A fuzzy c-regression model clustering algorithm based on Bias-Eliminated Least Squares method (BELS) is presented. This method is designed to develop an identification procedure for noisy nonlinear systems. The BELS m...
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ISBN:
(纸本)9781467363020
A fuzzy c-regression model clustering algorithm based on Bias-Eliminated Least Squares method (BELS) is presented. This method is designed to develop an identification procedure for noisy nonlinear systems. The BELS method is used to identify consequent parameters and eliminate the bias. The proposed approach has been applied to benchmark modeling problem which proved a good performance.
Particles can remember some information in an optimization process. They learn by themselves and from other particles, so the next generation can inherit much information from their parents and finally find optimal so...
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Particles can remember some information in an optimization process. They learn by themselves and from other particles, so the next generation can inherit much information from their parents and finally find optimal solutions. But particles are also faced with two problems of stagnating in a local but not global optimum. Genetic algorithms have strong global search ability. Genetic algorithms are combined with particles swarm optimization and an improved particles swarm optimization algorithm is proposed in this paper. The better individuals obtained by improved genetic algorithms can be improved further by particles swarm optimization. The experiments show that the proposed algorithm is better than traditional genetic algorithm and particles swarm.
This work shows an extension of dual-modifier adaptation methodology for RTO to reduce the infeasibilities. The main idea is to add a PI controller that is activated only when the measurements shows a violation in the...
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Many researchers have studied connections between the problems of feedback control and of communicating over a channel with feedback. We study two such feedback communication schemes, and focus on properties such as p...
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ISBN:
(纸本)9781467357159
Many researchers have studied connections between the problems of feedback control and of communicating over a channel with feedback. We study two such feedback communication schemes, and focus on properties such as phase margin, robustness with respect to unmodeled time delays, and exogenous noise inputs. In particular, we study the impact of unstable poles in the encoder or decoder on these properties, as quantified by the Bode sensitivity integral.
Efficient control of Networked control System (NCS) is a challenge, as the control methods need to deal with non-deterministic variable delays and data loss. This paper presents a novel hybrid approach to NCS where Mo...
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Efficient control of Networked control System (NCS) is a challenge, as the control methods need to deal with non-deterministic variable delays and data loss. This paper presents a novel hybrid approach to NCS where Model Predictive control (MPC) is applied as a main controller and implicit switching MPC is used for data transmission control in event-driven shared communication medium, leading to complex control system with active data transmission mechanisms.
Sustainable operation of Critical Infrastructure systems (CISs) is of a major concern to modern societies. Monitoring, control and security of such systems plays a key role in guaranteeing continuous, reliable and abo...
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Sustainable operation of Critical Infrastructure systems (CISs) is of a major concern to modern societies. Monitoring, control and security of such systems plays a key role in guaranteeing continuous, reliable and above all secure access to the resources provided by these systems. Development of adequate software and hardware structures, as well as algorithms to perform such functions cannot be done apart from the operational conditions of the plant. On the other hand the dependencies between the resources provided by the CIS and the societies, prevents from experiments. Also this approach could be found costly and hard to justify in the world driven by hard economics. This, once again calls for the simulation tools to be exploited. Due to the vast complexity of these systems including spatial distribution over a wide area, a controlengineering based multiagent framework is often utilised to cope with the issues of monitoring, control and security of CIS. Since there is no off the shelve solution for the development of such systems a novel, interesting, approach is proposed within this work to cope with the CIS simulation environment. The environment is based on the JADE and Matlab. A simple, but computational demanding example is provided, presenting the abilities and performance of the Research Platform. The simulation example is presented in the context of the new complex water quality model.
In this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM...
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In this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring and model predictive control purposes. The advantageous structure of PPM offers a considerable simplification of those algorithms in terms of computational burden in comparison to the nonlinear structures. Moreover, the availability of technical tools makes the analysis of the final form algorithms straightforward. An application to water quality estimation/prediction in drinking water distribution system illustrates the technology.
The Critical Infrastructure systems (CISs) have received in recent years a considerable attention due to their heavy impact on sustainable development of modern societies. Most CISs may be classified as large scale co...
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The Critical Infrastructure systems (CISs) have received in recent years a considerable attention due to their heavy impact on sustainable development of modern societies. Most CISs may be classified as large scale complex systems of network structure, influenced by strong interactions form the surrounding environment, internal and external interconnections. The later is a result of inter-CIS dependencies. The control, monitoring and control of these system is crucial to guaranty safe access to the resources distributed by the means of CIS. Among those systems the Drinking Water Distribution System (DWDS) may be found – a nonlinear dynamic carrier-load networked system. To handle these systems in a proper (robustly feasible) manner one needs to consider a nontrivial control task complimented by a set of input and state constraints. This surely points to model predictive optimal control schemes. To carry on the control a set of actuators – disinfectant booster stations – needs to be allocated within the DWDS to enable the control system to be robustly feasible. The task of optimised allocation has been addressed within this paper based on old (linear) and new (nonlinear) quality models in order to determine the impact of model structure and thus precision on the allocation results. The allocation task is formulated as a multiobjective, nonlinear/linear mixed-integer optimisation problem to be solved by a genetic algorithm (implementation of NSGA-II) due to nature of the problem. The newly obtained numerical examples are to illustrate the results. For this purpose a Chojnice (city in northern Poland) DWDS case study plant was utilised.
The paper develops a novel open loop set bounded observer for robust estimation of water quality in DWDS based on the advanced nonlinear quality dynamics model including disinfections by-products (DBPs). The observer ...
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The paper develops a novel open loop set bounded observer for robust estimation of water quality in DWDS based on the advanced nonlinear quality dynamics model including disinfections by-products (DBPs). The observer utilises a cooperativeness of the quality dynamics model and is computationally efficient, hence applicable to on-line quality monitoring. The simulation results illustrate its good and sustainable performance.
Many systems for which compressive sensing is used today are dynamical. The common approach is to neglect the dynamics and see the problem as a sequence of independent problems. This approach has two disadvantages. Fi...
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ISBN:
(纸本)9781467357159
Many systems for which compressive sensing is used today are dynamical. The common approach is to neglect the dynamics and see the problem as a sequence of independent problems. This approach has two disadvantages. Firstly, the temporal dependency in the state could be used to improve the accuracy of the state estimates. Secondly, having an estimate for the state and its support could be used to reduce the computational load of the subsequent step. In the linear Gaussian setting, compressive sensing was recently combined with the Kalman filter to mitigate above disadvantages. In the nonlinear dynamical case, compressive sensing can not be used and, if the state dimension is high, the particle filter would perform poorly. In this paper we combine one of the most novel developments in compressive sensing, nonlinear compressive sensing, with the particle filter. We show that the marriage of the two is essential and that neither the particle filter or nonlinear compressive sensing alone gives a satisfying solution.
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