This technical note gives a new solution to the output feedback H 2 problem for quadratically invariant communication delay patterns. A characterization of all stabilizing controllers satisfying the delay constraints...
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This technical note gives a new solution to the output feedback H 2 problem for quadratically invariant communication delay patterns. A characterization of all stabilizing controllers satisfying the delay constraints is given and the decentralized H 2 problem is cast as a convex model matching problem. The main result shows that the model matching problem can be reduced to a finite-dimensional quadratic program. A recursive state-space method for computing the optimal controller based on vectorization is given.
control of robot locomotion profits from the use of pre-planned trajectories. This paper presents a way to generalize globally optimal and dynamically consistent trajectories for cyclic bipedal walking. A small task-s...
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control of robot locomotion profits from the use of pre-planned trajectories. This paper presents a way to generalize globally optimal and dynamically consistent trajectories for cyclic bipedal walking. A small task-space consisting of stride-length and step time is mapped to spline parameters which fully define the optimal joint space motion. The paper presents the impact of different machine learning algorithms for velocity and torque optimal trajectories with respect to optimality and feasibility. To demonstrate the usefulness of the trajectories, a control approach is presented that allows general walking including transitions between points in the task-space.
This paper presents a non-linear, data driven Adaptive Network based Fuzzy Inference System (ANFIS) modeling of a Two Tanks Hydraulic System (TTHS). The paper also addresses the design of a Type 1 Fuzzy Logic controll...
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ISBN:
(纸本)9781467366991
This paper presents a non-linear, data driven Adaptive Network based Fuzzy Inference System (ANFIS) modeling of a Two Tanks Hydraulic System (TTHS). The paper also addresses the design of a Type 1 Fuzzy Logic controller optimized with Genetic Algorithms (GA). The controller was designed and tested in simulation with the obtained ANFIS model and validated in real-time with the actual TTHS. Obtained model shows an accurate and adequate description of the real system, useful for many applications that require a non-linear functioning representation of the TTHS. The designed controller also demonstrates excellent performance by being able to follow diverse shaped references. This work successfully demonstrates the utility of soft-computing techniques in their application to real world industrial complex systems.
In this paper, an approach is proposed for planning distribution networks in which the placement of distribution transformer is optimally planned. The size, number, and placement of distribution transformers are optim...
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ISBN:
(纸本)9781467380416
In this paper, an approach is proposed for planning distribution networks in which the placement of distribution transformer is optimally planned. The size, number, and placement of distribution transformers are optimally determined in order to improve system reliability and to minimize the losses under load growth. An objective function is constituted, composed of the investment cost, maintenance cost, loss cost, and reliability cost. The reliability worth is not usually considered in the optimization of the distribution substation placement. However, it may be effective on the planning problem. The proposed approach is applied to a test system consisting of 42 electric load points. It is observed that the considering reliability in the planning approach reduces the total cost of the distribution transformer placement. However, the associated investment cost is increased but the reliability cost is more decreased.
This paper presents a method to control vehicular platoons in an event-triggered fashion. Therefore, every vehicle broadcasts its position and velocity information only at discrete event times. These events are determ...
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ISBN:
(纸本)9781479917730
This paper presents a method to control vehicular platoons in an event-triggered fashion. Therefore, every vehicle broadcasts its position and velocity information only at discrete event times. These events are determined by a trigger rule only depending on the agents state and on time. Two control architectures are considered. The first one, called symmetric bidirectional, uses information of the front and back neighbor in the control law. The architecture is analyzed with a linear controller and it is shown that the state error converges to an adjustable region around the origin. In earlier work it is suggested to use a nonlinear controller if solely information from the front neighbor is available. Thus, a nonlinear event-triggered predecessor-following control is developed and analyzed additionally. Not only bounds are given for the state of each vehicle, but it is also shown that the converging input converging state property holds. In both cases we guarantee the existence of a lower bound on the inter-event times. The benefits of both strategies are verified in numerical simulations.
In this paper, we look to address the problem of estimating the dynamic direction of arrival (DOA) of a narrowband signal impinging on a sensor array from the far field. The initial estimate is made using a Bayesian c...
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ISBN:
(纸本)9781479974047
In this paper, we look to address the problem of estimating the dynamic direction of arrival (DOA) of a narrowband signal impinging on a sensor array from the far field. The initial estimate is made using a Bayesian compressive sensing (BCS) framework and then tracked using a Bayesian compressed sensing Kalman filter (BCSKF). The BCS framework splits the angular region into N potential DOAs and enforces a belief that only a few of the DOAs will have a non-zero valued signal present. A BCSKF can then be used to track the change in the DOA using the same framework. There can be an issue when the DOA approaches the endfire of the array. In this angular region current methods can struggle to accurately estimate and track changes in the DOAs. To tackle this problem, we propose changing the traditional sparse belief associated with BCS to a belief that the estimated signals will match the predicted signals given a known DOA change. This is done by modelling the difference between the expected sparse received signals and the estimated sparse received signals as a Gaussian distribution. Example test scenarios are provided and comparisons made with the traditional BCS based estimation method. They show that an improvement in estimation accuracy is possible without a significant increase in computational complexity.
Most nonlinear modelling approaches focus on solving a model selection problem with complete data, and in many cases original data are pre-processed with some nonlinear transforms such as Box-Tidwell and fractional po...
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ISBN:
(纸本)9781479987023
Most nonlinear modelling approaches focus on solving a model selection problem with complete data, and in many cases original data are pre-processed with some nonlinear transforms such as Box-Tidwell and fractional polynomial transformation. Often these approaches can lead to models that are better than traditional models (for example, logistic model and quadratic model). However, in the case of missing data, it is not easy to predict the relationship between the predictor and dependent variables;traditional nonlinear models in some cases of missing data analysis give poor results. This paper explains nonlinear model selection techniques for missing data. It includes an overview of nonlinear model selection with complete data, and provides accessible descriptions of Box-Tidwell and fractional polynomial methods for model selection. In particular, this paper focuses on a fractional polynomial method for nonlinear modelling in cases of missing data and presents analysis examples to illustrate performance of the method.
A central question in the analysis and operation of power networks is the feasibility of a unique high-voltage solution to the power flow equations satisfying operational constraints. For planning, monitoring, and con...
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ISBN:
(纸本)9781479978878
A central question in the analysis and operation of power networks is the feasibility of a unique high-voltage solution to the power flow equations satisfying operational constraints. For planning, monitoring, and contingency analysis in transmission networks, the high-voltage solution of these nonlinear equations can be constructed only numerically or roughly approximated using a linear DC power flow. In this work we analytically study the solvability of the nonlinear decoupled reactive power flow equations, and present a solvability condition relating the existence of a unique high-voltage solution to the spatial distribution of loading and the effective impedances between load buses. We validate the accuracy and applicability of our results through standard power network test cases.
In this paper we study the problem of computing the (family of) reduced order model(s) that satisfy the following properties the systems match the moments of the given to be reduced system and the same property holds ...
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In this paper we study the problem of computing the (family of) reduced order model(s) that satisfy the following properties the systems match the moments of the given to be reduced system and the same property holds for the first order derivatives of the corresponding transfer functions. We prove that such a model exists and compute it. We also study the problem of moment matching for the state-space representations of the first order derivatives of rational transfer functions. Finally, we show that the model that matches the moment of both the given system and its first order derivative is a member of the family of reduced order models whose first order derivatives achieve moment matching.
This paper provides experimental verification of a fault isolation sequence in a DC Zonal electrical System. Three electrical zones consisting of phase controlled rectifier interfaces to medium voltage AC distribution...
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This paper provides experimental verification of a fault isolation sequence in a DC Zonal electrical System. Three electrical zones consisting of phase controlled rectifier interfaces to medium voltage AC distribution, two DC distribution buses and downstream converters, inverters feeding loads are energized and bolted faults are applied to various locations. The Fault Isolation and Reconfiguration approach utilizes no load switches for fault isolation aided by de-energization of the affected buses. Three electromechanical no load switches in a single assembly are utilized at the interface between electrical zones. The instantaneous peak fault currents were captured at each switch and sent to adjacent modules over a Ethernet-based Local Area Network in order to locate and isolate the fault to the nearest bus segment. Experimental results show that in most cases full output capacity was restored autonomously. Loss of communications scenarios are tested showing limited power restoration.
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