed approach a two degree of freedom helicopter simulator is used.Unfalsified adaptive control for manipulators with parameter uncertainties
http://hdl.handle.net/2117/87027
Unfalsified adaptive control for manipulators with parameter uncertainties
Arango Castro, Jaime Enrique; Ocampo-Martínez, Carlos; Bianchi, Fernando Daniel; Osorio Londoño, Gustavo Adolfo
This work evaluates by simulation the performance of the Unfalsified Adaptive Control (UAC) for Multiple Degree of Freedom (MDoF) serial manipulators. The UAC is a data-driven technique that addresses stability issues of model-based controllers for robot arms with inertial uncertainties. The unfalsified controller selects the most suitable controller from a set, based on performance, to decide whether the controller in the closed loop should be changed, using only system inputs and outputs, i.e., torques and joint variables of the robotic arm, respectively. In this work, performance and robustness is evaluated by simulation on a 5-DoF manipulator showing the ability of the UAC to accomplish tracking tasks in the presence of inertial parameters disturbances.
2016-05-12T17:42:56ZArango Castro, Jaime EnriqueOcampo-Martínez, CarlosBianchi, Fernando DanielOsorio Londoño, Gustavo AdolfoThis work evaluates by simulation the performance of the Unfalsified Adaptive Control (UAC) for Multiple Degree of Freedom (MDoF) serial manipulators. The UAC is a data-driven technique that addresses stability issues of model-based controllers for robot arms with inertial uncertainties. The unfalsified controller selects the most suitable controller from a set, based on performance, to decide whether the controller in the closed loop should be changed, using only system inputs and outputs, i.e., torques and joint variables of the robotic arm, respectively. In this work, performance and robustness is evaluated by simulation on a 5-DoF manipulator showing the ability of the UAC to accomplish tracking tasks in the presence of inertial parameters disturbances.Temperature regulation of a pilot-scale batch reaction system via explicit model predictive control
http://hdl.handle.net/2117/86962
Temperature regulation of a pilot-scale batch reaction system via explicit model predictive control
Sánchez Cossio, Javier; Ortega Álvarez, Juan David; Ocampo-Martínez, Carlos
In this paper, the temperature of a pilot-scale batch reaction system is modeled towards the design of a controller based on the explicit model predictive control (EMPC) strategy. Some mathematical models are developed from experimental data to describe the system behavior. The simplest, yet reliable, model obtained is a (1,1,1)-order ARX polynomial model for which the mentioned EMPC controller has been designed. The resultant controller has a reduced mathematical complexity and, according to the successful results obtained in simulations, will be used directly on the real control system in a next stage of the entire experimental framework.
2016-05-11T17:43:06ZSánchez Cossio, JavierOrtega Álvarez, Juan DavidOcampo-Martínez, CarlosIn this paper, the temperature of a pilot-scale batch reaction system is modeled towards the design of a controller based on the explicit model predictive control (EMPC) strategy. Some mathematical models are developed from experimental data to describe the system behavior. The simplest, yet reliable, model obtained is a (1,1,1)-order ARX polynomial model for which the mentioned EMPC controller has been designed. The resultant controller has a reduced mathematical complexity and, according to the successful results obtained in simulations, will be used directly on the real control system in a next stage of the entire experimental framework.An application of the Shapley value to perform system partitioning
http://hdl.handle.net/2117/86291
An application of the Shapley value to perform system partitioning
Muros Ponce, Francisco; Maestre Torreblanca, José María; Algaba Durán, Encarnación; Ocampo-Martínez, Carlos; Fernández Camacho, Eduardo
We introduce a new method to perform the partitioning of non-centralized dynamical linear systems based on the relevance of the possible interconnections among the smallest components of the system. In particular, we analyze the importance of the interconnections using game theoretical tools, so that they can be arranged as a function of their expected contribution to the overall system performance. In addition, this method allows to identify unnecessary interconnections and highlights the most appropriate communication links facing the application of distributed control schemes. The effectiveness of the proposed method is shown at the end of this work by means of a numerical example.
2016-04-27T17:29:11ZMuros Ponce, FranciscoMaestre Torreblanca, José MaríaAlgaba Durán, EncarnaciónOcampo-Martínez, CarlosFernández Camacho, EduardoWe introduce a new method to perform the partitioning of non-centralized dynamical linear systems based on the relevance of the possible interconnections among the smallest components of the system. In particular, we analyze the importance of the interconnections using game theoretical tools, so that they can be arranged as a function of their expected contribution to the overall system performance. In addition, this method allows to identify unnecessary interconnections and highlights the most appropriate communication links facing the application of distributed control schemes. The effectiveness of the proposed method is shown at the end of this work by means of a numerical example.Icing detection in unmanned aerial vehicles with longitudinal motion using an LPV unknown input observer
http://hdl.handle.net/2117/86191
Icing detection in unmanned aerial vehicles with longitudinal motion using an LPV unknown input observer
Rotondo, Damiano; Cristofaros, A; Johansen, T; Nejjari Akhi-Elarab, Fatiha; Puig Cayuela, Vicenç
This paper proposes a linear parameter varying (LPV) unknown input observer for the diagnosis of actuator faults and icing in unmanned aerial vehicles (UAVs). The accretion of ice layers on wings and control surfaces modifies the shape of the aircraft and alters the performance and controllability of the vehicles. The correct detection of this phenomenon is of paramount importance for the efficient implementation of de-icing techniques. The advantage of deriving the unknown input observer within the LPV framework is the possibility to deal with the nonlinearities of the UAV model by embedding them within some varying parameters. Results obtained with a Zagi Flying Wing simulator are used to validate the effectiveness of the proposed approach.
2016-04-26T11:28:47ZRotondo, DamianoCristofaros, AJohansen, TNejjari Akhi-Elarab, FatihaPuig Cayuela, VicençThis paper proposes a linear parameter varying (LPV) unknown input observer for the diagnosis of actuator faults and icing in unmanned aerial vehicles (UAVs). The accretion of ice layers on wings and control surfaces modifies the shape of the aircraft and alters the performance and controllability of the vehicles. The correct detection of this phenomenon is of paramount importance for the efficient implementation of de-icing techniques. The advantage of deriving the unknown input observer within the LPV framework is the possibility to deal with the nonlinearities of the UAV model by embedding them within some varying parameters. Results obtained with a Zagi Flying Wing simulator are used to validate the effectiveness of the proposed approach.Shifting linear quadratic control of constrained continuous-time descriptor LPV systems
http://hdl.handle.net/2117/85887
Shifting linear quadratic control of constrained continuous-time descriptor LPV systems
Rotondo, Damiano; Nejjari Akhi-Elarab, Fatiha; Puig Cayuela, Vicenç
Recently, the concept of shifting linear quadratic control (SLQC), where some varying parameters are introduced and used to schedule the weighting matrices of a quadratic cost function, has been introduced. This paper further explores this concept by considering the presence of constraints in the system to be controlled. In particular, two types of constraints are considered: a) algebraic constraints between the variables of the system; and b) constraints on the allowed values for the input and the state variables. The proposed solution, investigated under the descriptor linear parameter varying (D-LPV) framework, requires solving a set of linear matrix inequalities (LMIs), a problem for which efficient solvers are available nowadays. A numerical example illustrates the application of the proposed theory.
2016-04-19T11:23:24ZRotondo, DamianoNejjari Akhi-Elarab, FatihaPuig Cayuela, VicençRecently, the concept of shifting linear quadratic control (SLQC), where some varying parameters are introduced and used to schedule the weighting matrices of a quadratic cost function, has been introduced. This paper further explores this concept by considering the presence of constraints in the system to be controlled. In particular, two types of constraints are considered: a) algebraic constraints between the variables of the system; and b) constraints on the allowed values for the input and the state variables. The proposed solution, investigated under the descriptor linear parameter varying (D-LPV) framework, requires solving a set of linear matrix inequalities (LMIs), a problem for which efficient solvers are available nowadays. A numerical example illustrates the application of the proposed theory.