This paper examines robust partially mode de lay dependent H ∞ output feedback controller design for discrete-time systems with random communication delays. A finite state Markov chain with partially known transitio...
详细信息
This paper examines robust partially mode de lay dependent H ∞ output feedback controller design for discrete-time systems with random communication delays. A finite state Markov chain with partially known transition probabilities is used to model random communication delays between sensors and controller. Based on Lyapunov-Krasovskii functional, a novel methodology for designing a partially mode delay-dependent output feedback controller is proposed. Using cone complementarity linearization algorithm bilinear matrix inequalities (BMIs) are solved to obtain the controller gains. We also show that the results for completely known transition probabilities and completely unknown transition probabilities can be derived as special cases of our result. The effectiveness of the proposed design methodology is demonstrated by a numer ical example. To the best of authors' knowledge, the problem of designing an output feedback controller for a partially known transition probability has not been fully investigated.
In this paper, a direct synthesis approach is proposed to design ETF based multivariable decoupling controllers. This new scheme is different from two existing ETF based decoupling schemes which involves the following...
详细信息
In this paper, a direct synthesis approach is proposed to design ETF based multivariable decoupling controllers. This new scheme is different from two existing ETF based decoupling schemes which involves the following steps: (1) by uniquely determine the ETFs for every transfer function element, the inverse matrix of transfer function matrix is approximated; (2) selecting the desired closed-loop system transfer function such that the resulted controllers are stable, causal and proper; (3) deriving the achievable full-matrix decoupling controller by specifying the tuning parameters. The effectiveness of the proposed design approach is verified by two multivariable industrial processes, which shows that it results in better overall system performance than other two ETF based schemes.
Quantization effects are inevitable in networked controlsystems (NCSs). These quantization effects can be reduced by increasing the number of quantization levels. However, increasing the number of quantization levels...
详细信息
Quantization effects are inevitable in networked controlsystems (NCSs). These quantization effects can be reduced by increasing the number of quantization levels. However, increasing the number of quantization levels may lead to network congestion, (i.e., the network needs to transfer more information than its capacity). In this paper, we investigate the problem of designing a robust ℋ ∞ output feedback controller for discrete-time networked systems with an adaptive quantization density or limited information. More precisely, the quantization density is designed to be a function of the network load condition which is modeled by a Markov process. A stability criterion is developed by using Lyapunov-Krasovskii functional and sufficient conditions for the existence of a dynamic quantized output feedback controller are given in terms of Bilinear Matrix Inequalities(BMIs). An iterative algorithm is suggested to obtain quasi-convex Linear Matrix Inequalities (LMIs) from BMIs. An example is presented to illustrate the effectiveness of the proposed design.
This paper presents a new adaptive controller for visual tracking control of a robot manipulator in 3D general motion with a fixed camera whose intrinsic and extrinsic parameters are uncalibrated. In addition to camer...
详细信息
This paper presents a new adaptive controller for visual tracking control of a robot manipulator in 3D general motion with a fixed camera whose intrinsic and extrinsic parameters are uncalibrated. In addition to camera parameters, the feature positions in 3D space are also assumed unknown. Based on the fact that the unknown parameters appears linearly in the closed-loop dynamics of the system if the depth-independent interaction matrix is adopted to map the image errors onto the joint space of the manipulator, we developed a new adaptive algorithm to estimated the unknown parameters on-line. With a full consideration of dynamic responses of the robot manipulator, we employ the Lyapunov method to prove asymptotic convergence of the image errors. Experimental results are used to demonstrate the performance of the proposed approach.
Abstract Epistatic miniarray profiling (E-MAP) is powerful for measuring gene biological relevance. However, E-MAP suffers from large number of missing values, and in order to use the E-MAP information more efficientl...
详细信息
Abstract Epistatic miniarray profiling (E-MAP) is powerful for measuring gene biological relevance. However, E-MAP suffers from large number of missing values, and in order to use the E-MAP information more efficiently, the missing values have to be estimated. In this paper, considering advantages and disadvantages of different independent algorithms, we proposed a novel fusion approach based on the high-level diversity to estimate missing values that consists of two global and four local base estimators. Experiment results show our fusion scheme is more effective and robust for the missing value imputations and outperforms all single base algorithms on E-MAP data.
In wireless sensor networks (WSNs), trap coverage has recently been proposed to tradeoff between the availability of sensor nodes and sensing performance. It offers an efficient framework to tackle the challenge of li...
详细信息
In wireless sensor networks (WSNs), trap coverage has recently been proposed to tradeoff between the availability of sensor nodes and sensing performance. It offers an efficient framework to tackle the challenge of limited resources in large scale sensor networks. Currently, existing works only studied the theoretical foundation of how to decide the deployment density of sensors to ensure the desired degree of trap coverage. However, the practical issues such as how to efficiently schedule sensor node to guarantee trap coverage under an arbitrary deployment is still left untouched. In this paper, we formally formulate the Minimum Weight Trap Cover Problem and prove it is an NP-hard problem. To solve the problem, we introduce a bounded approximation algorithm, called Trap Cover Optimization (TCO) to schedule the activation of sensors while satisfying specified trap coverage requirement. The performance of Minimum Weight Trap Coverage we find is proved to be at most O(ρ) times of the optimal solution, where ρ is the density of sensor nodes in the region. To evaluate our design, we perform extensive simulations to demonstrate the effectiveness of our proposed algorithm and show that our algorithm achieves at least 14% better energy efficiency than the state-of-the-art solution.
Nowadays, probe vehicles equipped with Global Position system (GPS) are an effective way of collecting real-time traffic information. This paper first briefly introduces the Curve-Fitting Estimation Model (CFEM), whic...
详细信息
Nowadays, probe vehicles equipped with Global Position system (GPS) are an effective way of collecting real-time traffic information. This paper first briefly introduces the Curve-Fitting Estimation Model (CFEM), which is one of the typical methods using GPS data to estimate the traffic flow state. After that, it is detailedly analyzed how many probe vehicles the CFEM requires in order to ensure enough estimated accuracy. Furthermore, a sample size algorithm is developed to calculate the minimum sample size of the CFEM. In the algorithm, the road type, the length of road section, and sample frequency are taken into account. Finally, the proposed algorithm of sample size analysis are tested by the experiments using the data collected from the road network of the whole center region of Shanghai.
The estimator design of discrete-time networked controlsystems with multi-quantized output feedback is concerned. First, the system model and the estimate model of multi-quantized network controlsystem with two quan...
详细信息
The estimator design of discrete-time networked controlsystems with multi-quantized output feedback is concerned. First, the system model and the estimate model of multi-quantized network controlsystem with two quantizers are given, respectively. Then the asymptotic invariance of the covariance matrix about the estimation error system is studied, and some corresponding conclusions are obtained. The estimator error is made minimum by the designed state estimator. At last, a numerical example is given to illustrate the effectiveness of the estimator.
Because the structure and function of a high-rise building is complex and the density of occupants in it is high, fire safety is still a worldwide difficult problem. Safety and timely evacuation is an important issue ...
详细信息
Nowadays, decision tree is widely used as one of the most powerful tools in data mining. However, to construct an optimization decision tree is a complete NP problem. So a new method about how to construct decision tr...
详细信息
ISBN:
(纸本)9781612844923
Nowadays, decision tree is widely used as one of the most powerful tools in data mining. However, to construct an optimization decision tree is a complete NP problem. So a new method about how to construct decision tree, which is based on association rule mining, is proposed in this paper. Firstly, approximate exact rule with high reliability is defined. Secondly new attributes are generated from the approximate exact rule. And then its evaluation method is discussed in detail. Thirdly, the decision tree is constructed with both the new generated attributes and its original data. Finally, after comprehensive analysis, experimental results show that this new method has higher accuracy than any other old method.
暂无评论