The proposed adaptive control algorithm combines the recursive least-squares system identification algorithm and the generalized predictive control (GPC) design algorithm, referred to as recursive generalized predicti...
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The proposed adaptive control algorithm combines the recursive least-squares system identification algorithm and the generalized predictive control (GPC) design algorithm, referred to as recursive generalized predictive control (RGPC.) In the GPC design process, the prediction horizon and control horizon are the constants to be chosen. Two new parameters are defined to describe the effects of the prediction and control horizons and those parameters provide the effective ranges of the horizons. The RGPC algorithm adjusts the control penalty based on the stability of a closed-loop system model. A time-varying algorithm for the control penalty allows to design an aggressive controller. The multi-sampling rate algorithm is added between the system identification and the control design in order to design a higher order controller. The RGPC algorithm is applied to three different systems: a cantilevered beam, a sound enclosure. and an optical jitter suppression tesibed. (C) 2003 Published by Elsevier Ltd.
Recent low-thrust space missions have highlighted the importance of designing trajectories that are robust against uncertainties. In its complete form, this process is formulated as a nonlinear constrained stochastic ...
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Recent low-thrust space missions have highlighted the importance of designing trajectories that are robust against uncertainties. In its complete form, this process is formulated as a nonlinear constrained stochastic optimal control problem. This problem is among the most complex in control theory, and no practically applicable method to low-thrust trajectory optimization problems has been proposed to date. This paper presents a new algorithm to solve stochastic optimal control problems with nonlinear systems and constraints. The proposed algorithm uses the unscented transform to convert a stochastic optimal control problem into a deterministic problem, which is then solved by trajectory optimization methods such as differential dynamic programming. Two numerical examples, one of which applies the proposed method to low-thrust trajectory design, illustrate that it automatically introduces margins that improve robustness. Finally, Monte Carlo simulations are used to evaluate the robustness and optimality of the solution.
Series braking resistors (SeBR) offer an effective way to enhance transient stability for severe near-to-generator faults cleared with a delay. The SeBR is switched on for a short time, already during the fault. The S...
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Series braking resistors (SeBR) offer an effective way to enhance transient stability for severe near-to-generator faults cleared with a delay. The SeBR is switched on for a short time, already during the fault. The SeBR should switch on as quickly as possible after identifying the risk of losing transient stability. Then, the SeBR is switched off, and it is the decision-making algorithm that chooses the switch-off time. This paper presents an algorithm to choose the moment the SeBR switches off. The algorithm identifies the direction of a rotor motion based on changes in the square of the current and real power of the synchronous machine. The proposed algorithm is characterized by its simplicity, and is easy to implement because it uses local measurements. To develop the control algorithm, the effect of the SeBR on power angle characteristics for a fault state and post-fault states were determined. In addition, the effect of the SeBR on transient stability is explained using the equal area method. The conducted simulation tests have confirmed that the proposed SeBR control algorithm leads to longer critical clearing times, and thus it contributes to enhanced transient stability.
The number of cable-stayed bridges has been increasing worldwide, causing issues in maintaining the structural safety and integrity of bridges. The stay cable, one of the most critical members in cable-stayed bridges,...
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The number of cable-stayed bridges has been increasing worldwide, causing issues in maintaining the structural safety and integrity of bridges. The stay cable, one of the most critical members in cable-stayed bridges, is vulnerable to wind induced vibrations owing to its inherent low damping capacity. Thus, vibration mitigation of stay cables has been an important issue both in academia and practice. While a semi-active control scheme shows effective vibration reduction compared to a passive control scheme, real-world applications are quite limited because it requires complicated equipment, including for data acquisition, and power supply. This study aims to develop an Arduino-based integrated cable vibration control system implementing a semi-active control algorithm. The integrated control system is built on the low-cost, low-power Arduino platform, embedding a semi-active control algorithm. A MEMS accelerometer is installed in the platform to conduct a state feedback for the semi-active control. The Linear Quadratic Gaussian control is applied to estimate a cable state and obtain a control gain, and the clipped optimal algorithm is implemented to control the damping device. This study selects the magneto-rheological damper as a semi-active damping device, controlled by the proposed control system. The developed integrated system is applied to a laboratory size cable with a series of experimental studies for identifying the effect of the system on cable vibration reduction. The semi-active control embedded in the integrated system is compared with free and passive mode cases and is shown to reduce the vibration of stay-cables effectively.
In this paper we propose two globally stable control algorithms for robust stabilization of spacecraft in the presence of control input saturation, parametric uncertainty, and external disturbances. The control algori...
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In this paper we propose two globally stable control algorithms for robust stabilization of spacecraft in the presence of control input saturation, parametric uncertainty, and external disturbances. The control algorithms are based on variable structure control design and have the following properties: 1) fast and accurate response in the presence of bounded external disturbances and parametric uncertainty;2) explicit accounting for control input saturation;3) computational simplicity and straightforward tuning. We include a detailed stability analysis for the resulting closed-loop system. The stability proof is based on a Lyapunov-like analysis and the properties of the quaternion representation of spacecraft dynamics. It is also shown that an adaptive version of the proposed controller results in substantially simpler stability analysis and improved overall response. We also include numerical simulations to illustrate the spacecraft performance obtained using the proposed controllers.
Model predictive control (MPC) represents nowadays one of the main methods employed for process control in industry. Its strong suits comprise a simple algorithm based on a straightforward formulation and the flexibil...
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Model predictive control (MPC) represents nowadays one of the main methods employed for process control in industry. Its strong suits comprise a simple algorithm based on a straightforward formulation and the flexibility to deal with constraints. On the other hand, it can be questioned its robustness regarding model uncertainties and external noises. Thus, a lot of efforts have been spent in the past years into the search of methods to address these shortcomings. In this study, the authors propose a robust MPC controller which stems from the idea of adding robustness in the prediction phase of the algorithm while leaving the core of MPC untouched. More precisely, they consider a robust Kalman filter that has been recently introduced and they further extend its usability to feedback control systems. Overall the proposed control algorithm allows to maintain all of the advantages of MPC with an additional improvement in performance and without any drawbacks in terms of computational complexity. To test the actual reliability of the algorithm, they apply it to control a servomechanism system characterised by non-linear dynamics.
The bearing-based coordinated circumnavigation control for networked multi-agent systems with only bearing measurements in the presence of moving target is studied. First, a distributed algorithm is proposed to estima...
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The bearing-based coordinated circumnavigation control for networked multi-agent systems with only bearing measurements in the presence of moving target is studied. First, a distributed algorithm is proposed to estimate the target's velocity and the distances between the agents and the target, based on the velocity and the bearing information of the local network. Then, a distributed circumnavigation algorithm is designed to drive the agents to circumnavigate around a moving target at a desired distance. The stability of the proposed control algorithm is proven by employing the newly developed bearing rigidity theory. Finally, the simulation experiment is performed based on the Gazebo simulator to illustrate the effectiveness of the proposed circumnavigation control law.
This study presents a filter-based control scheme for an H-bridge inverter with an output inductor-capacitor filter. This approach relies only on a single output voltage measurement to reduce the system cost as well a...
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This study presents a filter-based control scheme for an H-bridge inverter with an output inductor-capacitor filter. This approach relies only on a single output voltage measurement to reduce the system cost as well as measurement noise and disturbance injected by output current and/or inductor current measurements. Also, the proposed control algorithm is robust against parameter discrepancy. A Lyapunov stability analysis is performed to demonstrate the control objective is met and that all signals in the closed loop system are stable. Experimental results demonstrate excellent voltage tracking, insensitivity to the load and system parameter variations, and low output voltage distortion as well as the stability of the system under both linear and non-linear loads.
Apparently, battery energy storage (BES), intelligent protection and power quality are considered as independent issues. These three factors can be interlinked effectively for control of microgrid through automated de...
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Apparently, battery energy storage (BES), intelligent protection and power quality are considered as independent issues. These three factors can be interlinked effectively for control of microgrid through automated demand side management (ADSM). In this context, the proposed approach may change the conventional way for microgrid operation and control giving priority to the power quality issues considering protection and BES systems. The control algorithm is implemented through fuzzy inference system based power quality monitoring index and ADSM. As a part of intelligent protection, logic table for circuit breaker (CB) coordination has been developed without/with backup for relay devices to provide ADSM. The model has been simulated using Matlab-software and validated experimentally using OPAL-RT OP4510 real-time simulator through the assessment of power quality-related parameters such as voltage, frequency, total harmonic distortion and power factor. The results are found satisfactory showing the feasibility of the proposed microgrid model.
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