This paper proposes a method to compute finite abstractions that can be used for synthesizing robust hybrid control strategies for nonlinear systems. Most existing methods for computing finite abstractions utilize som...
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This paper proposes a model predictive control (MPC) approach for discrete-time jump Markov linear systems (JMLS) considering constraints on the inputs as well as on the expectancy of the states. Prediction equations ...
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ISBN:
(纸本)9781479917730
This paper proposes a model predictive control (MPC) approach for discrete-time jump Markov linear systems (JMLS) considering constraints on the inputs as well as on the expectancy of the states. Prediction equations for the first moment of the states are formulated, in which the dependencies on the inputs, on the expected values of disturbances, and on the current states are directly considered. For the computation of the matrices needed for predicting the first moment of the states, a recursive algorithm is presented. Finally, the prediction equations are used to formulate the MPC problem as a quadratic program (QP). Due to the recursive structure of the prediction equations and the formulation as a QP, the computational effort is low compared to existing approaches. Simulation results demonstrate the properties of the presented MPC approach and its capabilities of controlling large-scale JMLS online.
The outage probability of a two-hop coordinated decode-and-forward relay network is investigated. Relay coordination is performed only with the dominant interferer. Different levels of network coordination are studied...
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ISBN:
(纸本)9781467364300
The outage probability of a two-hop coordinated decode-and-forward relay network is investigated. Relay coordination is performed only with the dominant interferer. Different levels of network coordination are studied and their performances are compared. Exact expressions are derived for the outage probability of a particular mobile user for each coordination scheme. Asymptotic outage probability is derived to identify the diversity and coding gains for each coordination scheme.
The performance of optimum combining (OC) in decode-and forward (DF) relaying in the presence of a Poisson field of interferers is analyzed. An approximation for the outage probability of the OC receiver is derived by...
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ISBN:
(纸本)9781467364300
The performance of optimum combining (OC) in decode-and forward (DF) relaying in the presence of a Poisson field of interferers is analyzed. An approximation for the outage probability of the OC receiver is derived by considering the temporal correlation of the interference. Despite the randomness of the number and the locations of the interferers, the OC receiver suppresses the interference at the destination node and diversity gains are achieved, provided that the relay nodes are noise limited. For single-antenna relay nodes, the end-to-end performance is vulnerable to interference at the relay nodes which is not canceled, resulting in zero diversity gains.
In this paper, the state estimation problem is investigated for a class of discrete-time complex networks under the eventtriggered framework. The event-based estimator receives the updated measurements from the sensor...
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ISBN:
(纸本)9781467374439
In this paper, the state estimation problem is investigated for a class of discrete-time complex networks under the eventtriggered framework. The event-based estimator receives the updated measurements from the sensors only when the prespecified event-triggering rule is violated. Compared with the traditional estimator with the clock driven rule, a series of event-based state estimators are developed so as to reduce unnecessary data transmissions in the communication channel. Attention is focused on the analysis and design problem of the event-based estimators for the addressed discrete-time complex networks such that the estimation error is exponentially bounded in mean square. Some sufficient conditions are obtained to ensure the existence of the desired estimators and the upper bound of the estimation error is derived. By using the convex optimization technique,the gain parameters of the desired estimators are obtained in an explicit form. Finally, a numerical example is used to show the effectiveness of the proposed estimation approach.
Visitors utilize the urban space based on their thermal perception and thermal environment. The thermal adaptation engages the user’s behavioural, physiological and psychological aspects. These aspects play critical ...
Visitors utilize the urban space based on their thermal perception and thermal environment. The thermal adaptation engages the user’s behavioural, physiological and psychological aspects. These aspects play critical roles in user’s ability to assess the thermal environments. Previous studies have rarely addressed the effects of identified factors such as gender, age and locality on outdoor thermal comfort, particularly in hot, dry climate. This study investigated the thermal comfort of visitors at two city squares in Iran based on their demographics as well as the role of thermal environment. Assessing the thermal comfort required taking physical measurement and questionnaire survey. In this study, a non-linear model known as the neural network autoregressive with exogenous input (NN-ARX) was employed. Five indices of physiological equivalent temperature (PET), predicted mean vote (PMV), standard effective temperature (SET), thermal sensation votes (TSVs) and mean radiant temperature (T
mrt) were trained and tested using the NN-ARX. Then, the results were compared to the artificial neural network (ANN) and the adaptive neuro-fuzzy inference system (ANFIS). The findings showed the superiority of the NN-ARX over the ANN and the ANFIS. For the NN-ARX model, the statistical indicators of the root mean square error (RMSE) and the mean absolute error (MAE) were 0.53 and 0.36 for the PET, 1.28 and 0.71 for the PMV, 2.59 and 1.99 for the SET, 0.29 and 0.08 for the TSV and finally 0.19 and 0.04 for the T
mrt.
We propose a forward error correction (FEC) coding rate adaptation scheme which maximizes the quality of experience (QoE), for scalable video coding (SVC) based video transmissions over multi-input multi-output (MIMO)...
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ISBN:
(纸本)9781467364300
We propose a forward error correction (FEC) coding rate adaptation scheme which maximizes the quality of experience (QoE), for scalable video coding (SVC) based video transmissions over multi-input multi-output (MIMO) systems. The proposed scheme adaptively selects the best set of spatial channels, number of video layers and their corresponding FEC coding rate according to channel state information (CSI) from the receiver. Unlike previous work, our proposed scheme distributes the FEC encoded bit streams to multiple spatial channels so that additional diversity gains can be obtained. Due to the complexity of the optimization, we decompose the original problem into several sub-problems, which can then be solved by a heuristic algorithm. The optimal solution can be found by choosing the best among all the candidate solutions obtained from the sub-problems. The effectiveness and superb performance of our proposed scheme can be demonstrated by many simulations with different videos and channel conditions.
Characteristic modeling and the adaptive control design based on it have attracted increasing attention from the research community due to their many successful practical applications that have been reported. This pap...
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ISBN:
(纸本)9781467374439
Characteristic modeling and the adaptive control design based on it have attracted increasing attention from the research community due to their many successful practical applications that have been reported. This paper presents a Matlab simulation platform that has been developed to facilitate the study of characteristic model based adaptive controlsystems. The simulation platform consists of two interweaving components: for a given continuous-time linear time-invariant plant, represented by a transfer function, and a specified sampling period, the simulation platform calculates a discretized model of the plant, and the corresponding characteristic model, and with a specified set of initial conditions of the characteristic model and its coefficients, along with the specified duration of simulation and reference input, the simulation platform will adaptively tune the coefficients of the characteristic model and calculate the outputs of the plant and the characteristic model. All the data needed for the simulation will be entered through a graphic user interface, which also plots the evolution of the outputs of the plant and the characteristic model as well as the evolution of the coefficients of the characteristic model. The simulation results can also be saved for off line plotting and analysis through the graphic user interface.
In this paper, the accuracy of soft computing technique in solar radiation prediction based on series of measured meteorological data (monthly mean sunshine duration, monthly mean maximum and minimum temperature) taki...
In this paper, the accuracy of soft computing technique in solar radiation prediction based on series of measured meteorological data (monthly mean sunshine duration, monthly mean maximum and minimum temperature) taking from Iseyin meteorological station in Nigeria was examined. The process, which simulates the solar radiation with support vector regression (SVR), was constructed. The inputs were monthly mean maximum temperature (Tmax), monthly mean minimum temperature (Tmin) and monthly mean sunshine duration ( $$ \bar{n} $$ ). Polynomial and radial basis functions (RBF) are applied as the SVR kernel function to estimate solar radiation. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR with polynomial basis function compared to RBF. The SVR coefficient of determination R 2 with the polynomial function was 0.7395 and with the radial basis function, the R 2 was 0.5877.
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