Pub Date : 2024-10-16DOI: 10.1109/TCST.2024.3473772
Yuyu Yao;Mayuresh V. Kothare
Vagal nerve stimulation (VNS) is currently under investigation for the treatment of various cardiovascular diseases including heart failure, arrhythmia, and hypertension. In preclinical and clinical studies, VNS stimulation parameters are heuristically determined in the open loop. However, its therapeutic efficacy remains inconclusive, strongly suggesting the need for a closed-loop approach to optimize patient-specific stimulation parameters. In this paper, we develop a multiple model predictive control (MMPC) algorithm for automated regulation of heart rate (HR) and mean arterial pressure by optimally adjusting the amplitude and frequency of electrical pulses applied to three locations of the vagal nerve. The multiple local models are identified from our previously reported pulsatile rat cardiac model that emulates symptoms of hypertension in rest and exercise states. The computational expense of the proposed method is verified in simulation with rigorous hardware-in-the-loop (HIL) implementation.
{"title":"Multiple Model Predictive Control of the Cardiovascular System Using Vagal Nerve Stimulation","authors":"Yuyu Yao;Mayuresh V. Kothare","doi":"10.1109/TCST.2024.3473772","DOIUrl":"https://doi.org/10.1109/TCST.2024.3473772","url":null,"abstract":"Vagal nerve stimulation (VNS) is currently under investigation for the treatment of various cardiovascular diseases including heart failure, arrhythmia, and hypertension. In preclinical and clinical studies, VNS stimulation parameters are heuristically determined in the open loop. However, its therapeutic efficacy remains inconclusive, strongly suggesting the need for a closed-loop approach to optimize patient-specific stimulation parameters. In this paper, we develop a multiple model predictive control (MMPC) algorithm for automated regulation of heart rate (HR) and mean arterial pressure by optimally adjusting the amplitude and frequency of electrical pulses applied to three locations of the vagal nerve. The multiple local models are identified from our previously reported pulsatile rat cardiac model that emulates symptoms of hypertension in rest and exercise states. The computational expense of the proposed method is verified in simulation with rigorous hardware-in-the-loop (HIL) implementation.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"400-407"},"PeriodicalIF":4.9,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1109/TCST.2024.3470388
Ravi Prakash;Laxmidhar Behera;Sarangapani Jagannathan
Realistic manipulation tasks involve a prolonged sequence of motor skills in varying control environments consisting of uncertain robot dynamic models and end-effector payloads. To address these challenges, this article proposes an adaptive critic (AC)-based basis function neural network (BFNN) optimal controller. Using a single neural network (NN) with a basis function, the proposed optimal controller simultaneously learns task-related optimal cost function, robot internal dynamics, and optimal control law. This is achieved through the development of a novel BFNN tuning law using closed-loop system stability. Therefore, the proposed optimal controller provides real-time, implementable, cost-effective control solutions for practical robotic tasks. The stability and performance of the proposed control scheme are verified theoretically via the Lyapunov stability theory and experimentally using a 7-DoF Barrett WAM robot manipulator with uncertain dynamics. The proposed controller is then integrated with learning from demonstration (LfD) to handle the temporal and spatial robustness of a real-world task. The validations for various realistic robotic tasks, e.g., cleaning the table, serving water, and packing items in a box, highlight the efficacy of the proposed approach in addressing the challenges of real-world robotic manipulation tasks.
{"title":"Adaptive Critic Optimal Control of an Uncertain Robot Manipulator With Applications","authors":"Ravi Prakash;Laxmidhar Behera;Sarangapani Jagannathan","doi":"10.1109/TCST.2024.3470388","DOIUrl":"https://doi.org/10.1109/TCST.2024.3470388","url":null,"abstract":"Realistic manipulation tasks involve a prolonged sequence of motor skills in varying control environments consisting of uncertain robot dynamic models and end-effector payloads. To address these challenges, this article proposes an adaptive critic (AC)-based basis function neural network (BFNN) optimal controller. Using a single neural network (NN) with a basis function, the proposed optimal controller simultaneously learns task-related optimal cost function, robot internal dynamics, and optimal control law. This is achieved through the development of a novel BFNN tuning law using closed-loop system stability. Therefore, the proposed optimal controller provides real-time, implementable, cost-effective control solutions for practical robotic tasks. The stability and performance of the proposed control scheme are verified theoretically via the Lyapunov stability theory and experimentally using a 7-DoF Barrett WAM robot manipulator with uncertain dynamics. The proposed controller is then integrated with learning from demonstration (LfD) to handle the temporal and spatial robustness of a real-world task. The validations for various realistic robotic tasks, e.g., cleaning the table, serving water, and packing items in a box, highlight the efficacy of the proposed approach in addressing the challenges of real-world robotic manipulation tasks.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"316-326"},"PeriodicalIF":4.9,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1109/TCST.2024.3469032
Fen Liu;Shenghai Yuan;Kun Cao;Wei Meng;Lihua Xie
This article proposes a comprehensive strategy for complex multitarget-multidrone encirclement in an obstacle-rich and global positioning system (GPS)-denied environment, motivated by practical scenarios such as pursuing vehicles or humans in urban canyons. The drones have omnidirectional range sensors that can robustly detect ground targets and obtain noisy relative distances. After each drone task is assigned, a novel distance-based target state estimator (DTSE) is proposed by estimating the measurement output noise variance and utilizing the Kalman filter. By integrating anti-synchronization (AS) techniques and pseudo-force functions, an acceleration controller enables two tasking drones to cooperatively encircle a target from opposing positions while navigating obstacles. The algorithm’s effectiveness for the discrete-time double-integrator system is established theoretically, particularly regarding observability. Moreover, the versatility of the algorithm is showcased in aerial-to-ground scenarios, supported by compelling simulation results. Experimental validation demonstrates the effectiveness of the proposed approach.
{"title":"Distance-Based Multiple Noncooperative Ground Target Encirclement for Complex Environments","authors":"Fen Liu;Shenghai Yuan;Kun Cao;Wei Meng;Lihua Xie","doi":"10.1109/TCST.2024.3469032","DOIUrl":"https://doi.org/10.1109/TCST.2024.3469032","url":null,"abstract":"This article proposes a comprehensive strategy for complex multitarget-multidrone encirclement in an obstacle-rich and global positioning system (GPS)-denied environment, motivated by practical scenarios such as pursuing vehicles or humans in urban canyons. The drones have omnidirectional range sensors that can robustly detect ground targets and obtain noisy relative distances. After each drone task is assigned, a novel distance-based target state estimator (DTSE) is proposed by estimating the measurement output noise variance and utilizing the Kalman filter. By integrating anti-synchronization (AS) techniques and pseudo-force functions, an acceleration controller enables two tasking drones to cooperatively encircle a target from opposing positions while navigating obstacles. The algorithm’s effectiveness for the discrete-time double-integrator system is established theoretically, particularly regarding observability. Moreover, the versatility of the algorithm is showcased in aerial-to-ground scenarios, supported by compelling simulation results. Experimental validation demonstrates the effectiveness of the proposed approach.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"261-273"},"PeriodicalIF":4.9,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1109/TCST.2024.3467808
Luís F. Normandia Lourenço;Alessio Iovine;Gilney Damm;Alfeu J. Sguarezi Filho
The development of the modular multilevel converter (MMC) enabled the efficient creation of high-power high-voltage direct current (HVdc) transmission systems. As a result, MMC-HVdc transmission systems became the main alternative to integrate remote renewable energy sources being deployed in accelerating rates to fight climate change. As the number of online classical synchronous generators (SGs) decreases while the one of converter-based power sources increases, power systems are suffering from lower inertia levels and from fewer providers of ancillary services. Therefore, new control strategies, such as the grid-forming (GFM) converter operation, were developed to address the ongoing power system transformation. The main contribution of this article is to propose a nonlinear (NL) control strategy compatible with GFM operation for an MMC-HVdc transmission system controlled as a virtual synchronous machine (VSM). The control strategy is developed using NL control tools, such as feedback linearization, dynamic feedback linearization, and backstepping. In addition, this article provides a rigorous mathematical stability analysis applying Lyapunov theory. The proposed control strategy is then validated by simulations using the MATLAB/Simscape Electrical package in three situations: active power tracking, converter energy tracking, and a frequency support scenario. Results show the good performance of the proposed NL controller for all situations considered, presenting a fast response and a faster disturbance rejection compared with the classical proportional integral (PI) controller.
{"title":"Nonlinear Controller for MMC-HVdc Operating in Grid-Forming Mode","authors":"Luís F. Normandia Lourenço;Alessio Iovine;Gilney Damm;Alfeu J. Sguarezi Filho","doi":"10.1109/TCST.2024.3467808","DOIUrl":"https://doi.org/10.1109/TCST.2024.3467808","url":null,"abstract":"The development of the modular multilevel converter (MMC) enabled the efficient creation of high-power high-voltage direct current (HVdc) transmission systems. As a result, MMC-HVdc transmission systems became the main alternative to integrate remote renewable energy sources being deployed in accelerating rates to fight climate change. As the number of online classical synchronous generators (SGs) decreases while the one of converter-based power sources increases, power systems are suffering from lower inertia levels and from fewer providers of ancillary services. Therefore, new control strategies, such as the grid-forming (GFM) converter operation, were developed to address the ongoing power system transformation. The main contribution of this article is to propose a nonlinear (NL) control strategy compatible with GFM operation for an MMC-HVdc transmission system controlled as a virtual synchronous machine (VSM). The control strategy is developed using NL control tools, such as feedback linearization, dynamic feedback linearization, and backstepping. In addition, this article provides a rigorous mathematical stability analysis applying Lyapunov theory. The proposed control strategy is then validated by simulations using the MATLAB/Simscape Electrical package in three situations: active power tracking, converter energy tracking, and a frequency support scenario. Results show the good performance of the proposed NL controller for all situations considered, presenting a fast response and a faster disturbance rejection compared with the classical proportional integral (PI) controller.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"229-244"},"PeriodicalIF":4.9,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article proposes a collision avoidance method for ellipsoidal rigid bodies that utilizes a control barrier function (CBF) designed from a supporting hyperplane. We formulate the problem in the special Euclidean groups ${SE}(2)$ and ${SE}(3)$ , where the kinematics are described as rigid body motion (RBM). We consider the condition for separating two ellipsoidal rigid bodies by employing a signed distance from a supporting hyperplane of a rigid body to the other rigid body. Although a positive value of this signed distance implies that the two rigid bodies are collision-free, a naively designed supporting hyperplane yields a smaller value than the actual distance. To avoid such a conservative evaluation, the supporting hyperplane is rotated so that the signed distance from the supporting hyperplane to the other rigid body is maximized. We prove that the maximum value of this optimization problem is equal to the actual distance between two ellipsoidal rigid bodies, hence eliminating excessive conservativeness. We leverage this signed distance as a CBF to prevent collision while the supporting hyperplane is rotated via a gradient-based input. The designed CBF is integrated into a quadratic programming (QP) problem, where each rigid body calculates its collision-free input in a distributed manner, given communication among rigid bodies. We exemplify that our method can be extended to other kinematic models. The proposed method is demonstrated through simulation results.
{"title":"Collision Avoidance for Ellipsoidal Rigid Bodies With Control Barrier Functions Designed From Rotating Supporting Hyperplanes","authors":"Riku Funada;Koju Nishimoto;Tatsuya Ibuki;Mitsuji Sampei","doi":"10.1109/TCST.2024.3467809","DOIUrl":"https://doi.org/10.1109/TCST.2024.3467809","url":null,"abstract":"This article proposes a collision avoidance method for ellipsoidal rigid bodies that utilizes a control barrier function (CBF) designed from a supporting hyperplane. We formulate the problem in the special Euclidean groups \u0000<inline-formula> <tex-math>${SE}(2)$ </tex-math></inline-formula>\u0000 and \u0000<inline-formula> <tex-math>${SE}(3)$ </tex-math></inline-formula>\u0000, where the kinematics are described as rigid body motion (RBM). We consider the condition for separating two ellipsoidal rigid bodies by employing a signed distance from a supporting hyperplane of a rigid body to the other rigid body. Although a positive value of this signed distance implies that the two rigid bodies are collision-free, a naively designed supporting hyperplane yields a smaller value than the actual distance. To avoid such a conservative evaluation, the supporting hyperplane is rotated so that the signed distance from the supporting hyperplane to the other rigid body is maximized. We prove that the maximum value of this optimization problem is equal to the actual distance between two ellipsoidal rigid bodies, hence eliminating excessive conservativeness. We leverage this signed distance as a CBF to prevent collision while the supporting hyperplane is rotated via a gradient-based input. The designed CBF is integrated into a quadratic programming (QP) problem, where each rigid body calculates its collision-free input in a distributed manner, given communication among rigid bodies. We exemplify that our method can be extended to other kinematic models. The proposed method is demonstrated through simulation results.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"148-164"},"PeriodicalIF":4.9,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10709633","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-04DOI: 10.1109/TCST.2024.3469051
Mahmoud Farhat;Yassine Kali;Maarouf Saad;Mohammad Habibur Rahman;Roberto E. Lopez-Herrejon
In this article, we present a new fixed-time observer (FTO) with time delay estimation (TDE)-based model-free fixed-time sliding mode for the problem of robust walking of the NAO robot. The proposed technique ensures convergence in fixed time, regardless of initial conditions, thereby enhancing both convergence speed and robustness. This method allows for precise tracking of the joint angles’ positions without depending on the robot’s dynamic models while reducing the chattering via a modified exponential reaching law (MERL). To address the complexities of stabilizing the walking dynamics of the NAO robot, which include highly nonlinear dynamics and limited computational process, the proposed strategy utilizes the TDE technique for system model estimation. To mitigate estimation errors, a novel observer with guaranteed fixed-time stability is proposed. This last helps to enhance the tracking performance. Using the Lyapunov theory and experimental validation, within the proposed composite control method, the proposed nonsingular terminal sliding surface’s fixed-time stability along with the system state’s stability is verified. Significantly improved stability and accuracy in the robot’s joint movements are demonstrated through experimental results, validating the efficacy of the tracking trajectory for robotic systems such as the NAO humanoid robot.
{"title":"New Fixed-Time Observer-Based Model-Free Fixed-Time Sliding Mode of Joint Angle Commanded NAO Humanoid Robot","authors":"Mahmoud Farhat;Yassine Kali;Maarouf Saad;Mohammad Habibur Rahman;Roberto E. Lopez-Herrejon","doi":"10.1109/TCST.2024.3469051","DOIUrl":"https://doi.org/10.1109/TCST.2024.3469051","url":null,"abstract":"In this article, we present a new fixed-time observer (FTO) with time delay estimation (TDE)-based model-free fixed-time sliding mode for the problem of robust walking of the NAO robot. The proposed technique ensures convergence in fixed time, regardless of initial conditions, thereby enhancing both convergence speed and robustness. This method allows for precise tracking of the joint angles’ positions without depending on the robot’s dynamic models while reducing the chattering via a modified exponential reaching law (MERL). To address the complexities of stabilizing the walking dynamics of the NAO robot, which include highly nonlinear dynamics and limited computational process, the proposed strategy utilizes the TDE technique for system model estimation. To mitigate estimation errors, a novel observer with guaranteed fixed-time stability is proposed. This last helps to enhance the tracking performance. Using the Lyapunov theory and experimental validation, within the proposed composite control method, the proposed nonsingular terminal sliding surface’s fixed-time stability along with the system state’s stability is verified. Significantly improved stability and accuracy in the robot’s joint movements are demonstrated through experimental results, validating the efficacy of the tracking trajectory for robotic systems such as the NAO humanoid robot.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"304-315"},"PeriodicalIF":4.9,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-02DOI: 10.1109/TCST.2024.3460648
Sencheng Yu;Xingyong Song;Zongxuan Sun
Off-road vehicles, such as wheel loaders, consume a significant amount of fuel during the transportation of materials. The gear-shifting process is crucial in fuel savings for transportation, and therefore, optimization of gearshifts is important for vehicle control. For an autonomous off-road vehicle, there is potential for more fuel savings by proper coordination of gearshift optimization and optimization of other control inputs. This brief proposes a new method for integrating gear-shifting into transportation optimization for an autonomous wheel loader to minimize fuel consumption. Tests conducted on short loading cycles show that this method can save around 10%–20% of fuel on average compared with a conventional gearshift-scheduling method.
{"title":"Real-Time Gear-Shift Optimization for an Autonomous Wheel Loader","authors":"Sencheng Yu;Xingyong Song;Zongxuan Sun","doi":"10.1109/TCST.2024.3460648","DOIUrl":"https://doi.org/10.1109/TCST.2024.3460648","url":null,"abstract":"Off-road vehicles, such as wheel loaders, consume a significant amount of fuel during the transportation of materials. The gear-shifting process is crucial in fuel savings for transportation, and therefore, optimization of gearshifts is important for vehicle control. For an autonomous off-road vehicle, there is potential for more fuel savings by proper coordination of gearshift optimization and optimization of other control inputs. This brief proposes a new method for integrating gear-shifting into transportation optimization for an autonomous wheel loader to minimize fuel consumption. Tests conducted on short loading cycles show that this method can save around 10%–20% of fuel on average compared with a conventional gearshift-scheduling method.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"384-391"},"PeriodicalIF":4.9,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-02DOI: 10.1109/TCST.2024.3464118
Dominic Liao-McPherson;Efe C. Balta;Mohamadreza Afrasiabi;Alisa Rupenyan;Markus Bambach;John Lygeros
Additive manufacturing (AM) processes are flexible and efficient technologies for producing complex geometries. However, ensuring reliability and repeatability is challenging due to the complex physics and various sources of uncertainty in the process. In this work, we investigate closed-loop control of the melt pool dimensions in a 2-D laser powder bed fusion (LPBF) process. We propose a trajectory optimization-based layer-to-layer (L2L) controller based on a linear parameter-varying (LPV) model that adjusts the laser power input to the next layer to track a desired melt pool depth and validate our controller by placing it in closed-loop high-fidelity multilayer smoothed particle hydrodynamics simulator of the 2-D LPBF process. Detailed numerical case studies demonstrate successful regulation of the melt pool depth on brick and overhang geometries and provide first of its kind results on the effectiveness of L2L input optimization for the LPBF process as well as detailed insight into the physics of the controlled process. Computational complexity and process performance results illustrate the method’s effectiveness and provide an outlook for its implementation onto real systems.
{"title":"Layer-to-Layer Melt Pool Control in Laser Powder Bed Fusion","authors":"Dominic Liao-McPherson;Efe C. Balta;Mohamadreza Afrasiabi;Alisa Rupenyan;Markus Bambach;John Lygeros","doi":"10.1109/TCST.2024.3464118","DOIUrl":"https://doi.org/10.1109/TCST.2024.3464118","url":null,"abstract":"Additive manufacturing (AM) processes are flexible and efficient technologies for producing complex geometries. However, ensuring reliability and repeatability is challenging due to the complex physics and various sources of uncertainty in the process. In this work, we investigate closed-loop control of the melt pool dimensions in a 2-D laser powder bed fusion (LPBF) process. We propose a trajectory optimization-based layer-to-layer (L2L) controller based on a linear parameter-varying (LPV) model that adjusts the laser power input to the next layer to track a desired melt pool depth and validate our controller by placing it in closed-loop high-fidelity multilayer smoothed particle hydrodynamics simulator of the 2-D LPBF process. Detailed numerical case studies demonstrate successful regulation of the melt pool depth on brick and overhang geometries and provide first of its kind results on the effectiveness of L2L input optimization for the LPBF process as well as detailed insight into the physics of the controlled process. Computational complexity and process performance results illustrate the method’s effectiveness and provide an outlook for its implementation onto real systems.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"207-218"},"PeriodicalIF":4.9,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study proposes a novel predictive input optimization and disturbance prediction strategy for semi-active vibration control using a piezoelectric transducer, leveraging the statistically oriented prediction and optimization scheme and Gaussian process (GP) enhanced disturbance prediction. Here, semi-active switching, which manipulates the piezoelectric charge, is executed to suppress vibration. State-dependent discontinuity of the semi-active input trajectory owing to the switching makes it challenging to formulate a prediction-based optimization strategy in conventional methods. Incorporating the dynamical model of disturbance is also crucial to compensate for those undesired effects effectively. The proposed GP-enhanced disturbance predictor, which combines the empirical model and GP regression, provides the disturbance trajectory over a finite time horizon. The empirical model approximates the periodic disturbance with known frequencies, while the GP regression model handles other unknown components, enabling the predictor to function under different conditions. Furthermore, the predicted disturbance trajectory is applied for control optimization, allowing the controller to determine the optimal control input trajectory that compensates for future disturbances. The proposed strategy employs the tree-based scheme to formulate a prediction and optimization algorithm that determines the optimal semi-active input trajectory. Further, it includes a statistically oriented switching criterion that reduces the computational costs by selecting the trajectory to be predicted. This criterion utilizes kernel density estimation to learn the probability density function of suppression performance, allowing the controller to adaptively select trajectories to predict online while not excluding promising ones. The effectiveness of the proposed statistically oriented predictive switching vibration control with tree-based formulation and optimization (S-PSTFO) strategy was validated through experiments, demonstrating superior suppression performance over the conventional method.
{"title":"Statistically Oriented Optimal Control and Disturbance Prediction for Piezoelectric Semi-Active Vibration Suppression","authors":"Mizuki Abe;Koyo Mishima;Yushin Hara;Keisuke Otsuka;Kanjuro Makihara","doi":"10.1109/TCST.2024.3463333","DOIUrl":"https://doi.org/10.1109/TCST.2024.3463333","url":null,"abstract":"This study proposes a novel predictive input optimization and disturbance prediction strategy for semi-active vibration control using a piezoelectric transducer, leveraging the statistically oriented prediction and optimization scheme and Gaussian process (GP) enhanced disturbance prediction. Here, semi-active switching, which manipulates the piezoelectric charge, is executed to suppress vibration. State-dependent discontinuity of the semi-active input trajectory owing to the switching makes it challenging to formulate a prediction-based optimization strategy in conventional methods. Incorporating the dynamical model of disturbance is also crucial to compensate for those undesired effects effectively. The proposed GP-enhanced disturbance predictor, which combines the empirical model and GP regression, provides the disturbance trajectory over a finite time horizon. The empirical model approximates the periodic disturbance with known frequencies, while the GP regression model handles other unknown components, enabling the predictor to function under different conditions. Furthermore, the predicted disturbance trajectory is applied for control optimization, allowing the controller to determine the optimal control input trajectory that compensates for future disturbances. The proposed strategy employs the tree-based scheme to formulate a prediction and optimization algorithm that determines the optimal semi-active input trajectory. Further, it includes a statistically oriented switching criterion that reduces the computational costs by selecting the trajectory to be predicted. This criterion utilizes kernel density estimation to learn the probability density function of suppression performance, allowing the controller to adaptively select trajectories to predict online while not excluding promising ones. The effectiveness of the proposed statistically oriented predictive switching vibration control with tree-based formulation and optimization (S-PSTFO) strategy was validated through experiments, demonstrating superior suppression performance over the conventional method.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"165-180"},"PeriodicalIF":4.9,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703149","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1109/TCST.2024.3464111
J. Gabirondo-López;I. Arredondo;J. M. Igartua
This article introduces a cascade control system designed to precisely manage complex heating processes characterized by two actuator saturations, the absence of any cooling system, variable properties of the sample being heated, and a wide temperature span. The proposed control system combines an industrial PID for furnace heating element control with a model-free controller to control the temperature of the heated sample. We clearly describe the procedure to tune the controller and to accurately model the whole heating process. We have performed simulations to compare the performance of the control system we propose to the performance of conventional cascade controllers; our control system is superior in terms of accuracy and adaptability. We have successfully implemented the control system in an experimental instrument: an infrared emissometer. We have proved that the implementation is effective in controlling both tuned plants and unknown plants, without the need to modify the previous control configurations. The tests we have done also demonstrate that the achieved final model represents the whole experimental system with a high degree of accuracy, as the results from the simulations match with the experimental results.
{"title":"Temperature Control of Nonlinear Uncertain Systems via Model-Free Cascaded Controller: Application to an Infrared Emissometer","authors":"J. Gabirondo-López;I. Arredondo;J. M. Igartua","doi":"10.1109/TCST.2024.3464111","DOIUrl":"https://doi.org/10.1109/TCST.2024.3464111","url":null,"abstract":"This article introduces a cascade control system designed to precisely manage complex heating processes characterized by two actuator saturations, the absence of any cooling system, variable properties of the sample being heated, and a wide temperature span. The proposed control system combines an industrial PID for furnace heating element control with a model-free controller to control the temperature of the heated sample. We clearly describe the procedure to tune the controller and to accurately model the whole heating process. We have performed simulations to compare the performance of the control system we propose to the performance of conventional cascade controllers; our control system is superior in terms of accuracy and adaptability. We have successfully implemented the control system in an experimental instrument: an infrared emissometer. We have proved that the implementation is effective in controlling both tuned plants and unknown plants, without the need to modify the previous control configurations. The tests we have done also demonstrate that the achieved final model represents the whole experimental system with a high degree of accuracy, as the results from the simulations match with the experimental results.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"219-228"},"PeriodicalIF":4.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10701453","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：