Application of the Robust control Toolbox for Time Delay Systems with Parametric and Periodic Uncertainties Using SSV (Structured Singular Value) for the Matlab system to uncertain time delay system with astatism is p...
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ISBN:
(纸本)9789897583803
Application of the Robust control Toolbox for Time Delay Systems with Parametric and Periodic Uncertainties Using SSV (Structured Singular Value) for the Matlab system to uncertain time delay system with astatism is performed. The D-K iteration and the algebraic approach implemented in the toolbox are applied to 2nd order system with astatism and uncertain time delay and two other parameters in the numerator and denominator of the plant transfer function. Multiplicative uncertainty is used for treating uncertain time delay, the parametric uncertainty is modelled using general interconnection for the systems with parametric uncertainty in numerator and denominator.
The problem of discrete-time multi-agent systems governed by general MIMO dynamics is addressed. By employing a PID-like distributed protocol, we aim to solve two relevant consensus problems, namely the leaderless con...
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ISBN:
(纸本)9789897583049
The problem of discrete-time multi-agent systems governed by general MIMO dynamics is addressed. By employing a PID-like distributed protocol, we aim to solve two relevant consensus problems, namely the leaderless consensus under disturbances and leader-follower under time-varying reference state ones. Sufficient conditions for stability as well as two LMI approaches to tune the controller gains are provided. The latter are either based on a H-infinity formulation of the problem or on fast response to a reference exogenous signal. Numerical simulations give some insight of which tuning should be considered according to the problem addressed.
This paper proposes a new approach to control system design through solving a Constraint Satisfaction Problem (CSP) using artificial intelligence, first using a genetic algorithm then using a Convolutional Neural Netw...
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ISBN:
(纸本)9789897585227
This paper proposes a new approach to control system design through solving a Constraint Satisfaction Problem (CSP) using artificial intelligence, first using a genetic algorithm then using a Convolutional Neural Network (CNN). The genetic algorithm determines the feasible controller parameters by minimizing a cost function subject to inequality design constraints. The CNN-finds the parameters by designing a deep neural network. It is shown that the evolutionary optimization algorithm converges almost surely to the optimal solution. To demonstrate the methodologies, they are applied to the design of PID controllers for linear and nonlinear systems. Two examples are presented, an armature-controlled DC motor and Bouc-Wen nonlinear hysteresis model. Simulations results show that the proposed methods yield solutions that satisfy design specifications.
This paper presents modeling of stepping motor and control design of input pulse timing for the suppression control of vibration. The stepping motor has the transient response of electric current for the pulse input. ...
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ISBN:
(纸本)9789728865825
This paper presents modeling of stepping motor and control design of input pulse timing for the suppression control of vibration. The stepping motor has the transient response of electric current for the pulse input. Therefore, the motor model considering the transient response of the current is built. The validity of the proposed model is verified by comparing the model considering the transient response of the current with the one without its consideration. Design of the pulse input timing in the method of the four pulse drive is realized to achieve the desired angle without vibration and overshoot using an optimization method. Finally, the effectiveness of the proposed method is demonstrated by comparing simulation results with experiments.
Since the beginning of 2020 in few weeks all the world has been interested by the pandemic due to SARS-CoV 2, causing more than 3 millions of dead people and more than 146 millions of infected patients. The virus move...
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ISBN:
(纸本)9789897585227
Since the beginning of 2020 in few weeks all the world has been interested by the pandemic due to SARS-CoV 2, causing more than 3 millions of dead people and more than 146 millions of infected patients. The virus moves with people and the most effective containment measure appears to be the severe lockdown;on the other hand, for obvious social and economic reasons, it can not be applied for long periods. Moreover, the increasing knwoledge on the virus and on its trasmission modes suggested various strategies, such as the use of masks, social distancing, disinfection and the fast identification of infected patients, up to the recent vaccination campaign. In this paper, the COVID-19 spread is studied referring to the Italian situation;the control actions introduced during 2020-2021 are identified in terms of their actual effects, allowing to study possible intervention scenarios.
In this paper, a new SMC (sliding mode control) method for the slip suppression control of EVs (electric vehicles) is proposed. The proposed method aims to improve the maneuverability, the stability and the low energy...
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ISBN:
(纸本)9789898565716
In this paper, a new SMC (sliding mode control) method for the slip suppression control of EVs (electric vehicles) is proposed. The proposed method aims to improve the maneuverability, the stability and the low energy consumption of EVs by controlling the wheel slip ratio. The proposed method is the extended SMC method adding the integral term to improve the control performance. There also include numerical simulation results to demonstrate the effectiveness of the method.
In this paper the operation of electric power system is treated as a discrete event system and a Petri Net is used as formal tool to achieve it. Each component of power system is modelled as a single Petri Net and the...
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ISBN:
(纸本)9789897581984
In this paper the operation of electric power system is treated as a discrete event system and a Petri Net is used as formal tool to achieve it. Each component of power system is modelled as a single Petri Net and the complete model is reached by composition of these single Petri Nets. Properties such as: parallelism, conflict, concurrency and others are used to study the operation of the modelled system. In this study are detected undesired behaviors on the dynamics of system. The theory of supervisory control is used to avoid these undesired behaviors forcing the system to have a controlled behavior. To obtain a controlled system a set of constraint are modelled by linear inequalities and the systems is forced to obey it. A case study application is presented to illustrate the proposed model here.
This paper presents an original performance analysis applied to a flow-shop system driven by a set of local command units and a central controller. The performance evaluation is done with a timed coloured Petri net mo...
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ISBN:
(纸本)9728865600
This paper presents an original performance analysis applied to a flow-shop system driven by a set of local command units and a central controller. The performance evaluation is done with a timed coloured Petri net model. Simulation results show needs for bounding the controller response time in order to meet production targets.
Autonomous navigation in off-road environments is a challenging task for mobile robots. Recent success in artificial intelligence research demonstrates the suitability and relevance of neural networks and learning app...
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ISBN:
(纸本)9789897583803
Autonomous navigation in off-road environments is a challenging task for mobile robots. Recent success in artificial intelligence research demonstrates the suitability and relevance of neural networks and learning approaches for image classification and off-road robotics. Nonetheless, meaningful decision making processes require semantic knowledge to enable complex scene understanding on a higher abstraction level than pure image data. A promising approach to incooperate semantic knowledge are ontologies. Especially in the off-road domain, scene object correlations heavily influence the navigation outcome and misinterpretations may lead to the loss of the robot, environmental, or even personal damage. In the past, behavior-based control systems have proven to robustly handle such uncertain environments. This paper combines both approaches to achieve a situation-aware navigation in off-road environments. Hereby, the robot's navigation is improved using high-level off-road background knowledge in form of ontologies along with a reactive, and modular behavior network. The feasibility of the approach is demonstrated within different simulation scenarios.
The paper describes an interesting combination of auto-tuning and adaptive scheduling approaches to design and update a feedback/feedforward control of the temperature in buildings. The focus here is on residential ho...
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ISBN:
(纸本)9789897583049
The paper describes an interesting combination of auto-tuning and adaptive scheduling approaches to design and update a feedback/feedforward control of the temperature in buildings. The focus here is on residential houses endowed with radiant floors, which are intrinsically complex to control due to large inertia and operational constraints, and on the disturbance rejection of the external temperature. Pure auto-tuning techniques may fail to converge if the initialization step is not done properly, due to the wide variety of possible buildings and compensation hard to adapt in closed loop. The proposed approach combines a classification of the typology of rooms based on physical parameters with auto-tuning, so that in a two-step closed-loop procedure, the room cluster can be quickly identified, and consequently the feedback controller and feedforward compensator be tuned. Numerical examples are provided to test the robustness of the proposed approach.
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