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Indoor applications based on vehicular robotics require accurate, reliable and efficient localisation. In the absence of a GPS signal, an increasingly popular solution is based on fusing information from a dead reckoning system that utilises on-board sensors with absolute position data extracted from the environment. In the application considered in this paper, the information on absolute position...
The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global...
Kinetic systems form a wide nonlinear system class with good descriptive power that can efficiently be used for the dynamical modeling of non-negative models emerging not only in (bio)chemistry but in other important scientific and engineering fields as well. The directed graph structure assigned to kinetic models give us important information about the qualitative dynamical properties of the system...
The problem of model-based fault detection in the presence of both parametric uncertainty and noise is addressed in this paper. Intervals are used to represent the uncertainty in the system parameters and interval extensions of parity equations are used as adaptive threshold selectors. A proper combination in time of different (interval) parity equations, together with a robust indicator, is used...
New algorithms are presented for the computation of good upper and lower bounds on the structured singular value μ, for high order plants subject to purely real or mixed real/complex uncertainty. A geometric form of the Hahn-Banach theorem is used to develop an algorithm for computing an upper bound on μ, involving a linear program and a symmetric eigenvalue problem at each iteration. A proof of convergence...
The use of active magnetic bearings (AMB) is increasing in high-speed applications, because their low friction operation allows higher rotational speeds than the traditional bearings. The inherent instability and complexity of the AMB rotor system with high nonlinearities pose challenges to the controller design. This leads to a problem of robust design. Robustness of LQG and loop-shaping H∞ controllers...
Disassembly is a systematic method for separating a product into its constituent parts. Based on the uncertain feature of disassembly process, combined with the defined probability transmission rules of different constrain nodes, the optimal disassembly sequence is determined by the probabilistic planning method. Simultaneously, a simple example is presented to test the proposed probabilistic planning...
In the evacuation problem, departure time, route, and destination instructions are optimized to increase the effectiveness of the evacuation (i.e., more arrivals at the destinations). In literature, evacuation instructions are mostly optimized for a problem without uncertainty (the so-called nominal problem): one specific scenario regarding the system, the hazard and the evacuees is assumed. In this...
In the process of achieving enterprise value maximization, agricultural enterprises will face external and internal risks of uncertainty. The premise of risk control is to conduct a risk assessment. The key of risk assessment is to establish and optimize the evaluation index system. In this paper, we use factor analysis to optimize the evaluation index system of agricultural enterprises risk. The...
Batch chemical processes have become significant in chemical manufacturing. Recently, economy globalization has resulted in growing worldwide competitions in traditional chemical process industry. In order to increase competition, reduce production costs and meet safety requirements, it is necessary to implement varies optimization methods and advanced control strategies. The goal of this paper is...
Probability intervals and random sets are special cases of interval-valued probability measures. In this paper, we analyze the relationship between a probability interval and a random set. We provide a construction of a random set for a given probability interval. This construction is easier to apply than an existence construction.
As an important type of reliability optimization problems, the component assignment problem (CAP) is to find the optimal arrangement of n available components to n positions of a system such that the resulting system reliability is maximized. The CAP is a combinatorial problem in nature and needs effective solution methods. The importance measures of components, e.g., the Birnbaum importance (BI),...
Many sequential decision making problems require an agent to balance exploration and exploitation to maximise long-term reward. Existing policies that address this tradeoff typically have parameters that are set a priori to control the amount of exploration. In finite-time problems, the optimal values of these parameters are highly dependent on the problem faced. In this paper, we propose adapting...
This paper considers finite-horizon optimal control for multi-agent systems subject to additive Gaussian-distributed stochastic disturbance and a chance constraint. The problem is particularly difficult when agents are coupled through a joint chance constraint, which limits the probability of constraint violation by any of the agents in the system. Although prior approaches can solve such a problem...
This work considers a robust fault detection and isolation (FDI) problem for linear discrete-time systems subject to faults, bounded additive disturbances and norm-bounded uncertainties. We propose a receding horizon estimation procedure (which is a dual scheme to Model Predictive Control (MPC)) to solve FDI problems in which the upper and lower bounds on the faults are computed by using a system...
The method by which individual decisions are combined in cooperative cognitive radio networks is crucial to minimising the overall probabilities of false alarm and missed detection. In this paper, general expressions for these probabilities are derived for a double threshold energy detector-based network, and an analytical solution for the optimal value of voting rule is found so that the overall...
We revisit robust complex- and mixed-μ synthesis problems based on upper bounds and show that they can be recast as specially structured controller design programs. The proposed reformulations suggest a streamlined handling of μ synthesis problems using recently developed (local) nonsmooth optimization methods where both scalings or multipliers and a controller of given structure are obtained simultaneously...
Influence diagrams (IDs) are compact and intuitive models for representation and analysis of decision problems under uncertainty. Influence diagrams have always been imposed on no-forgetting and regularity constraints which guarantee that global optimal strategy can be solved successively by local computations on each decision nodes according to a solution ordering. However, it is difficult to solve...
Motivated by biological applications, this paper addresses the problem of network reconstruction from data. Previous work has shown necessary and sufficient conditions for network reconstruction of noise-free LTI systems. This paper assumes that the conditions for network reconstruction have been met but here we additionally take into account noise and unmodelled dynamics (including nonlinearities)...
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