The paper describes a substantial extension of Norm Optimal Iterative Learning control (NOILC) that permits tracking of a class of finite dimensional reference signals whilst simultaneously minimizing a quadratic cost...
The paper describes a substantial extension of Norm Optimal Iterative Learning control (NOILC) that permits tracking of a class of finite dimensional reference signals whilst simultaneously minimizing a quadratic cost function. Motivated by practical problems in automation and control, this enables point-to-point motion tasks to be performed whilst reducing effects such as payload spillage, vibration tendencies and actuator wear. Solutions combine feedforward and feedback actions, and are experimentally tested using a robotic arm.
The design, characterization and control of a novel 2-DOF MEMS nanopositioner is presented, with Z-shaped electrothermal actuators being used to position the device's central stage. Whereas the more commonly-used ...
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The design, characterization and control of a novel 2-DOF MEMS nanopositioner is presented, with Z-shaped electrothermal actuators being used to position the device's central stage. Whereas the more commonly-used V-shaped electrothermal actuator only allows displacements in one direction, the design of the Z-shaped beams used in the presented device allows two actuators to be coupled back-to-back to achieve bidirectional motion along each of the two axes. Testing of the device shows that stage displacements in excess of ϕ5 μm are achievable for both the x and y axes. The device features integrated displacement sensors based on polysilicon electrothermal heaters, which are supplied with an electrical bias voltage that results in Joule heating. The resistance of each heater varies depending on the position of the central stage, with two heaters being used per axis in a differential configuration. The displacement measurements are utilized as part of an implemented closed-loop control scheme that uses both feedforward and feedback mechanisms based on the principle of internal model control. Experimental testing shows that the use of the controller enhances the static and dynamic performance of the system, with particular improvements being seen in the device's reference tracking, response time and cross-coupling rejection.
The increased penetration of renewable energy sources to the network highlights the necessity of constructing stochastic variants of the standard unit commitment and reserve scheduling problems. Earlier approaches to ...
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ISBN:
(纸本)9781479901890
The increased penetration of renewable energy sources to the network highlights the necessity of constructing stochastic variants of the standard unit commitment and reserve scheduling problems. Earlier approaches to such problems are either restricted to ad-hoc methodologies (at the expense of a suboptimal solution), or lead to computationally intractable formulations. In this paper we provide a unified framework to deal with such planning problems for systems with uncertain generation, while providing a-priori probabilistic certificates for the robustness properties of the resulting solution. Our methodology is based on a mixture of randomized and robust optimization and leads to a tractable problem formulation. To illustrate the performance of the proposed methodology we apply it to the IEEE 30-bus network, and compare it by means of Monte Carlo simulations against an algorithm based on a deterministic variant of the unit commitment problem.
This paper deals with the problem of reserve scheduling for power systems with wind power generation, and proposes a new set-up that incorporates an AC Optimal Power Flow (AC OPF) formulation. The AC OPF problem is no...
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This paper deals with the problem of reserve scheduling for power systems with wind power generation, and proposes a new set-up that incorporates an AC Optimal Power Flow (AC OPF) formulation. The AC OPF problem is nonconvex and in general hard to solve. Here we propose an approach building on convex relaxations of the AC OPF problems and discuss a modification that we believe has certain advantages when combined with the reserve scheduling formulation. Numerical simulations suggest that the proposed relaxation technique results in a feasible solution for the exact problem. Using the proposed modification of the AC OPF problem, we focus on systems with uncertain generation and formulate a chance constrained optimization problem to determine the minimum cost of production and reserves. Due to the complex structure of the resulting problem, we use a heuristic procedure to solve it numerically. This is achieved following a sampling based methodology. The proposed algorithm is applied to the IEEE-30 bus network and is compared against its DC power flow counterpart by means of Monte Carlo simulations.
The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times s...
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Recently, a finite horizon minimum variance control problem was proposed using feedback over a Gaussian communication channel. Because only the terminal state is penalized, it was shown that linear communication and c...
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ISBN:
(纸本)9781479901890
Recently, a finite horizon minimum variance control problem was proposed using feedback over a Gaussian communication channel. Because only the terminal state is penalized, it was shown that linear communication and control strategies are optimal and achieve the information theoretic minimum cost. However, because the transient state is not penalized, the transient behavior can be poor. In the present paper, we show that if there is at most one open loop unstable plant pole, then the transient response will remain bounded as the control horizon tends to infinity, and will approach a value determined by the solution to a certain algebraic Riccati equation.
Several sources of error exist in lidar measurements for feedforward control of wind turbines including the ability to detect only radial velocities, spatial averaging, and wind evolution. This paper investigates anot...
Several sources of error exist in lidar measurements for feedforward control of wind turbines including the ability to detect only radial velocities, spatial averaging, and wind evolution. This paper investigates another potential source of error: the upstream induction zone. The induction zone can directly affect lidar measurements and presents an opportunity for further decorrelation between upstream wind and the wind that interacts with the rotor. The impact of the induction zone is investigated using the combined CFD and aeroelastic code SOWFA. Lidar measurements are simulated upstream of a 5 MW turbine rotor and the true wind disturbances are found using a wind speed estimator and turbine outputs. Lidar performance in the absence of an induction zone is determined by simulating lidar measurements and the turbine response using the aeroelastic code FAST with wind inputs taken far upstream of the original turbine location in the SOWFA wind field. Results indicate that while measurement quality strongly depends on the amount of wind evolution, the induction zone has little effect. However, the optimal lidar preview distance and circular scan radius change slightly due to the presence of the induction zone.
Considering a constrained discrete-time linear time-varying system, this paper proposes a novel approach which aims at achieving high performance and enlarging the domain of attraction with respect to any particular l...
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ISBN:
(纸本)9781479901890
Considering a constrained discrete-time linear time-varying system, this paper proposes a novel approach which aims at achieving high performance and enlarging the domain of attraction with respect to any particular linear controller. The main idea of the paper is to use a linear decomposition principle together with a parameter dependent Lyapunov function. At each time instant a quadratic programming problem is solved on-line. Proofs of recursive feasibility and asymptotic stability are given.
This paper covers a case study of broken bar detection for 3.15 MW motor in a thermal power plant application. The motor current is measured in one phase. Feature extraction is based on transient and steady state anal...
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This paper covers a case study of broken bar detection for 3.15 MW motor in a thermal power plant application. The motor current is measured in one phase. Feature extraction is based on transient and steady state analysis. Hilbert and Wavelet transforms are used to extract broken bar features. To discuss rotor condition in time domain skewness and kurtosis of current envelope are also considered. Low shaft-load conditions are present. In case of high-voltage, high-power induction motor reliable broken bar detection is possible when contemporary digital signal processing techniques are used.
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