In the context of industry 4.0 and the fast development taking place nowadays all over the world towards industry 5.0, it's obvious that Robots are playing a very important role in this context alongside human in ...
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In the context of industry 4.0 and the fast development taking place nowadays all over the world towards industry 5.0, it's obvious that Robots are playing a very important role in this context alongside human in incorporating sustainability and resilience aims. so that, the robotic non-contact manipulation in the field of industry, medicine and chemical processes is considered as a main core nowadays due to its ability to achieve the desired targets with high accuracy, less time and less faults to do such a duty, and this depends on how to control the robotic operations effectively to fulfill the proper demands. This research article proposed the model reference adaptive control approach to be applied for the first time on one of the most well-known non-contact methods which is acoustic levitation based on standing waves. The control approach used in this study succeeded in accomplishing the required performance and keeping the levitated particle at the desired point within the sonic field.
In this paper, a control architecture merging a reference Governor and a model reference adaptive control law is tested on a high-fidelity Simulink model of a Parrot Bebop 2 Drone. This system is considered to be subj...
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ISBN:
(数字)9781624107115
ISBN:
(纸本)9781624107115
In this paper, a control architecture merging a reference Governor and a model reference adaptive control law is tested on a high-fidelity Simulink model of a Parrot Bebop 2 Drone. This system is considered to be subject to velocity constraints, and the flight simulations are performed in the presence of simulated matched uncertainties to recreate the typical uncertain environment in which a drone operates. The proposed control framework allows for precise tracking and constraints enforcement despite the uncertainties and the perturbations acting on the system. The novelty of the approach consists of exploiting the adaptive law performance to build a robust reference Governor with limited conservatism. As a result, larger uncertainties can be handled, and the computational complexity of the governor's optimization problem is limited compared to the standard robust reference Governor strategy.
This paper develops a new model reference adaptive control for multi-variable systems with input disturbance. The controller structure is established by using reduced-order state observer and the direct estimate of no...
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ISBN:
(纸本)9798350373707;9798350373691
This paper develops a new model reference adaptive control for multi-variable systems with input disturbance. The controller structure is established by using reduced-order state observer and the direct estimate of nominal controller parameters. The output matching condition, new tracking error, estimate error as well as adaptive properties are developed depending on the available signals, rather than the state or output signals in the existing schemes. The new output matching condition is crucial to the analysis of model reference adaptive control output tracking. With this presented control design, the desired system properties are achieved including system stability and output tracking, and the simulation results indicate the disturbance rejection ability of the developed scheme.
Output regulation theory is a highly effective method for achieving accurate time-varying command following, but redesigning its control architecture for different time-varying command profiles can be necessary. Yet, ...
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In this contribution we extend the classical update law of the certainty equivalence based (indirect) model reference adaptive control (MRAC) with an additional feedthrough error term. We use a linear state-space repr...
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ISBN:
(纸本)9798331540920;9783907144107
In this contribution we extend the classical update law of the certainty equivalence based (indirect) model reference adaptive control (MRAC) with an additional feedthrough error term. We use a linear state-space representation of the parameter estimation error in order to construct a Lyapunov function. Without unstructured uncertainties, we can show asymptotic stability of the closed loop. Even for relatively high adaptation gains the algorithm can reduce the oscillations of the state variables. In case of unstructured input uncertainties, the additional term reduces the model following error drastically without increasing the control signal for low frequency unstructured uncertainties. For the simplified pure linear case we analyze the effect of the additional proportional error feedthrough in the adaptation law showing its similarity to a disturbance observer. As a simulation example the wing-rock dynamics are reconsidered.
This abstract introduces a cuttingedge approach to power management in space systems through the development of a model reference adaptive control (MRAC) buck converter. This converter is designed to dynamically optim...
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In this paper, we explore the capabilities of model reference adaptive controllers for better response to uncertain over-actuated nonlinear dynamical systems that use nonlinear refer ence models. It is common practice...
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The paper discusses the concentration control in Continuous Stirred Tank Reactors (CSTR) using another CSTR as a referencemodel. The PI controller regulates the referencemodel, which adjusts the modelreference adap...
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The study considers model reference adaptive control for a single-input, single-output discrete-time system using an idea of the virtual reference feedback tuning (VRFT). The standard VRFT resolves a modelreference c...
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Due to their large volume structure, when a heavy vehicle encounters sudden road conditions, emergency turns, or lane changes, it is very easy for vehicle rollover accidents to occur;however, well-designed suspension ...
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Due to their large volume structure, when a heavy vehicle encounters sudden road conditions, emergency turns, or lane changes, it is very easy for vehicle rollover accidents to occur;however, well-designed suspension systems can greatly reduce vehicle rollover occurrence. In this article, a novel semi-active suspension adaptivecontrol based on AdaBoost algorithm is proposed to effectively improve the vehicle rollover stability under dangerous working conditions. This research first established a vehicle rollover warning model based on the AdaBoost algorithm. Meanwhile, the approximate skyhook damping suspension model is established as the referencemodel of the semi-active suspension. Furthermore, the model reference adaptive control (MRAC) system is established based on Lyapunov stability theory, and the adaptivecontroller is designed. Finally, on the same road condition, the rollover warning control simulations are carried out under the following conditions: the 180-degree step, the fishhook, and the double-lane-change condition. Simulation results show that the proposed referenceadaptivecontrol based on the AdaBoost algorithm for rollover control can effectively predict vehicle rollover in early warning and improve the anti-rollover capability of vehicles.
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