Time delay and sampling appear in many industrial systems. It is irrefutable that applying measurement delay with controls can cause the sampling of control laws with the delay in the behavior of ...nonlinear control systems. As a result, in this paper, the stability of nonlinear time varying switched system with time delay in the input and the states of the system is studied in two modes by a new Lyapunov Krasovskii functional (LKF). Firstly, if all subsystems of the proposed nonlinear switched system with time delay are stable. Then, if some of the subsystems of the proposed switched system are unstable. This paper is organized in two steps. In the first step, the upper bound for the time delay under sufficient conditions in the nonlinear systems with time delay in input and states is obtained. In this step, the Uniformly Globally Asymptotic Stability is proved for nonlinear systems with the presence of time delay. In the second step, with a proper Lyapunov Krasovskii functional, the global exponential stability of the proposed switched system is proved. Also, finally a proper observer is designed for our proposed switched system in two stable and unstable modes.
This work considers the problem of decentralized control of inverter-based
ac
micro-grid in different operation modes. The main objectives are to (i) design decentralized frequency and voltage ...controllers, to gather with power sharing, without information exchange between microsources (ii) design passive dynamic controllers which ensure stability of the entire microgrid system (iii) capture nonlinear, interconnected and large-scale dynamic of the micro-grid system with meshed topology as a port-Hamiltonian formulation (iv) expand the property of shifted-energy function in the context of decentralized control of
ac
micro-grid (v) analysis of system stability in large signal point of view. More precisely, to deal with nonlinear, interconnected and large-scale structure of micro-grid systems, the port-Hamiltonian formulation is used to capture the dynamic of micro-grid components including microsource, distribution line and load dynamics as well as interconnection controllers. Furthermore, to deal with large signal stability problem of the microgrid system in the grid-connected and islanded conditions, the shifted-Hamiltonian energy function is served as a storage function to ensure incremental passivity and stability of the microgrid system. Moreover, it is shown that the aggregating of the microgrid dynamic and the decentralized controller dynamics satisfies the incremental passivity. Finally, the effectiveness of the proposed controllers is evaluated through simulation studies. The different scenarios including grid-connected and islanded modes as well as transition between both modes are simulated. The simulation conforms that the decentralized control dynamics are suited to achieve the desired objective of frequency synchronization, voltage control and power sharing in the grid-connected and islanded modes. The simulation results demonstrate the effectiveness of the proposed control strategy.
► A combined neural network and watershed algorithm is used for liver segmentation. ► Neural networks are used to adjust the parameters of algorithm automatically. ► The algorithm solves the ...oversegmentation problem of the watershed transformation. ► The proposed algorithm can be generalized for the extraction of other regions. ► Experiments using the dataset show positive results for the proposed algorithm.
Precise liver segmentation in abdominal MRI images is one of the most important steps for the computer-aided diagnosis of liver pathology. The first and essential step for diagnosis is automatic liver segmentation, and this process remains challenging. Extensive research has examined liver segmentation; however, it is challenging to distinguish which algorithm produces more precise segmentation results that are applicable to various medical imaging techniques. In this paper, we present a new automatic system for liver segmentation in abdominal MRI images. The system includes several successive steps. Preprocessing is applied to enhance the image (edge-preserved noise reduction) by using mathematical morphology. The proposed algorithm for liver region extraction is a combined algorithm that utilizes MLP neural networks and watershed algorithm. The traditional watershed transformation generally results in oversegmentation when directly applied to medical image segmentation. Therefore, we use trained neural networks to extract features of the liver region. The extracted features are used to monitor the quality of the segmentation using the watershed transform and adjust the required parameters automatically. The process of adjusting parameters is performed sequentially in several iterations. The proposed algorithm extracts liver region in one slice of the MRI images and the boundary tracking algorithm is suggested to extract the liver region in other slices, which is left as our future work. This system was applied to a series of test images to extract the liver region. Experimental results showed positive results for the proposed algorithm.
In this paper, an optimal solution to the eigen-structure problem that dramatically reduces the control effort required for a multi-input multi-output (MIMO) multirate system is proposed. This ...technique not only minimize the amplitude of state transmission and control signal changes but also reduce the sensitivity to the effects of internal sampling in multirate MIMO systems results from interactions of the model order reduction. In this study, a constrained eigen-structure method with nonlinear constraints is used. The novelty of this study is that by using partial derivatives, a gain optimization process to optimize the nonlinearly constrained eigen-structure method is proposed. First, this method is explained, and then the desired method is applied for optimization operations, and finally, the results will be shown with a numerical example and a simulation.
The main purpose of this study is to propose a method to achieve optimal response and performance of the multi rate systems in existence of different sampling rates and to avoid data losses in such ...systems. In this paper, a new approach based on the multi-rate digital system is proposed. Based on this method, we will be able to maintain optimal performance of these systems without losing data, in addition to establishing connections between subsystems with different sampling rates. By the proposed method, not only the effect of different sampling rates in multi-rate systems is ignored, but also, we can connect subsystems with different rate operations without compromising system performance and data loss which simplified system design and sensor selection by the digital system designers. This means the designer can choose any sensor without concerning about the sampling rate and the operation rate of the system and matching them together. Finally, a guided missile with different sampling rates between the seeker, autopilot, guidance law and the output feedback are simulated and its effective performance in pursuit, hitting and smooth motion toward the target in a motion scenario is shown.
The main purpose of this study is to propose a method to achieve optimal response and performance of the multi rate systems in existence of different sampling rates and to avoid data losses in such ...systems. In this paper, a new approach based on the multi-rate digital system is proposed. Based on this method, we will be able to maintain optimal performance of these systems without losing data, in addition to establishing connections between subsystems with different sampling rates. By the proposed method, not only the effect of different sampling rates in multi-rate systems is ignored, but also, we can connect subsystems with different rate operations without compromising system performance and data loss which simplified system design and sensor selection by the digital system designers. This means the designer can choose any sensor without concerning about the sampling rate and the operation rate of the system and matching them together. Finally, a guided missile with different sampling rates between the seeker, autopilot, guidance law and the output feedback are simulated and its effective performance in pursuit, hitting and smooth motion toward the target in a motion scenario is shown.
One of the major tools for power system operators is optimal power flow (OPF) which is an important tool in both planning and operating stages, designed to optimize a certain objective over power ...network variables under certain constraints. Without doubt one of the simple but powerful optimization algorithms in the field of evolutionary optimization is imperialist competitive algorithm (ICA); outperforming many of the already existing stochastic and direct search global optimization techniques. The original ICA method often converges to local optima. In order to avoid this shortcoming, we propose a new method that profits from teaching learning algorithm (TLA) to improve local search near the global best and a series of modifications is purposed to the assimilation policy rule of ICA in order to further enhance algorithm’s rate of convergence for achieving a better solution quality. This paper investigates the possibility of using recently emerged evolutionary-based approach as a solution for the OPF problem which is based on hybrid modified ICA (MICA) and TLA (MICA–TLA) for optimal settings of OPF control variables. The performance of this approach is studied and evaluated on the standard IEEE 30-bus and IEEE 57-bus test systems with different objective functions and is compared to methods reported in the literature. The hybrid MICA–TLA provides better results compared to the original ICA, TLA, MICA, and other methods reported in the literature as demonstrated by simulation results.
•A novel hybrid algorithm.•Hybrid MICA–TLA has been offered as a novel solution for solving OPF problem.•Hybrid MICA–TLA was successfully implemented.
Combined heat and power units are playing an ever increasing role in conventional power stations due to advantages such as reduced emissions and operational cost savings. This paper investigates a ...more practical formulation of the complex non-convex, non-smooth and non-linear multi-objective dynamic economic emission dispatch that incorporates combined heat and power units. Integrating these types of units, and their power ramp constraints, require an efficient tool to cope with the joint characteristics of power and heat. Unlike previous approaches, the spinning reserve requirements of this system are clearly formulated in the problem. In this way, a new multi-objective optimisation based on an enhanced firefly algorithm is proposed to achieve a set of non-dominated (Pareto-optimal) solutions. A new tuning parameter based on a chaotic mechanism and novel self adaptive probabilistic mutation strategies are used to improve the overall performance of the algorithm. The numerical results demonstrate how the proposed framework was applied in real time studies.
► Investigate a practical formulation of the DEED (Dynamic Economic Emission Dispatch). ► Consider combined heat and power units. ► Consider power ramp constraints. ► Consider the system spinning reserve requirements. ► Present a new multi-objective optimization firefly.
AbstractThe closed-loop performance of an inertial stable platform (ISP) affects the operation of navigation in moving objects. In this paper, the issue of high-performance control of ISP is ...discussed. By proposing a novel backstepping controller, the ISP plant with external stochastic disturbance, unknown dynamics, and actuator saturation is stabilized and regulated to the desired reference. Since unfamiliar terms appear in the practical ISP plant, a novel adaptive neural network model is suggested. To deal with the stochastic disturbance and modeling error, the stochastic bounded stability scheme is considered. Moreover, the practical problem of actuator saturation is involved in the design procedure. The suggested robust controller needs only one scalar adaptation law for all of the neural network gains. The virtual command inputs are propagated into a first-order filter to eliminate the conventional procedure of calculating the time-derivative terms. Eventually, a novel control technique is suggested for a nonlinear three Degrees of Freedom (3-DOF) ISP plant case study. Results illustrate the high performance of the robust controller in the presence of stochastic disturbance and input saturation.
In this study, an efficient and smart fuzzy logic controller (FLC) is designed for charging/discharging (C/D) nodes of plug-in electric vehicles (PEVs). The designed controller controls the amount of ...power to be compensated by these nodes in order to meet the required peak shaving and voltage flattening. The main focus of this work is to practically coordinate the mobile PEVs in a multiobjective security constrained dynamic optimal power flow (OPF) problem that aims at simultaneously minimizing the operation cost and emission over 24-h time horizons. In the formulation of the problem, nonsmooth, nonconvex, and nonlinear natures of valve-point effects, multifuel options, prohibited zones, and ac power flow equations are also considered. This complex problem needs a robust, fast, and powerful optimization algorithm, which is able to extract the Pareto-optimal surface (POS). Hence, a new improved black hole (IBH) algorithm is proposed with a new formulation for updating particles to allow a greater exploration and appropriate exploitation of the search space. The proposed framework is applied on IEEE 118-bus test system incorporating several aggregated PEVs to show its efficiency and ability.
PDF
