SAC - Sistemes Avançats de Control
http://hdl.handle.net/2117/1124
2024-03-29T07:33:53Z
2024-03-29T07:33:53Z
Non-intrusive condition monitoring based on event detection and functional data clustering
Bermeo Ayerbe, Miguel Ángel
Ocampo-Martínez, Carlos
Díaz Rozo, Javier
http://hdl.handle.net/2117/405014
2024-03-25T01:34:52Z
2024-03-20T12:33:55Z
Non-intrusive condition monitoring based on event detection and functional data clustering
Bermeo Ayerbe, Miguel Ángel; Ocampo-Martínez, Carlos; Díaz Rozo, Javier
Implementing monitoring electricity consumption strategies in industrial environments provides improvements in both the maintenance process and energy efficiency. The contribution of this work is an industry-oriented non-intrusive load monitoring approach based on an unsupervised algorithm, encompassing a method of event detection, functional data clustering, and condition monitoring. With this method, multiple devices can be monitored by only one electric meter in industrial environments, enhancing the early detection of anomalies and energy inefficiencies. The proposed approach presents a robust event detection to deal with different industrial contexts due to its intuitive parameters, which allows adapting the detection to be more sensitive or to filter out higher noise variations. Unlike other feature-based clusterings, the proposed functional data clustering enables high-precision identification of transient state patterns, characterizing specific shapes for each pattern to properly cluster them, and provides higher reliability during load detection. Thus, this load detection segments the power consumption to extract transient states and identify which load acts on each event based on functional data clusters. By detecting when loads start to consume, the proposed energy disaggregation extracts the frequency spectrum of each device from the aggregate current consumption, which is used in a condition monitoring strategy to track the spectrum behavior of each device. In this way, the condition of multiple loads can be monitored using a single electric meter, whose information can be relevant to accurately schedule maintenance interventions and detect anomalies or inefficiencies early. The proposed approach was validated in three industrial contexts: The load detection accuracy was verified in an industrial testbed, giving a precision higher than 99% for monitoring five devices. The second and third industrial scenarios validate the accuracy of the proposed condition monitoring method. The last scenario was carried out at Bilbao airport to track the condition of multiple conveyor belts of a baggage handling system located at check-in. As a result, the degradation trend of three sets of conveyor belts was monitored.
2024-03-20T12:33:55Z
Bermeo Ayerbe, Miguel Ángel
Ocampo-Martínez, Carlos
Díaz Rozo, Javier
Implementing monitoring electricity consumption strategies in industrial environments provides improvements in both the maintenance process and energy efficiency. The contribution of this work is an industry-oriented non-intrusive load monitoring approach based on an unsupervised algorithm, encompassing a method of event detection, functional data clustering, and condition monitoring. With this method, multiple devices can be monitored by only one electric meter in industrial environments, enhancing the early detection of anomalies and energy inefficiencies. The proposed approach presents a robust event detection to deal with different industrial contexts due to its intuitive parameters, which allows adapting the detection to be more sensitive or to filter out higher noise variations. Unlike other feature-based clusterings, the proposed functional data clustering enables high-precision identification of transient state patterns, characterizing specific shapes for each pattern to properly cluster them, and provides higher reliability during load detection. Thus, this load detection segments the power consumption to extract transient states and identify which load acts on each event based on functional data clusters. By detecting when loads start to consume, the proposed energy disaggregation extracts the frequency spectrum of each device from the aggregate current consumption, which is used in a condition monitoring strategy to track the spectrum behavior of each device. In this way, the condition of multiple loads can be monitored using a single electric meter, whose information can be relevant to accurately schedule maintenance interventions and detect anomalies or inefficiencies early. The proposed approach was validated in three industrial contexts: The load detection accuracy was verified in an industrial testbed, giving a precision higher than 99% for monitoring five devices. The second and third industrial scenarios validate the accuracy of the proposed condition monitoring method. The last scenario was carried out at Bilbao airport to track the condition of multiple conveyor belts of a baggage handling system located at check-in. As a result, the degradation trend of three sets of conveyor belts was monitored.
Neuro-fuzzy Takagi Sugeno observer for fault diagnosis in wind turbines
Pérez Pérez, Esvan de Jesús
Puig Cayuela, Vicenç
López Estrada, Francisco Ronay
Valencia Palomo, Guillermo
Santos Ruiz, Ildeberto
http://hdl.handle.net/2117/405005
2024-03-25T01:42:49Z
2024-03-20T10:32:42Z
Neuro-fuzzy Takagi Sugeno observer for fault diagnosis in wind turbines
Pérez Pérez, Esvan de Jesús; Puig Cayuela, Vicenç; López Estrada, Francisco Ronay; Valencia Palomo, Guillermo; Santos Ruiz, Ildeberto
This work proposes a method for fault diagnosis based on Takagi Sugeno (TS) observers and convex models identified with a multioutput adaptive neuro-fuzzy inference system (MANFIS) derived from structural analysis. A bank of zonotopic TS observers is implemented to detect sensors and actuators faults. Unlike other works that require data from fault scenarios to train the MANFIS neural network, only fault-free data are considered. In addition, uncertainty related to aerodynamic loads and measurement noise is considered for testing the proposed method's robustness. The method performance is evaluated using measurements from a 5 MW wind turbine benchmark.
2024-03-20T10:32:42Z
Pérez Pérez, Esvan de Jesús
Puig Cayuela, Vicenç
López Estrada, Francisco Ronay
Valencia Palomo, Guillermo
Santos Ruiz, Ildeberto
This work proposes a method for fault diagnosis based on Takagi Sugeno (TS) observers and convex models identified with a multioutput adaptive neuro-fuzzy inference system (MANFIS) derived from structural analysis. A bank of zonotopic TS observers is implemented to detect sensors and actuators faults. Unlike other works that require data from fault scenarios to train the MANFIS neural network, only fault-free data are considered. In addition, uncertainty related to aerodynamic loads and measurement noise is considered for testing the proposed method's robustness. The method performance is evaluated using measurements from a 5 MW wind turbine benchmark.
Integral sliding-mode fault-tolerant pitch control of wind turbines
Serrano, Fernando E.
Puig Cayuela, Vicenç
http://hdl.handle.net/2117/404934
2024-03-25T01:42:47Z
2024-03-19T12:44:02Z
Integral sliding-mode fault-tolerant pitch control of wind turbines
Serrano, Fernando E.; Puig Cayuela, Vicenç
In this paper, an integral sliding-mode fault-tolerant pitch control of wind turbines is presented. The proposed approach uses a fault diagnosis strategy which consists of a sliding-mode fault diagnosis observer. This observer is based on using an integral sliding-mode estimation scheme by using a suitable Lyapunov functional. Based on the previous fault diagnosis strategy, an integral sliding mode controller is designed by selecting an appropriate sliding mode surface in order to obtain the fault tolerant-control law obtained by also selecting appropriated Lyapunov functional. A wind-turbine case study is used to validate in simulation the the proposed approach.
2024-03-19T12:44:02Z
Serrano, Fernando E.
Puig Cayuela, Vicenç
In this paper, an integral sliding-mode fault-tolerant pitch control of wind turbines is presented. The proposed approach uses a fault diagnosis strategy which consists of a sliding-mode fault diagnosis observer. This observer is based on using an integral sliding-mode estimation scheme by using a suitable Lyapunov functional. Based on the previous fault diagnosis strategy, an integral sliding mode controller is designed by selecting an appropriate sliding mode surface in order to obtain the fault tolerant-control law obtained by also selecting appropriated Lyapunov functional. A wind-turbine case study is used to validate in simulation the the proposed approach.
Job shop scheduling with limited-capacity buffers using constraint programming and genetic algorithms
Pedrosa Alias, Javier
Puig Cayuela, Vicenç
http://hdl.handle.net/2117/404930
2024-03-25T01:42:02Z
2024-03-19T12:19:52Z
Job shop scheduling with limited-capacity buffers using constraint programming and genetic algorithms
Pedrosa Alias, Javier; Puig Cayuela, Vicenç
This article aims to propose a new approach for solving production planning and scheduling in the process industries, in such a way to be adaptable to any manufacturing plant and exploring the use of innovative AI-style technologies. The main contributions of the work are: (i) the design of a specific data format to describe any manufacturing plant (including resources, layout and production recipes), being the input of the method; and (ii) the consideration of limited-capacity production lines with intermediate and final buffers in the optimization. The method involves two stages: the first one corresponds to a deterministic optimization algorithm based on Constraint Programming modelling to solve the JSSP in an ideal scenario with no storage limitation; while the second one is a Genetic Algorithm that only comes into play when the solutions obtained from the first one are infeasible for the available storage, so it is a complementary layer to try to solve the mismatches stochastically.
2024-03-19T12:19:52Z
Pedrosa Alias, Javier
Puig Cayuela, Vicenç
This article aims to propose a new approach for solving production planning and scheduling in the process industries, in such a way to be adaptable to any manufacturing plant and exploring the use of innovative AI-style technologies. The main contributions of the work are: (i) the design of a specific data format to describe any manufacturing plant (including resources, layout and production recipes), being the input of the method; and (ii) the consideration of limited-capacity production lines with intermediate and final buffers in the optimization. The method involves two stages: the first one corresponds to a deterministic optimization algorithm based on Constraint Programming modelling to solve the JSSP in an ideal scenario with no storage limitation; while the second one is a Genetic Algorithm that only comes into play when the solutions obtained from the first one are infeasible for the available storage, so it is a complementary layer to try to solve the mismatches stochastically.
Robust tube-based TS-MPC for safe coordination of autonomous vehicle
Requena Gallego, José
Puig Cayuela, Vicenç
http://hdl.handle.net/2117/404923
2024-03-25T01:41:25Z
2024-03-19T11:59:30Z
Robust tube-based TS-MPC for safe coordination of autonomous vehicle
Requena Gallego, José; Puig Cayuela, Vicenç
In this work, a robust vehicle control scheme is proposed, which is capable of coordinating with nearby vehicles in order to optimally compute control actions that achieve collision-free overtaking maneuvers. The control actions are computed online by a global model predictive control (MPC) controller, which assumes a nominal disturbance-free vehicle model. To reduce the computational burden of the MPCs optimization problem, the vehicle model is reformulated into a pseudo-linear Takagi-Sugeno (TS) representation. Furthermore, the mismatch error between the real and the nominal model is corrected by a local TS H8-optimal state-feedback controller. Moreover, the robust feasibility of the MPCs optimization problem is guaranteed by implementing a tube-based architecture. Finally, the proposed control scheme is tested and validated in a high-fidelity simulation, in which the controlled vehicle was capable of overtaking multiple vehicles while rejecting disturbances.
2024-03-19T11:59:30Z
Requena Gallego, José
Puig Cayuela, Vicenç
In this work, a robust vehicle control scheme is proposed, which is capable of coordinating with nearby vehicles in order to optimally compute control actions that achieve collision-free overtaking maneuvers. The control actions are computed online by a global model predictive control (MPC) controller, which assumes a nominal disturbance-free vehicle model. To reduce the computational burden of the MPCs optimization problem, the vehicle model is reformulated into a pseudo-linear Takagi-Sugeno (TS) representation. Furthermore, the mismatch error between the real and the nominal model is corrected by a local TS H8-optimal state-feedback controller. Moreover, the robust feasibility of the MPCs optimization problem is guaranteed by implementing a tube-based architecture. Finally, the proposed control scheme is tested and validated in a high-fidelity simulation, in which the controlled vehicle was capable of overtaking multiple vehicles while rejecting disturbances.
Zonotopic set-membership state estimation for switched LPV systems
Zhang, Shuang
Puig Cayuela, Vicenç
Ifqir, Sara
http://hdl.handle.net/2117/404922
2024-03-25T01:40:46Z
2024-03-19T11:50:20Z
Zonotopic set-membership state estimation for switched LPV systems
Zhang, Shuang; Puig Cayuela, Vicenç; Ifqir, Sara
This paper addresses the state estimation problem for switched discrete-time Linear Parameter Varying (LPV) systems with mensurable and unmeasurable scheduling parameters. A zonotopic switched polytopic state estimator, considering parameter uncertainty, is proposed based on a Set-Membership Approach (SMA). Taking Average Dwell Time (ADT) into account, a new criterion is proposed to guarantee the convergence of the estimation. An application to vehicle lateral dynamics state estimation is used as case study. Simulation results reveal the effectiveness of the proposed algorithm and demonstrate advantages over the existing methods.
2024-03-19T11:50:20Z
Zhang, Shuang
Puig Cayuela, Vicenç
Ifqir, Sara
This paper addresses the state estimation problem for switched discrete-time Linear Parameter Varying (LPV) systems with mensurable and unmeasurable scheduling parameters. A zonotopic switched polytopic state estimator, considering parameter uncertainty, is proposed based on a Set-Membership Approach (SMA). Taking Average Dwell Time (ADT) into account, a new criterion is proposed to guarantee the convergence of the estimation. An application to vehicle lateral dynamics state estimation is used as case study. Simulation results reveal the effectiveness of the proposed algorithm and demonstrate advantages over the existing methods.
Nonlinear observer for online concentration estimation in vanadium flow batteries based on half-cell voltage measurements
Puleston, Thomas Paul
Cecilia Piñol, Andreu
Costa Castelló, Ramon
Serra, Maria
http://hdl.handle.net/2117/404918
2024-03-25T01:43:53Z
2024-03-19T11:14:50Z
Nonlinear observer for online concentration estimation in vanadium flow batteries based on half-cell voltage measurements
Puleston, Thomas Paul; Cecilia Piñol, Andreu; Costa Castelló, Ramon; Serra, Maria
This paper presents a nonlinear observer to estimate the active species concentrations in vanadium flow batteries. To conduct the estimation, the observer relies only on current, flow rate and two half-cell voltage measurements. In contrast to previous works in the field, the proposed observer is capable to deal simultaneously with two significant and challenging conditions: (1) a not necessarily high flow rate, which results in different concentrations for tanks and cells, and (2) presence of crossover and oxidation side reactions, that result in imbalance between the electrolytes on the positive and negative sides of the system. The stability and convergence of the observer are formally demonstrated using a Lyapunov analysis and subsequently validated through comprehensive computer simulations. Finally, utilising the information provided by the observer, a strategy to independently regulate the flow rate of each electrolyte based on their individual state of charge is developed.
2024-03-19T11:14:50Z
Puleston, Thomas Paul
Cecilia Piñol, Andreu
Costa Castelló, Ramon
Serra, Maria
This paper presents a nonlinear observer to estimate the active species concentrations in vanadium flow batteries. To conduct the estimation, the observer relies only on current, flow rate and two half-cell voltage measurements. In contrast to previous works in the field, the proposed observer is capable to deal simultaneously with two significant and challenging conditions: (1) a not necessarily high flow rate, which results in different concentrations for tanks and cells, and (2) presence of crossover and oxidation side reactions, that result in imbalance between the electrolytes on the positive and negative sides of the system. The stability and convergence of the observer are formally demonstrated using a Lyapunov analysis and subsequently validated through comprehensive computer simulations. Finally, utilising the information provided by the observer, a strategy to independently regulate the flow rate of each electrolyte based on their individual state of charge is developed.
Scheduling inland waterway transport vessels and locks using a switching max-plus-linear systems approach
Segovia Castillo, Pablo
Pesselse, Mike
van den Boom, Ton
Reppa, Vasso
http://hdl.handle.net/2117/404429
2024-03-18T01:57:10Z
2024-03-13T12:26:28Z
Scheduling inland waterway transport vessels and locks using a switching max-plus-linear systems approach
Segovia Castillo, Pablo; Pesselse, Mike; van den Boom, Ton; Reppa, Vasso
This paper considers the inland waterborne transport (IWT) problem, and presents a scheduling approach for inland vessels and locks to generate optimal vessel and lock timetables. The scheduling strategy is designed in the switching max-plus-linear (SMPL) systems framework, as these are characterized by a number of features that make them well suited to represent the IWT problem. In particular, the resulting model is linear in the max-plus algebra, and SMPL systems can switch between modes, an interesting feature due to the presence of vessel routing and ordering constraints in the model. Moreover, SMPL systems can be transformed into mixed-integer linear programming (MILP) problems, for which efficient solvers are available. Finally, a realistic case study is used to test the approach and assess its effectiveness.
2024-03-13T12:26:28Z
Segovia Castillo, Pablo
Pesselse, Mike
van den Boom, Ton
Reppa, Vasso
This paper considers the inland waterborne transport (IWT) problem, and presents a scheduling approach for inland vessels and locks to generate optimal vessel and lock timetables. The scheduling strategy is designed in the switching max-plus-linear (SMPL) systems framework, as these are characterized by a number of features that make them well suited to represent the IWT problem. In particular, the resulting model is linear in the max-plus algebra, and SMPL systems can switch between modes, an interesting feature due to the presence of vessel routing and ordering constraints in the model. Moreover, SMPL systems can be transformed into mixed-integer linear programming (MILP) problems, for which efficient solvers are available. Finally, a realistic case study is used to test the approach and assess its effectiveness.
A model predictive scheduling strategy for coordinated inland vessel navigation and bridge operation
Segovia Castillo, Pablo
Puig Cayuela, Vicenç
Reppa, Vasso
http://hdl.handle.net/2117/404421
2024-03-22T01:26:28Z
2024-03-13T12:13:30Z
A model predictive scheduling strategy for coordinated inland vessel navigation and bridge operation
Segovia Castillo, Pablo; Puig Cayuela, Vicenç; Reppa, Vasso
This paper presents the design of a model predictive scheduling strategy to address the inland waterborne transport (IWT) problem considering bridges that must open to enable vessel passage. The main contribution is the formulation of a control-oriented model of the problem, including propositional logic expressions that characterize system behavior and their conversion into (in)equality constraints. The resulting model is embedded into a predictive scheduling approach to determine bridge opening timetables and vessel passage times in a coordinated manner. The effectiveness of the strategy is demonstrated on a realistic case study based on the Rhine-Alpine corridor.
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
2024-03-13T12:13:30Z
Segovia Castillo, Pablo
Puig Cayuela, Vicenç
Reppa, Vasso
This paper presents the design of a model predictive scheduling strategy to address the inland waterborne transport (IWT) problem considering bridges that must open to enable vessel passage. The main contribution is the formulation of a control-oriented model of the problem, including propositional logic expressions that characterize system behavior and their conversion into (in)equality constraints. The resulting model is embedded into a predictive scheduling approach to determine bridge opening timetables and vessel passage times in a coordinated manner. The effectiveness of the strategy is demonstrated on a realistic case study based on the Rhine-Alpine corridor.
An output-feedback fault-tolerant control approach for multiple faults
Pazera, Marcin
Witczak, Marcin
Puig Cayuela, Vicenç
Aubrun, C
http://hdl.handle.net/2117/404420
2024-03-13T12:20:26Z
2024-03-13T12:10:54Z
An output-feedback fault-tolerant control approach for multiple faults
Pazera, Marcin; Witczak, Marcin; Puig Cayuela, Vicenç; Aubrun, C
This paper proposes an output-feedback fault-tolerant control approach for multiple faults. The proposed approach is able to deal with both sensors and actuator faults. Moreover, the disturbances are assumed to be bounded within an ellipsoidal sets. The proposed strategy boils down to solving a set of LMIs along with an auxiliary parameter, which determines the convergence rate of the approach. Finally, the proposed strategy is illustrated with two-rotor aerodynamical system.
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
2024-03-13T12:10:54Z
Pazera, Marcin
Witczak, Marcin
Puig Cayuela, Vicenç
Aubrun, C
This paper proposes an output-feedback fault-tolerant control approach for multiple faults. The proposed approach is able to deal with both sensors and actuator faults. Moreover, the disturbances are assumed to be bounded within an ellipsoidal sets. The proposed strategy boils down to solving a set of LMIs along with an auxiliary parameter, which determines the convergence rate of the approach. Finally, the proposed strategy is illustrated with two-rotor aerodynamical system.