This paper proposes a new actuator-fault detection and isolation (FDI) strategy for closed-loop discrete time-invariant systems by using invariant sets and tubes. In this approach, invariant sets are used for fault de...
This paper proposes a new actuator-fault detection and isolation (FDI) strategy for closed-loop discrete time-invariant systems by using invariant sets and tubes. In this approach, invariant sets are used for fault detection (FD) and the establishment of FDI conditions, while the tubes are generated for fault isolation (FI) at transient state. Comparing with the existing set-theoretic FDI techniques, the advantage of this approach consists in that it exhibits a balance between the conservativeness of FDI conditions, the fast FI response and the computational complexity. The effectiveness of the proposed technique is illustrated by a numerical example.
In this paper we propose a robust self-triggered model predictive control algorithm for linear systems with additive bounded disturbances and hard constraints on the inputs and state. In self-triggered control, at eve...
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In this paper we propose a robust self-triggered model predictive control algorithm for linear systems with additive bounded disturbances and hard constraints on the inputs and state. In self-triggered control, at every sampling instant the time until the next sampling instant is computed online based on the current state of the system. The goal is to achieve a low average sampling rate, thereby minimizing communication in the control system and possibly reducing the number of control updates as is required in sparse control applications. Naturally, and intentionally, our approach leads to long spans of time in which the plant is controlled in an open-loop fashion. Especially for unstable plants or large disturbances this necessitates taking into account the disturbance characteristics in the design of the control law in order to prevent constraint violation in the closed-loop system. We use constraint tightening methods as proposed in Tube Model Predictive control to guarantee robust constraint satisfaction. The self-triggered controller is shown to stabilize a robust invariant set in the state space for the closed-loop system.
A novel protection scheme for two-phase faults in power distribution system with neutral ungrounded is presented. The feasibility of tripping single-phase circuit when a phase-tophase or two-phase-to-ground fault occu...
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ISBN:
(纸本)9781849198349
A novel protection scheme for two-phase faults in power distribution system with neutral ungrounded is presented. The feasibility of tripping single-phase circuit when a phase-tophase or two-phase-to-ground fault occurs is studied with induction motor loads as the focus. The paper at first analyses the effect of a induction motor runs with one phase cut off theoretically. And then a real power distribution system model with 110kV, 35kV and 6kV voltage levels is built in PSCAD/EMTDC. Three feasibility criteria are proposed for motors in continuous operation with single-phase opened. At last, the novel protection scheme is testified in simulation with protection time and reclosing time as variables respectively. The results verify that the scheme is feasible and power supply reliability is improved.
In this paper we consider the minimization of ℓ 0 -regularized nonlinear optimization problems, where the objective function is the sum of a smooth convex term and the ℓ 0 quasi-norm of the decision variable. We intr...
In this paper we consider the minimization of ℓ 0 -regularized nonlinear optimization problems, where the objective function is the sum of a smooth convex term and the ℓ 0 quasi-norm of the decision variable. We introduce the class of coordinatewise minimizers and prove that any point in this class is a local minimum for our ℓ 0 -regularized problem. Then, we devise a random proximal alternating minimization method, which has a simple iteration and is suitable for solving this class of optimization problems. Under convexity and coordinatewise Lipschitz gradient assumptions, we prove that any limit point of the sequence generated by our new algorithm belongs to the class of coordinatewise minimizers almost surely. We also show that the state estimation of dynamical systems with corrupted measurements can be modeled in our framework. Numerical experiments on state estimation of power systems, using IEEE bus test case, show that our algorithm performs favorably on solving such problems.
In this paper, an improved algorithm for actuator-fault detection and isolation (FDI) using a bank of interval observers is presented, where each interval observer matches one considered system mode. In this approach,...
In this paper, an improved algorithm for actuator-fault detection and isolation (FDI) using a bank of interval observers is presented, where each interval observer matches one considered system mode. In this approach, interval observers and invariant sets are simultaneously used for FDI. Under a collection of improved FDI conditions, this new algorithm can detect and isolate the considered actuator faults. At the end of this paper, a circuit example is used to illustrate the effectiveness of the proposed strategy.
The circuit principle of construction of the low-speed selective amplifiers (SA) of microwave range on the energy-efficient converters "voltage-current" is developed. The proposed solution provides the possi...
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The circuit principle of construction of the low-speed selective amplifiers (SA) of microwave range on the energy-efficient converters "voltage-current" is developed. The proposed solution provides the possibility of cascade connection of several SA without additional loops of matching of the static mode. The principle of symmetry of the frequency-dependent feedback loop underlies in the circuit construction. The reviewed architecture of SA in contrast with the well-known ones reduces the asymptotic attenuation not only in the traditional high-frequency range but also in low-frequency one without a separating capacitor. This effect is achieved by using CMOS transistors in the input differential stage. The results of the mathematical analysis and simulation of SA on 0.25 um SiGe process are given. Shown the possibility of parametric optimization the sensitivity functions of quasi-resonance frequency and Q-factor SA instability parameters of passive elements.
Nowadays, the overhead expenses are a significant component of the manufacturing cost. The expenditures occasioned by running the shop floor energy system are one of the most important among the overhead expenses. How...
Nowadays, the overhead expenses are a significant component of the manufacturing cost. The expenditures occasioned by running the shop floor energy system are one of the most important among the overhead expenses. However, the manufacturing process optimization actually does not take into account these expenses. More than that, the expenses for running the shop floor energy system are not constant, varying after the external environment seasonal conditions, and they are depending on several issues, like the building's energetic exchange with its environment, or the loading degree of the machine tools from the shop floor. This paper approaches the relation between the shop floor energy system expenditures, on one hand, and the manufacturing process optimality, on the other hand. A case study, revealing the influence of the shop floor energy system on the manufacturing cost-optimal solution is also included.
This paper investigates convergence properties of scalable algorithms for nonconvex and structured optimization. We consider a method that is adapted from the classic quadratic penalty function method, the Alternating...
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This paper investigates convergence properties of scalable algorithms for nonconvex and structured optimization. We consider a method that is adapted from the classic quadratic penalty function method, the Alternating Direction Penalty Method (ADPM). Unlike the original quadratic penalty function method, in which single-step optimizations are adopted, ADPM uses alternating optimization, which in turn is exploited to enable scalability of the algorithm. A special case of ADPM is a variant of the well known Alternating Direction Method of Multipliers (ADMM), where the penalty parameter is increased to infinity. We show that due to the increasing penalty, the ADPM asymptotically reaches a primal feasible point under mild conditions. Moreover, we give numerical evidence that demonstrates the potential of the ADPM for computing local optimal points when the penalty is not updated too aggressively.
We address the weight-balancing problem for a distributed system whose components (nodes) can exchange information via interconnection links (edges) that form an arbitrary, possibly directed, communication topology (d...
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We address the weight-balancing problem for a distributed system whose components (nodes) can exchange information via interconnection links (edges) that form an arbitrary, possibly directed, communication topology (digraph). A weighted digraph is balanced if, for each node, the sum of the weights of the edges outgoing from that node is equal to the sum of the weights of the edges incoming to that node. Weight-balanced digraphs play a key role in a variety of applications, such as coordination of groups of robots, distributed decision making, and distributed averaging which is important for a wide range of applications in signal processing. We propose a distributed algorithm for solving the weight balancing problem in a minimum number of iterations, when the weights are nonnegative real numbers. We also provide examples to corroborate the proposed algorithm.
We present a mathematical programming-based method for optimal control of discrete-time dynamical systems subject to temporal logic task specifications. We use linear temporal logic (LTL) to specify a wide range of pr...
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We present a mathematical programming-based method for optimal control of discrete-time dynamical systems subject to temporal logic task specifications. We use linear temporal logic (LTL) to specify a wide range of properties and tasks, such as safety, progress, response, surveillance, repeated assembly, and environmental monitoring. Our method directly encodes an LTL formula as mixed-integer linear constraints on the continuous system variables, avoiding the computationally expensive processes of creating a finite abstraction of the system and a Büchi automaton for the specification. In numerical experiments, we solve temporal logic motion planning tasks for high-dimensional (10+ continuous state) dynamical systems.
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