The aim of this paper is to introduce, in detail, a novel approach for tuning of anisochronic singleinput single-output controllers for infinite-dimensional feedback control systems. A class of Linear Time- Invariant ...
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The aim of this paper is to introduce, in detail, a novel approach for tuning of anisochronic singleinput single-output controllers for infinite-dimensional feedback control systems. A class of Linear Time- Invariant Time Delay Systems (LTI TDSs) is taken as a typical representative of infinite-dimensional systems. control design to obtain the eventual controller structure is made in the special ring of quasipolynomial meromorphic functions (RMS). The use of this algebraic approach with a simple feedback loop for unstable or integrating systems leads to infinite-dimensional (delayed) controllers as well as the whole feedback loop. A natural task is to set tunable controller parameters in order to form the crucial area of the infinite closed-loop spectrum. It is worth noting that not only poles yet also zeros are taken into account. The prescribed positions of the right-most reference-to-output poles and zeros are given on the basis of the desired overshoot for a simple finite-dimensional matching model the detailed analysis of which is provided. The dominant poles and zeros are shifted to the prescribed positions using the Quasi-Continuous Shifting Algorithm (QCSA) followed by the use of an advanced optimization algorithm. The whole methodology is called the Pole-Placement Shifting based controller tuning Algorithm (PPSA). The PPSA is demonstrated on the setting of parameters of delayed controller for an unstable time delay plant of a skater on the controlled swaying bow. This example, however, shows a treachery of the algorithm and a natural feature of an infinite-dimensional system - namely, that its spectrum or even its dominant part can not be placed arbitrarily. Advantages and drawback as well as possible modification of the algorithm are also discussed.
In this paper a novel controller for stable and precise operation of multi-rotors with heavy slung loads is introduced. First, simplified equations of motions for the multi-rotor and slung load are derived. The model ...
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ISBN:
(纸本)9781479923779
In this paper a novel controller for stable and precise operation of multi-rotors with heavy slung loads is introduced. First, simplified equations of motions for the multi-rotor and slung load are derived. The model is then used to design a Nonlinear Model Predictive controller (NMPC) that can manage the highly nonlinear dynamics whilst accounting for system constraints. The controller is shown to simultaneously track specified waypoints whilst actively damping large slung load oscillations. A Linear-quadratic regulator (LQR) controller is also derived, and control performance is compared in simulation. Results show the improved performance of the Nonlinear Model Predictive control (NMPC) controller over a larger flight envelope, including aggressive maneuvers and large slung load displacements. Computational cost remains relatively small, amenable to practical implementation. Such systems for small Unmanned Aerial Vehicles (UAVs) may provide significant benefit to several applications in agriculture, law enforcement and construction.
The problems of delay-dependent robust stability and stabilization for continuously singular timedelay systems with norm-bounded uncertainties are investigated in this paper. Based on a Lyapunov functional, which incl...
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The paper proposes a new learning method for fuzzy cognitive maps, which makes it possible to encode an attractor into the map. The method is based on the principle of backpropagation through time known from the theor...
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ISBN:
(纸本)9781629934884
The paper proposes a new learning method for fuzzy cognitive maps, which makes it possible to encode an attractor into the map. The method is based on the principle of backpropagation through time known from the theory of artificial neural networks. Simulation results are presented to show how well the method performs. It is shown that the results are superior to those achieved using Hebbian learning approaches such as nonlinear Hebbian learning. Some lines for possible future research and development are given.
In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson's disease (the most important Neurodegenerative Disorder). Analysis of the information correspond...
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In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson's disease (the most important Neurodegenerative Disorder). Analysis of the information corresponding to a prescribed movement involving tremor, and the related changes in brain connectivity is novel and original. Analytically, developing a space-time nonlinear adaptive system which fuses brain and gait information algorithmically is proposed here for the first time. The overall dynamic system will be constrained by the clinical impressions of the patient symptoms embedded in a knowledge-based system. The entire complex constrained problem were solved to enable a powerful model for recognition and monitoring of Parkinson's disease and establishing appropriate rules for its clinical following up.
Conventional agricultural fields are sprayed uniformly to control weeds, insects, and diseases. To reduce cultivation expenses, to produce healthier food and to create more environmentally friendly farms, chemicals sh...
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ISBN:
(纸本)9781479952007
Conventional agricultural fields are sprayed uniformly to control weeds, insects, and diseases. To reduce cultivation expenses, to produce healthier food and to create more environmentally friendly farms, chemicals should only be applied to the right place at the right time and exactly with the right amount. In this article, a task and motion planning for a team of autonomous vehicles to reduce chemicals in farming is presented. Field data are collected by small unmanned helicopters equipped with a range of sensors, including multispectral and thermal cameras. Data collected are transmitted to a ground station to be analyzed and triggers aerial and ground-based vehicles to start close inspection and/or plant/weed treatment in specified areas. A complete trajectory is generated to enable ground-based vehicle to visit infested areas and start chemical/mechanical weed treatment.
In this paper, a mathematical modeling of pneumatic actuator system is developed by using RLS algorithm. An ARX model is chosen for the model structure. In order to cater the time-varying parameter of pneumatic system...
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In this study, the current tracking problem of PMSM is handled as static feed-forward controller design for Linear Parameter Varying (LPV) system. H infinity controller formulated by means of Linear Matrix inequalitie...
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The paper deals with the robust control of air-flow in air heating set. The identification is performed using step responses and approximation via second order system. The controller is designed using the structured s...
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ISBN:
(纸本)9781479909964
The paper deals with the robust control of air-flow in air heating set. The identification is performed using step responses and approximation via second order system. The controller is designed using the structured singular value (SSV or μ) and algebraic approach. Since the cost function is nonconvex the optimization cannot be done using standard tools. Hence an evolutionary algorithm - Differential Migration (DM) is employed yielding good results in this case. The functionality of the controller is verified through experiments on the real plant.
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