the adaptive control of an overhead crane is developed based on Generalized Predictive Control (GPC) technique. the one-step ahead predictive control scheme is proposed for reducing the residual and transient oscillat...
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the adaptive control of an overhead crane is developed based on Generalized Predictive Control (GPC) technique. the one-step ahead predictive control scheme is proposed for reducing the residual and transient oscillations of a payload suspended on a rope and transferred by a crane, with respect to the variation of rope length and mass of a payload. the recursive least square (RLS) algorithm is applied to real-time estimate parameters of discrete-time model of a crane dynamic system. Feasibility and applicability of the proposed control technique were confirmed during experiments carried out on the laboratory stand. the results of experiments are presented and compared with performances of the linear controllers-based scheme designed using pole placement method.
this paper describes a common issues in architecture of the variety kind of vision-based sway sensors dedicated for the anti-sway solution as a feedback in close-loop systems. However, in the statement the author'...
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this paper describes a common issues in architecture of the variety kind of vision-based sway sensors dedicated for the anti-sway solution as a feedback in close-loop systems. However, in the statement the author's attention was focused on the issue related with vision sensor architecture insensitiveness on actual exposure light conditions. the night vision functionality was obtained through use infrared radiation. Author main attention was focused on possibility of use IR as a solution for insufficient light condition and their usefulness in different non-contact vision-based sensor architecture. All obtained results and considerations were conducted on the base vision sway sensor integrated with infrared illuminator assembled on the physical scaled model of the overhead travelling crane with hosting capability of 150 kg.
Non-integer order filters allow much greater flexibility in shaping of frequency responses than classical methods. In this paper authors present the methodology of digital filter design using non-integer order filter ...
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Non-integer order filters allow much greater flexibility in shaping of frequency responses than classical methods. In this paper authors present the methodology of digital filter design using non-integer order filter as a prototype. Implementation on the embedded testbed was performed to validate the presented method. Experiments with measuring of frequency response show consistency of implementation with desired characteristics. the presented approach is promising and can be successfully used in multiple applications.
this paper deals with analysis of suboptimal dual controller design for linear discrete time stochastic system with uncertain parameters. the design of the dual controller is based on augmentation of the criterion wit...
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this paper deals with analysis of suboptimal dual controller design for linear discrete time stochastic system with uncertain parameters. the design of the dual controller is based on augmentation of the criterion with suitable measure of the parameters uncertainty in order to explicitly ensure the probing property of the control law. As the uncertainty measure the weighted prediction error of the augmented state is chosen. this approach provides very good quality of the resulting control compared to other explicit dual control method. the drawback of the method can be, however, seen in the lack of methodology for selection of the supplemental weighting matrix. the aim of this article is thus to provide insight into a way how to chose this supplemental weighting matrix with minimum necessary optional parameters.
the new tool for off-line estimation of the state of discrete linear systems is presented. the algorithm of Finite Impulse Response (FIR) smoother is described and its optimality is proven. the optimality of this smoo...
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the new tool for off-line estimation of the state of discrete linear systems is presented. the algorithm of Finite Impulse Response (FIR) smoother is described and its optimality is proven. the optimality of this smoother means that error covariance matrix of the estimation is minimal. It places this method in the Least Square Estimation (LSE) methods group, which are much better than frequently used Least Mean Square (LMS) methods. this method can also be used as FIR filter or predictor. In the paper the simple simulation, showing the mode of actions of described smoother, is presented. It is compared with others presented in the literature.
this paper reports on a novel nonlinear controller for a single one-degree-of-freedom (1-DOF) Active Magnetic Bearing (AMB) system. the nonlinear feedback tools such as Lyapunov based techniques, control Lyapunov func...
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this paper reports on a novel nonlinear controller for a single one-degree-of-freedom (1-DOF) Active Magnetic Bearing (AMB) system. the nonlinear feedback tools such as Lyapunov based techniques, control Lyapunov functions (CLFs), and feedback passivation control are developed. the control objective is to globally stabilize the mass position of an AMB with flux feedback. the flux-based control model for an AMB system is derived due to voltage switching strategy with voltage saturation. this strategy enables the flux control under a zero-bias operation. the proposed nonlinear CLF with a zero-bias can achieve a dynamic performance superior to that of a linear controller withthe zero-bias or withthe classical bias operations.
this paper describes a Model Predictive Control (MPC) algorithm in which a Radial Basis Function (RBF) neural network is used as a dynamic model of the controlled process and it reports training and selection of the R...
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this paper describes a Model Predictive Control (MPC) algorithm in which a Radial Basis Function (RBF) neural network is used as a dynamic model of the controlled process and it reports training and selection of the RBF model of the benchmark system for MPC. In order to obtain a computationally uncomplicated control scheme, the RBF model is successively linearised on-line, which leads to an easy to solve quadratic optimisation problem, nonlinear optimisation is not necessary. Efficacy of the MPC algorithm is shown for a neutralisation system, which is a significantly nonlinear dynamic process. It is shown that the described MPC algorithm with on-line model linearisation gives trajectories very similar to those obtained in a truly nonlinear MPC scheme, in which the full nonlinear RBF model is used for prediction.
this paper discusses the possibility of using a Jordan neural network as a model of dynamic systems and it presents a Model Predictive Control (MPC) algorithm in which such a network is used for prediction. the Jordan...
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this paper discusses the possibility of using a Jordan neural network as a model of dynamic systems and it presents a Model Predictive Control (MPC) algorithm in which such a network is used for prediction. the Jordan network is a simple recurrent neural structure in which only one value of the process input signal (from the previous sampling instant) and only one value of the delayed output signal of the model (from the previous sampling instant) are used as the inputs of the network. In order to obtain a computationally simple MPC algorithm, the nonlinear Jordan neural model is repeatedly linearised on-line around an operating point, which leads to a quadratic optimisation problem. Effectiveness of the described MPC algorithm is compared withthat of the truly nonlinear MPC scheme with on-line nonlinear optimisation performed at each sampling instant.
the paper discusses different abstract state-space representations for a class of linear distributed parameter systems of hyperbolic type defined on a one-dimensional spatial domain. It starts withthe homogeneous sta...
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the paper discusses different abstract state-space representations for a class of linear distributed parameter systems of hyperbolic type defined on a one-dimensional spatial domain. It starts withthe homogeneous state equation including the unbounded formal state operator. Based on the semigroup approach, some theoretical results of well-posedness and internal stability for the considered systems are given here. Next, the boundary and observation operators are introduced, taking a typical boundary inputs configuration as well as pointwise observations of the state variables. Consequently, the homogeneous state equation is extended to the so-called boundary control state/signal form. Finally, the most classical state-space representation involving typical (A, B, C)-triple of state, input and output operators is considered together withthe definition of the Pritchard-Salamon class of infinite-dimensional systems.
Nowadays, novel construction materials, more efficient power supplies and advanced artificial intelligence algorithms allow one to use unmanned aerial vehicles (UAV) in various fields of life. One of the biggest event...
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ISBN:
(纸本)9781479987023
Nowadays, novel construction materials, more efficient power supplies and advanced artificial intelligence algorithms allow one to use unmanned aerial vehicles (UAV) in various fields of life. One of the biggest events promoting this idea is the Air Cargo Challenge (ACC) competition. In this paper the motivation for ACC participation and the overall procedure of CAD aided UAV design are presented. the nonlinear aircraft model as well as Computational Fluid Dynamic simulations are discussed. Finally, some details concerning designed UAV prototype are revealed.
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