A quantum controltheory of pure state in non-ideal quantum systems is proposed in this paper. A non-ideal closed quantum systems means that the controlled quantum system is in two degenerate cases: one is at least tw...
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ISBN:
(纸本)9798331518509;9798331518493
A quantum controltheory of pure state in non-ideal quantum systems is proposed in this paper. A non-ideal closed quantum systems means that the controlled quantum system is in two degenerate cases: one is at least two transition frequencies between different energy levels are the same, or/and another is at least two eigenstates of the internal Hamiltonian are not directly coupled. the implicit Lyapunov control method based on the average value of an imaginary mechanical quantity is used to design the control laws. the design procedure of the imaginary mechanical quantity is derived. the relationships among the implicit Lyapunov control methods based on the state distance, the state error and the average value of an imaginary mechanical quantity are analyzed. Finally, some numerical simulation experiments are studied.
Microgrid is a typical cyber-physical system which integrates the power flow and the communication flow. Privacy preservation of sensitive information delivering over the communication network has received significant...
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ISBN:
(纸本)9798331518509;9798331518493
Microgrid is a typical cyber-physical system which integrates the power flow and the communication flow. Privacy preservation of sensitive information delivering over the communication network has received significant attention. In this paper, a privacy-preserving distributed secondary controller is proposed for DC microgrids. the privacy information is subjected to an output mask function to ensure its anonymity, thereby providing real-time security for private power information. Furthermore, by employing event-triggered mechanism to determine the updating of control signals, current sharing and voltage regulation are achieved simultaneously. In addition, the decreasing event-triggered threshold improves the systems response speed and accuracy. Finally, the simulation and experimental cases demonstrate the effectiveness of the proposed controller.
Autonomous robot navigation on Indian roads presents unique challenges, particularly within campuses limited by weak GPS signals due to surrounding buildings and trees. this paper proposes a cost-effective solution fo...
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ISBN:
(纸本)9798331518509;9798331518493
Autonomous robot navigation on Indian roads presents unique challenges, particularly within campuses limited by weak GPS signals due to surrounding buildings and trees. this paper proposes a cost-effective solution for navigating such environments using a DC-powered robot vehicle within the campus of CDAC Mumbai. the approach leverages computer vision for lane detection and road demarcation, eliminating reliance on GPS. the lane detection approach utilises binary mask generation, edge detection, and Hough transform, while road demarcation employs colour filtering, contouring, and moments from the OpenCV library. Experimental results demonstrate a 72% navigation accuracy with minimal false detections. this algorithm is applicable for real-time scenarios, and enables autonomous vehicle navigation using minimal and cost-effective sensors, making it suitable for environments with obstructed GPS signals.
van de Vusse reaction system in a continuous stirred tank reactor is a benchmark example to study the control of nonlinear non-minimum phase systems. Although different control strategies exist to deal with such syste...
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ISBN:
(纸本)9798331518509;9798331518493
van de Vusse reaction system in a continuous stirred tank reactor is a benchmark example to study the control of nonlinear non-minimum phase systems. Although different control strategies exist to deal with such systems, the controller's performance strongly depends on the accuracy of the process model. In this work, we develop a model-free, deep reinforcement learning-based control strategy to perform setpoint tracking control. In particular, we develop a deep Q-learning based controller and demonstrate the tracking performance for different reference trajectories of the desired product concentration. Furthermore, we illustrate the disturbance rejection ability of the proposed deep RL controller.
this study utilized the Gaussian Processes (GPs) regression framework to establish stochastic error bounds between nonlinear systems' actual and predicted state evolution. these systems are embedded in the linear ...
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ISBN:
(纸本)9798331518509;9798331518493
this study utilized the Gaussian Processes (GPs) regression framework to establish stochastic error bounds between nonlinear systems' actual and predicted state evolution. these systems are embedded in the linear parameter-varying (LPV) formulation and controlled using model predictive control (MPC). Our primary focus is quantifying the uncertainty of the LPVMPC framework's forward error resulting from scheduling signal estimation mismatch. We compared our stochastic approach with a recent deterministic approach and observed improvements in conservatism and robustness. To validate our analysis and method, we solved the regulator problem of an unbalanced disk.
In this work, we provide deterministic error bounds for the actual state evolution of nonlinear systems that can be embedded in linear parameter-varying (LPV) formulation and steered by model predictive control (MPC)....
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ISBN:
(纸本)9798331518509;9798331518493
In this work, we provide deterministic error bounds for the actual state evolution of nonlinear systems that can be embedded in linear parameter-varying (LPV) formulation and steered by model predictive control (MPC). the main novelty concerns the explicit derivation of these deterministic bounds as polytopic tubes using linear differential inclusions (LDIs). We provide exact error formulations compared to other approaches based on linearization schemes that inevitably introduce additional errors and deteriorate performance. the analysis and method are certified by solving the regulation problem of an unbalanced disk.
this paper presents the control of multiple unmanned aerial manipulators that perform various manipulator tasks keeping a given formation. the Software-in-loop simulation is utilised to test and validate three coopera...
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ISBN:
(纸本)9798331518509;9798331518493
this paper presents the control of multiple unmanned aerial manipulators that perform various manipulator tasks keeping a given formation. the Software-in-loop simulation is utilised to test and validate three cooperative algorithms, i.e., line formation tracking a piecewise continuous trajectory, circular trajectory in a cyclic pursuit, and finally a pick and place operation during formation. We employed leader-follower strategies and performed experiments using the Robot Operating System, Gazebo, and PX4. During the formation process, the manipulator is tested for various poses yet it maintained stability and followed the designated path. Performance of the proposed controller and algorithms are evaluated through real-time simulation analysis.
Melanoma is a very dangerous type of skin cancer and its detection in the early stages is necessary for proper treatment. the article proposes an intelligent system, based on the fusion of the decisions of several neu...
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ISBN:
(纸本)9798331518509;9798331518493
Melanoma is a very dangerous type of skin cancer and its detection in the early stages is necessary for proper treatment. the article proposes an intelligent system, based on the fusion of the decisions of several neural networks to increase the performance in melanoma detection from dermatoscopic images. the system implementation method is based on the optimal choice of the number and type of neural networks involved by testing the possible combinations. According to the selection procedure, a system was implemented with four neural networks DenseNet 201, VGG 19, MobileNet, and EfficientNet. the results obtained on two different databases (ISIC 2019 - for learning, validation, and testing - and PH2 for testing) were better than those obtained on individual networks or in other works from literature.
the paper describes a novel, publicly available toolbox for piecewise-affine (PWA) convex-lifting. the main goal is to provide a tool for efficient partitions of sets in finite-dimensional spaces with applications in ...
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ISBN:
(纸本)9798331518509;9798331518493
the paper describes a novel, publicly available toolbox for piecewise-affine (PWA) convex-lifting. the main goal is to provide a tool for efficient partitions of sets in finite-dimensional spaces with applications in navigation and control design. this objective is achieved by employing a lift-and-project philosophy that relies on performant linear programming optimization and polyhedra manipulation. Once a PWA lifting is constructed, the related polyhedral partition provides an interconnection graph that can be used for path planning, which is considered here as the main application. the paper provides the main theoretical elements of the technique's foundation and describes the toolbox's structure along withthe numerical artifacts used for its implementation. Illustrative examples for the practical problems are provided, supporting the claims of efficiency and versatility.
this work presents a body velocity control strategy for quadruped robots. Such control typically requires accurate kinematic and dynamic model knowledge, which is very challenging because of the multidimensional input...
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ISBN:
(纸本)9798331518509;9798331518493
this work presents a body velocity control strategy for quadruped robots. Such control typically requires accurate kinematic and dynamic model knowledge, which is very challenging because of the multidimensional input-output system and the ground contact. Based on the inverse kinematics, we propose a Proportional-Derivative controlled robot that uses Iterative Learning control to learn discrete body velocities, which are then generalized using the Gaussian Process Regression model for each joint separately. this controller design enables onboard control and learning in real-time without any simulation. this study illustrates the effectiveness of the proposed methodology over a range of velocities while emphasizing the minimal computational effort associated with its application in a practical context.
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