This paper employs the Teaching Learning Based Optimization (TLBO) algorithm for the design of an adaptive Model Predictive controller (AMPC) to control a discrete-time multi-input multi-output (MIMO) system. The MIMO...
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ISBN:
(数字)9798350391282
ISBN:
(纸本)9798350391299
This paper employs the Teaching Learning Based Optimization (TLBO) algorithm for the design of an adaptive Model Predictive controller (AMPC) to control a discrete-time multi-input multi-output (MIMO) system. The MIMO system considered in this work is associated with parametric uncertainties subjected to input constraints. Gradient descent-based adaption law has been used to update the system parameters. The effectiveness of the TLBO AMPC is verified through the simulation results. The output responses show that the system output tracks the reference input signal. The robustness of the controller is verified through its parameter variations.
This paper develops a data-driven stabilization method for continuous-time linear time-invariant systems with theoretical guarantees and no need for signal derivatives. The framework, based on linear matrix inequaliti...
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When estimating models of a multivariable dynamic system, a typical condition for consistency is to require the input signals to be persistently exciting, which is guaranteed if the input spectrum is positive definite...
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A CBjT high-speed operational amplifier (op-amp) has been developed and studied, which differs from known in its modified input stage (IS), as well as the architecture of the intermediate “folded” cascode (FC). The ...
ISBN:
(数字)9798350362893
ISBN:
(纸本)9798350362909
A CBjT high-speed operational amplifier (op-amp) has been developed and studied, which differs from known in its modified input stage (IS), as well as the architecture of the intermediate “folded” cascode (FC). The proposed circuits IS and FC circuits solve the problem of increasing the maximum slew rate of the output voltage (SR) in large-signal mode by more than 10 times. In the LTspice environment, computer simulation of an op-amp on complementary bipolar transistors was performed, which shows that the use of the developed transient correction circuits makes it possible to increase SR from 103 V/μs to 1408 V/μs. The logarithmic amplitude-frequency characteristics of the op-amp under study are given for different options for its inclusion - with and without general negative feedback. The leading and trailing edges of the op-amp transient process were studied with an input rectangular pulse signal with an amplitude of 5V at different values of the capacitance of the additional correction capacitor $C_{\mathbf{k1}}$. The simulation results are presented in the form of a table that establishes the relationship between the numerical values of the maximum rate of rise of the output voltage of the op-amp and the capacitance $C_{\mathbf{k1}}$. The considered op-amp is recommended for use in various automation devices and communication systems, for example, discrete-analog filters on switched capacitors, high-speed ADC drivers, etc.
Accurate wind speed prediction has been becoming an indispensable technology in system security,wind energy utilization,and power grid dispatching in recent ***,it is an arduous task to predict wind speed due to its v...
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Accurate wind speed prediction has been becoming an indispensable technology in system security,wind energy utilization,and power grid dispatching in recent ***,it is an arduous task to predict wind speed due to its variable and random *** the objective to enhance the performance of forecasting short-term wind speed,this work puts forward a hybrid deep learning model mixing time series decomposition algorithm and gated recurrent unit(GRU).The time series decomposition algorithm combines the following two parts:(1)the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),and(2)wavelet packet decomposition(WPD).Firstly,the normalized wind speed time series(WSTS)are handled by CEEMDAN to gain pure fixed-frequency components and a residual *** WPD algorithm conducts the second-order decomposition to the first component that contains complex and high frequency signal of raw ***,GRU networks are established for all the relevant components of the signals,and the predicted wind speeds are obtained by superimposing the prediction of each *** from two case studies,adopting wind data from laboratory and wind farm,respectively,suggest that the related trend of the WSTS can be separated effectively by the proposed time series decomposition algorithm,and the accuracy of short-time wind speed prediction can be heightened significantly mixing the time series decomposition algorithm and GRU networks.
Sleep apnoea is a common sleep disorder during human sleep. It is usually diagnosed by a doctor after recording one nights' sleep signals. Patients have to go to the hospital to record sleep signals, which is time...
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Converse negative imaginary theorems for linear time-invariant systems are derived. In particular, we provide necessary and sufficient conditions for a feedback system to be robustly stable against various types of ne...
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For identification of a single module in a linear dynamic network with correlated disturbances different meth-ods are available in a prediction error setting. While indirect methods fully rely on the presence of a suf...
For identification of a single module in a linear dynamic network with correlated disturbances different meth-ods are available in a prediction error setting. While indirect methods fully rely on the presence of a sufficient number of external excitation signals for achieving data-informativity, the local direct method with a MIMO predictor model can exploit also non-measured disturbance signals for data-informativity. However, a simple two-node example shows that this local direct method can also be conservative in terms of the number of ex-ternal excitation signals that is required. Inspired by a recently introduced multi-step method for full network identification, we present a multi-step least squares method for single module identification. In a first indirect step a model is estimated that is used to reconstruct the innovation on a set of output signals, which in a second step is used to directly estimate the module dynamics with a MISO predictor model. The resulting path-based conditions for data-informativity show that the multi-step method requires a smaller number of excitation signals for data-informativity than the local direct method.
Motivated by the increasing requirements in positioning precision for lithography applications, this paper analyzes how the position error in a high-precision motion system is affected by the response of the controlle...
Motivated by the increasing requirements in positioning precision for lithography applications, this paper analyzes how the position error in a high-precision motion system is affected by the response of the controlled power amplifier that drives the motor. Based on the analysis, guidelines for designing a reference model in continuous or discrete time that satisfies certain requirements that would decrease the overall position error are presented. Then, a data-driven control method, namely Virtual Reference Feedback Tuning (VRFT), is employed to directly synthesize both feedback and feedforward controllers based on the designed reference model. The position error of the motion system with the data-driven controlled power amplifier is compared to the case when classical industrial controllers are employed in the control of the amplifier. If adequate reference models are designed, the VRFT-controlled power amplifier can significantly decrease the position error such that it is close to the ideal position error. All of the presented results are based on simulations.
The expediency of using multi-functional laboratory stands in the process of training specialists in the electromechanical profession is substantiated. The paper contains characteristics of the small-scale model of th...
The expediency of using multi-functional laboratory stands in the process of training specialists in the electromechanical profession is substantiated. The paper contains characteristics of the small-scale model of the "Teplopunkt" laboratory stand, on the basis of which it is possible to research the means of automation of heating systems with supply ventilation. The structure of the automated control and monitoring system of the "Teplopunkt" laboratory stand is given. A laboratory workshop based on a small-scale model is developed. Its implementation allows improving the effectiveness of practical training of specialists in the field of automation of thermal processes. The dynamic characteristics of the operation of the laboratory stand with the maintenance of a constant temperature of the heat-transfer agent based on the mathematical model are obtained.
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