This paper deals with the actuator fault diagnosis and accommodation problem for the aero space vehicle (ASV). A novel nonlinear robust adaptive observer is developed for estimation of the actuator fault under the lip...
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The field of Unmanned Aerial Vehicles (UAV) has gained great significance in the R&D activities of several institutions, and numerous realizations have been constructed. Controlling the movement of a UAV is one of...
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ISBN:
(纸本)9789633130117
The field of Unmanned Aerial Vehicles (UAV) has gained great significance in the R&D activities of several institutions, and numerous realizations have been constructed. Controlling the movement of a UAV is one of the most significant tasks in the hierarchical control system that should be realized in order to successfully manage UAVs in several missions. Precise control of the movement requires accurate mathematical models of the aircraft that correspond to the several control schemes that are intended to apply, including linearised, LPV, and nonlinear ones. The source of mathematical models includes the physical model constructed on the basis of the Newtonian equations and the rules of aerodynamics, as well as the use of empirical observations, measurements. The methodology of system identification offers the tools that can be used to manage this field. The Systems and Control Laboratory of the computer and automation Research Institute in cooperation with University of Minnesota and Budapest University of Technology and Economics has built - as a part of a more general framework established to solve complex UAV control problems - small UAVs, equipped with on-board sensors and embedded computer with the purpose of obtaining an adequate test platform for the aircraft experiments. Based on on-board measurements acquired during the flight tests performed with the UAVs, the opportunity has been given to test several system identification approaches corresponding to the control tasks to be solved. This paper gives an outline of the system identification and modelling methods that have successfully been applied, and also analyzes the problems encountered in the data-acquisition - signal processing - computing chain.
Brain emotional learning based intelligent controller (BELBIC) is based on computational model of limbic system in the mammalian brain. In recent years, this model was applied in many linear and nonlinear control appl...
Brain emotional learning based intelligent controller (BELBIC) is based on computational model of limbic system in the mammalian brain. In recent years, this model was applied in many linear and nonlinear control applications. Previous studies show that this controller has fast response, simple implementation and robustness with respect to disturbances. It is also possible to define emotional signal based on control application objectives. But in the previous studies, internal instability of this controller was not considered and control task were done in limited time period. In this article mathematical description of BELBIC is investigated and improved to avoid internal instability. Simulation and implementation of improved model was done on level plant. The obtained results showed that instability of model has been solved in the new model without loss of performance by using Integral Anti Windup (IAW).
This paper investigates the robust sliding mode control problem for a class of uncertain switched delay systems. A single sliding surface is constructed such that the reduced-order equivalent sliding motion restricted...
This paper investigates the robust sliding mode control problem for a class of uncertain switched delay systems. A single sliding surface is constructed such that the reduced-order equivalent sliding motion restricted to the sliding surface is completely invariant to all admissible uncertainties. For the cases of known delay and unknown delay, the existence conditions of the sliding surface are proposed, respectively. The corresponding hysteresis switching laws are designed to asymptotically stabilize the sliding motion. Furthermore, variable structure controllers are developed to drive the state of the switched system to reach the single sliding surface in finite time and remain on it thereafter. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
The output feedback stabilizability problem of a class of uncertain switched systems is investigated using sliding mode control and a synthesis design solution derived. Firstly, a common sliding surface is constructed...
The output feedback stabilizability problem of a class of uncertain switched systems is investigated using sliding mode control and a synthesis design solution derived. Firstly, a common sliding surface is constructed such that the system restricted to the sliding surface is asymptotically stable and completely invariant to matched and mismatched uncertainties under arbitrary switching. Secondly, static and dynamic output feedback variable structure controllers are designed that can drive the state of the switched system to reach the common sliding surface in finite time and remain them thereafter. A illustrative example is given to demonstrate the effectiveness of the proposed method.
This paper deals with the actuator fault diagnosis and accommodation problem for the aero space vehicle (ASV). A novel nonlinear robust adaptive observer is developed for estimation of the actuator fault under the Lip...
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This paper deals with the actuator fault diagnosis and accommodation problem for the aero space vehicle (ASV). A novel nonlinear robust adaptive observer is developed for estimation of the actuator fault under the Lipschitz condition on the nonlinear part of such systems, which is used to continuously accommodate the control signal, so as to ensure the stability of faulty system. Finally, simulation results about ASV are presented to illustrate the feasibility and effectiveness of the proposed methods.
The paper investigates a model predictive control (MPC) strategy specialized in urban traffic management in order to relieve traffic congestion, reduce travel time and improve homogenous traffic flow. Over the theory ...
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The paper investigates a model predictive control (MPC) strategy specialized in urban traffic management in order to relieve traffic congestion, reduce travel time and improve homogenous traffic flow. Over the theory the realization of the control method is also presented. To validate the effectiveness of the controller a busy traffic network was chosen for test field. The MPC strategy was implemented into the test network control system (hardware in loop simulation). The applied environment is a microscopic traffic simulator with mathematical software and proper computational applications for the evaluation. The simulation results prove the effectiveness of the designed MPC based traffic control strategy. The system is able to improve the network efficiency and reduce travel time, creating optimal flow in the network subjected to control input constraints.
There are many different instruction scheduling techniques that are used in compilers today. The most frequently used one is the list scheduling. It is easy to implement and gives good results in most cases. It works ...
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There are many different instruction scheduling techniques that are used in compilers today. The most frequently used one is the list scheduling. It is easy to implement and gives good results in most cases. It works on the basic block level. According to Fisher and Rau instruction level parallelism that can be achieved using this technique cannot be greater then 2. Architectures with deep pipeline can run much more instructions in the same cycle and global scheduler techniques can give better results. In our tests we used a dominator path scheduler with three different strategies for choosing the scheduling paths. Our application encoded sound to the mp3 format, and was run on a digital signal processor with a deep pipeline. Using these scheduling techniques, our C compiler generated 10% fewer NOP instructions compared to local instruction scheduling. In addition, this implementation of a dominator path scheduler was used on a C compiler for SUN Sparc processors (for testing purposes only), and it was shown that the same implementation of the scheduler can be used for different platforms.
Using induced L 2 -norm minimization, a robust controller was developed for insulin delivery in Type I diabetic patients. The high-complexity nonlinear diabetic patient Sorensen-model [1] was considered. LPV (Linear P...
Using induced L 2 -norm minimization, a robust controller was developed for insulin delivery in Type I diabetic patients. The high-complexity nonlinear diabetic patient Sorensen-model [1] was considered. LPV (Linear Parameter Varying) methodology was used to develop open loop model and robust controller. Considering the normoglycemic set point (81.1 mg/dL), a polytopic set was created over the physiologic boundaries of the glucose-insulin interaction of the Sorensen-model. In this way, LPV model formalism was defined. The robust control was developed considering input and output multiplicative uncertainties with other weighting functions.
This paper introduces a complex dynamical network with time-varying coupling delays and investigates its locally and globally synchronization. Based on the Lyapunov-Krasovskii functional method, some decentralized ada...
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This paper introduces a complex dynamical network with time-varying coupling delays and investigates its locally and globally synchronization. Based on the Lyapunov-Krasovskii functional method, some decentralized adaptive synchronization criteria are derived. The coupling terms are bounded by high-order polynomials, which are applicable to a large class of complex dynamical networks. The effectiveness of the proposed synchronization scheme are illustrated by a numerical example.
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