This paper introduces an adaptive robust control approach tailored for underactuated mechanical systems encountering matched and mismatched uncertainty, employing a constraint-following methodology. The control strate...
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ISBN:
(纸本)9798331518509;9798331518493
This paper introduces an adaptive robust control approach tailored for underactuated mechanical systems encountering matched and mismatched uncertainty, employing a constraint-following methodology. The control strategy unfolds in two phases: initially, a nominal control scheme is devised neglecting uncertainty and deviations in initial conditions from constraints. Subsequently, uncertainty is categorized into matched and mismatched components, ensuring that mismatched uncertainties remain unobservable. Leveraging the structural characteristics of the uncertainty bound, a novel segmented adaptive law is proposed and seamlessly integrated into the adaptive robust control framework. By employing the Lyapunov minimax approach, the method ensures uniform boundedness and uniform ultimate boundedness simultaneously, thereby ensuring approximate adherence to constraints for underactuated mechanical systems facing both matched and mismatched uncertainties alongside initial condition deviations.
It is challenging to perform system identification on soft robots due to their underactuated, high-dimensional dynamics. In this work, we present a data-driven modeling framework, based on geometric mechanics (also kn...
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ISBN:
(纸本)9798350384581;9798350384574
It is challenging to perform system identification on soft robots due to their underactuated, high-dimensional dynamics. In this work, we present a data-driven modeling framework, based on geometric mechanics (also known as gauge theory) that can be applied to systems with low-bandwidth control of the system's internal configuration. This method constructs a series of connected models comprising actuator and locomotor dynamics based on data points from stochastically perturbed, repeated behaviors. By deriving these connected models from general formulations of dissipative Lagrangian systems with symmetry, we offer a method that can be applied broadly to robots with first-order, low-pass actuator dynamics, including swelling-driven actuators used in hydrogel crawlers. These models accurately capture the dynamics of the system shape and body movements of a simplified swimming robot model. We further apply our approach to a stimulus-responsive hydrogel simulator that captures the complexity of chemomechanical interactions that drive shape changes in biomedically relevant micromachines. Finally, we propose an approach of numerically optimizing control signals by iteratively refining models, which is applied to optimize the input waveform for the hydrogel crawler. This transfer to realistic environments provides promise for applications in locomotor design and biomedical engineering.
The combination of knowledge and skill sets from robotics and Artificial Intelligence has proven as a powerful catalyst for students' learning experiences, when applying available resources and knowledge acquired ...
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ISBN:
(纸本)9783031835223;9783031835230
The combination of knowledge and skill sets from robotics and Artificial Intelligence has proven as a powerful catalyst for students' learning experiences, when applying available resources and knowledge acquired through vocational training. Within the Department of IT at an Austrian vocational high school, our students actively engage in projects that combine robotics and AI. Our diploma theses extend beyond mere classroom theory, allowing interested students to apply their knowledge in authentic, real-world scenarios in the form of thesis projects which span different engineering and IT disciplines. Our goal is to emphasize hands-on experiences and encourage our students to design, construct and program robots, even with the addition of AI technology, such as image recognition and classification trained for specific tasks. Through this practical immersion, our students gain a deeper understanding of robotics and AI, disciplines that are at the forefront of today's technological innovation. We worked with two groups of students on interdisciplinary projects bridging the gap between robotics and AI and based on our students' feedback found an increase in motivation to learn not only about the fields themselves, but also about related fields, from mathematical theory to better understand the intricate workings of AI algorithms to electronics and working with microcontrollers. Personal interviews with involved students have also pointed toward an increased motivation through the intense cooperation between the team members as well as the teachers responsible for supporting the project teams through their thesis projects. Projects connecting robotics and AI empower students to become adaptable, creative problem-solvers which is a crucial foundation for success in the twenty-first century. By fostering collaboration and critical thinking, while enhancing students' technical skills and equipping them with the adaptability and creativity they require, this educational app
This paper investigates the issue of distributed H-infinity filtering for multi-sensor systems using quantization, in the presence of DoS (denial-of-service) attacks. Firstly, the logarithmic quantizers are introduced...
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ISBN:
(纸本)9798350373172;9798350373189
This paper investigates the issue of distributed H-infinity filtering for multi-sensor systems using quantization, in the presence of DoS (denial-of-service) attacks. Firstly, the logarithmic quantizers are introduced in the data transmission channel, where this quantized data is then used for the filter's input. Secondly, a switching analysis model for the filtering error system under cyber-attacks was established, and sufficient conditions are obtained for the allowed attack frequency and duration of DoS attacks. Then, it is deduced that the filtering error system possesses a finite-time bounded (FTB) characteristic and exhibits an H-infinity performance index. Next, the gains of the designed filter are solved using LMI. Finally, a simulation example is given to verify the effectiveness of the proposed approach.
This paper concentrate on the finite-time optimal control for the interconnected power systems with switching communication topology. The finite-time ADP-based optimal controller (FTADPOC) is proposed for the finite-t...
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ISBN:
(纸本)9798350373172;9798350373189
This paper concentrate on the finite-time optimal control for the interconnected power systems with switching communication topology. The finite-time ADP-based optimal controller (FTADPOC) is proposed for the finite-time stability of the interconnected power systems (IPSs). Firstly, the consensus error model with switching communication topology of the IPSs is given. Then, the finite-time optimal controller solved by the HJB equation with the value function in the finite-time stability space is constructed. Furthermore, based on the finite-time optimization theory, the finite-time critic network for the approximation of the value function is implemented to solve the optimal controller, and the corresponding finite-time convergence of the proposed tuning law is illustrated. Finally, the result analysis on the interconnected power systems illustrates the effectiveness of the proposed FTADPOC.
Robotic systems are highly complex, and debugging failures in them can prove challenging. We propose a technique for using multivariate decision trees to create human interpretable descriptions of the input conditions...
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ISBN:
(纸本)9798350395716;9798350395709
Robotic systems are highly complex, and debugging failures in them can prove challenging. We propose a technique for using multivariate decision trees to create human interpretable descriptions of the input conditions that cause these failures in roboticssystems. This approach uses active learning to efficiently create tests, and uses a multivariate decision tree that captures common boundary conditions in the software fault space. We provide an evaluation of this technique on a small set of faults from several roboticssystems, and compare it against a previous technique in this space, Hierarchical Product Set Learning. Our proposed technique requires fewer tests, provides more accurate estimates of the fault conditions, and is more interpretable than the prior approach.
This paper focuses on the design of linear integral controllers for uncertain nonlinear systems subjected to various types of time-varying perturbations. We propose a method called the feedback domination method to ad...
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Most Simultaneous localisation and mapping (SLAM) systems have traditionally assumed a static world, which does not align with real-world scenarios. To enable robots to safely navigate and plan in dynamic environments...
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ISBN:
(纸本)9798350384581;9798350384574
Most Simultaneous localisation and mapping (SLAM) systems have traditionally assumed a static world, which does not align with real-world scenarios. To enable robots to safely navigate and plan in dynamic environments, it is essential to employ representations capable of handling moving objects. Dynamic SLAM is an emerging field in SLAM research as it improves the overall system accuracy while providing additional estimation of object motions. State-of-the-art literature informs two main formulations for Dynamic SLAM, representing dynamic object points in either the world or object coordinate frame. While expressing object points in their local reference frame may seem intuitive, it does not necessarily lead to the most accurate and robust solutions. This paper conducts and presents a thorough analysis of various Dynamic SLAM formulations, identifying the best approach to address the problem. To this end, we introduce a front-end agnostic framework using GTSAM [1] that can be used to evaluate various Dynamic SLAM formulations.(1)
This paper investigates the secure consensus problem of multi-agent systems (MASs) under Denial-of-Service (DoS) attacks, in which the attacks is asynchronously launched in communication and control channels. For thes...
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We report a novel model-based nullspace adaptive trajectory-tracking control (NS-ATTC) algorithm for fully-actuated 6-degree-of-freedom (DOF) underwater vehicles which estimates unknown plant and actuator model parame...
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ISBN:
(纸本)9798350384581;9798350384574
We report a novel model-based nullspace adaptive trajectory-tracking control (NS-ATTC) algorithm for fully-actuated 6-degree-of-freedom (DOF) underwater vehicles which estimates unknown plant and actuator model parameters simultaneously. We provide a stability and convergence analysis with proof of asymptotically stable tracking error convergence, as well as a preliminary simulation study demonstrating 6-DOF trajectory tracking. The NS-ATTC algorithm does not require acceleration instrumentation and provides a stable online parameter estimate, enabling robust model-based autonomy.
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