When developing underwater stations and resident vehicles for subsea mining complexes service systems, it is necessary to solve a number of tasks. Some of them are traditional (for example, the tasks of bringing an un...
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This paper proposes a high-speed path-tracking algorithm based on the deep deterministic policy gradient (DDPG) strategy with curvature adaptive ability applied to automatic driving. The tracking controller contains t...
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ISBN:
(纸本)9798350365818;9798350365801
This paper proposes a high-speed path-tracking algorithm based on the deep deterministic policy gradient (DDPG) strategy with curvature adaptive ability applied to automatic driving. The tracking controller contains two mechanisms: the pure pursuit (PP) module and the model predictive control (MPC) module. The PP part works well in the small curvature road conditions, while the MPC can solve more complexproblems. Thus, DDPG triggers the decision of which mechanism to use: PP works on regular roads or scenes with relatively small curvature, while it is switched to MPC control for complex scenarios by building the testing environments in CarMaker to validate the control performance of our method.
Many problems related to optimization, optimal control, numerical calculations, etc. have been investigated and solved for problems with free boundaries. The proposed work is devoted to the study of the problem with f...
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The article devoted to the "information paradox," which originated in economic theory and formulated back in 1980s by Nobel Prize laureate Robert Solow. Author tries to explain this paradox from a broader pe...
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ISBN:
(纸本)9789819720521;9789819720538
The article devoted to the "information paradox," which originated in economic theory and formulated back in 1980s by Nobel Prize laureate Robert Solow. Author tries to explain this paradox from a broader perspective of modern systems sciences, cybernetics, and action theory. The aim is to develop a mathematical model of information application, leading to accurate predictions of its impact, based on formal modeling. I propose a graph-theoretic means to represent possible sequences of complex states and transitions which appear due to information application. This model is further used for creation of algebraic and programming code models, enabling the calculation of quantitative success measures for information application during system's functioning and the assessment of entropy change caused by information utilization. The article outlines various research directions related to the creation of mathematical models for information application. New approach presented to resolve the Solow paradox by mathematical modeling of information application results.
Magnetic continuum robots are subject to external magnetic fields and deformed remotely, simplifying the robot's transmission mechanism and providing it with significant potential for miniaturization and operation...
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ISBN:
(纸本)9798350377712;9798350377705
Magnetic continuum robots are subject to external magnetic fields and deformed remotely, simplifying the robot's transmission mechanism and providing it with significant potential for miniaturization and operational flexibility. However, modeling magnetic field distribution generated by permanent magnets is complex and requires time-consuming pre-calibrations. Moreover, it is highly susceptible to environments with ferromagnetic materials, posing significant challenges for the control of magnetic continuum robots. In response, we propose an approach that does not overly focus on the magnetic field distribution but instead directly learns the inverse kinematics of magnetic continuum robots end-to-end. Binding the robot's configuration to the pose of external magnets, precise control of continuum robots is facilitated. Additionally, we leverage teleoperation techniques to broaden the applicability of this method. By mounting magnets on a robotic arm and directly utilizing the target pose of the external magnet predicted by a multi-layer perceptron (MLP), we achieve the operation and navigation of magnetic continuum robots in complex environments. Experiments demonstrate that the mean control accuracy along the robot using our learning-based inverse kinematics is about half of the robot's diameter.
The stochastic optimal control problem of an ordinary non-linear discrete stochastic system is considered. The quality of control is estimated by the mathematical expectation of the Boltz type functional to be minimiz...
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Soft pneumatic actuators offer better safety and flexibility compared to rigid actuators. However, they suffer from modeling difficulties and nonlinear delays, which prevent precise control. Research on the dynamic mo...
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ISBN:
(纸本)9798350350319;9798350350302
Soft pneumatic actuators offer better safety and flexibility compared to rigid actuators. However, they suffer from modeling difficulties and nonlinear delays, which prevent precise control. Research on the dynamic modeling and control of soft pneumatic actuators is a difficult subject. Neural networks are powerful tools for modelingcomplex dynamic systems. This essay suggests a PID control algorithm based on neural network feedforward compensation for precise position control of soft pneumatic actuators. By introducing a neural network to establish a feedforward dynamic compensation model, the algorithm predicts the linear displacement error of the soft pneumatic actuator in advance and compensates for it. This approach combines with a PID position controller to form a composite controller. The dynamic model of actuator is utilized to convert displacement into the amount of air required by the controller for precise control. The drive position experiments demonstrate that the control method is able to reach the drive expectations quickly and stably, thus demonstrating that the control method is able to effectively control soft pneumatic drives.
The paper is devoted to the development of a modelingcomplex for managing the development of fast-growing companies based on technologies for integrating, processing and visualizing big data about the country's e...
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Purpose - Statistical process monitoring has been a relevant practice incorporated into quality management systems. In a controlled process, the variabilities of statistical parameter estimates are expected to fluctua...
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Landing on a vertically oscillating platform poses a significant challenge for multi-rotor unmanned aerial vehicle (UAVs) due to the time-varying ground effect (GE). In this work, we formulated a data-driven GE dynami...
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ISBN:
(纸本)9798350377712;9798350377705
Landing on a vertically oscillating platform poses a significant challenge for multi-rotor unmanned aerial vehicle (UAVs) due to the time-varying ground effect (GE). In this work, we formulated a data-driven GE dynamic model that accurately describes the complex interactions between UAVs and both stationary and oscillating platforms. Integrating this model with a feedforward controller effectively compensates for GE, resulting in improved landing performance. The proposed GE model elucidates the relationship between GE and factors such as UAVs' velocity, throttle magnitude, and the motion of the landing platform. It highlights that the GE experienced during the landing process of UAVs is not only contingent on the current state but also related to past states. The resulting GE model is parsimonious and suitable for onboard computers with limited computational power, and its accuracy has been confirmed through a series of flight experiments. To demonstrate the effectiveness of the developed UAVs landing scheme, we compared our approach with robust control and internal model control methods. Experimental results indicate that the proposed landing strategy achieves faster and smoother landings, with at least a 22% improvement in smoothness and a 25% reduction in landing time.
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