Sharif Digital Repository

Optimal control of large-scale uncertain dynamic systems with time delays in states is considered in this paper. For this purpose, a two-level strategy is proposed to decompose the large-scale system into several interconnected subsystems at the first level. Then optimal control inputs are obtained by minimization of convex performance indices in presence of uncertainties, in the form of states and interactions feedback. The solution is achieved by bounded data uncertainty problems, where the uncertainties are only needed to be bounded and it is not required to satisfy the so-called 'matching conditions'. At the second level, a simple substitution-type interaction prediction method is used... 

In large-scale power systems, classical centralized control approaches may fail due to geographically distribution of information and decentralized controllers result in sub-optimal solution for load-frequency control (LFC) problems. In this paper, a two-level structure is presented to obtain optimal solution for LFC problems and also reduce the computational complexity of centralized controllers. In this approach, an interconnected multi-area power system is decomposed into several sub-systems (areas) at the first-level. Then an optimization problem in each area is solved separately, with respect to its local information and interaction signals coming from other areas. At the second-level,... 

In this study, a hierarchical optimal robust controller is presented for the power system load-frequency control problem. In this approach, the multi-area power system is first decomposed into several sub-systems (areas). Then by using a two-level control strategy, the overall optimal solution is obtained. At the first level, the optimal control of each area is obtained with respect to local information and also considering interactions coming from other areas. At the second level, by using a coordination strategy, the local controllers will converge to global solution and optimal robust controller is achieved. This approach is applicable to both single-area and multi-area interconnected... 

This paper is concerned with the disturbance attenuation problem of fuzzy large-scale systems which consist of N interconnected subsystems which are represented by Takagi-Sugeno fuzzy models. Using Lyapunov function and linear matrix inequalities (LMIs), a criterion is proposed to have a prescribed level of disturbance attenuation. A numerical example is given to illustrate the control design procedure and its effectiveness  

A repeated inflation-unemployment game within the linear-quadratic frame-work of Barro and Gordon is studied assuming that the government would like to cheat optimally and the finite heterogeneous population of private agents attempts to learn the government's targets using a reinforcement learning algorithm. Private agents are heterogeneous in their initial expectations of inflation rate but are assumed to utilize an identical anticipatory reinforcement learning process, namely Q-learning. In our heterogeneous setting, the only way for the private agents to achieve a zero value for their loss function, is for all of them to correctly anticipate the Nash equilibrium. It is of particular... 

The purpose of this paper is to deal with a novel intelligent predictive control scheme using the multiple models strategy with its application to an industrial tubular heat exchanger system. The main idea of the strategy proposed here is to represent the operating environments of the system, which have a wide range of variation in the span of time by several local explicit linear models. In line with this strategy, the well-known linear generalized predictive control (LGPC) schemes are initially designed corresponding to each one of the linear models of the system. After that, the best model of the system and the LGPC control action are precisely identified, at each instant of time, by an... 

A repeated inflation-unemployment game within the linear-quadratic framework of Barro and Gordon is studied assuming that the government would like to cheat optimally and the finite heterogeneous population of private agents attempts to learn the government's targets using a reinforcement learning algorithm. Private agents are heterogeneous in their initial expectations of inflation rate but are assumed to utilize an identical anticipatory reinforcement learning process, namely Q-learning. In our heterogeneous setting, the only way for the private agents to achieve a zero value for their loss function, is for all of them to correctly anticipate the Nash equilibrium. It is of particular... 

This paper deals with the problem of multi-agent learning of a population of players, engaged in a repeated normal-form game. Assuming boundedly-rational agents, we propose a model of social learning based on trial and error, called "social reinforcement learning". This extension of well-known Q-learning algorithm, allows players within a population to communicate and share their experiences with each other. To illustrate the effectiveness of the proposed learning algorithm, a number of simulations on the benchmark game of "Battle of Sexes" has been carried out. Results show that supplementing communication to the classical form of Q-learning, significantly improves convergence speed towards... 

This work deals with the problem of controlling the outlet temperature of a tubular heat exchanger system by means of flow pressure. The usual industrial case is to try to control the outlet temperature by either the temperature or the flow of the fluid, which flows through the shell tube. But, in some situations, this is not possible, due to the fact that the whole of system coefficients variation cannot quite be covered by control action. In this case, the system behavior must precisely be modeled and appropriate control action needs to be obtained based on novel techniques. A new multiple models control strategy using the well-known linear generalized predictive control (LGPC) scheme has... 

In traditional game theory, the players play with policy of maximizing their payoffs. In real world, there are many situations where payoffs have uncertainty and are fuzzy in nature. In this paper, a new method for finding pure strategy Nash equilibriums, to realistically analyze the games with fuzzy payoffs is investigated. Using ranking fuzzy numbers, a fuzzy preference relation is constructed over payoffs. The priorities of payoffs are considered as the degree of being Nash equilibriums  

The purpose of the paper presented here is to control the fluid temperature that flows in the inner tube of a tubular heat exchanger system by means of the fluid flow pressure. This system in its present form has a specified range of the coefficients' variation, while the temperature of the outlet fluid could generally be controlled by either the temperature or the flow of the inlet fluid flowing in the shell tube. The control realization for the system presented is often complicated, because the variation of the system coefficients and the reference signal must be thoroughly covered by the control action. In such a case, the system behaviour must first be represented by the multiple... 

The main issue in a surveillance environment is the target tracking. The most important concern in this problem is the association of the various measurements with the existing target tracks. The fuzzy c-means data association (FCMDA) algorithm, based on the fuzzy c-means (FCM) algorithm, is an efficient solution for the problem of measurement to track association in a multisensor multitarget environment. It has a high accuracy in measurement to track association when targets are far from each other. However, its accuracy remains low when targets are close to one another. The FCMDA algorithm performance is usually lost in this environment, especially when measurement noise is high. In the... 

The problem of fuzzy data association for target tracking in a cluttered environment is discussed in this paper. In data association filters based on fuzzy clustering, the association probabilities of tracking filters are reconstructed by utilizing the fuzzy membership degree of the measurement belonging to the target. Clearly in these filters, the fuzzy clustering method has an important role; better approach causes better precision in target tracking. Recently, by using the information theory, the maximum entropy fuzzy data association filter (MEF-DAF), as a fast and efficient algorithm, is introduced in literature. In this paper, by modification of a fuzzy clustering objective function,... 

In this paper, a new fuzzy based Model Coordination (F-MC) strategy is proposed for hierarchical control of large-scale systems (LSS). To solve the overall problem with a two-level optimal control strategy, we first decompose the system into several sub-systems at the first level. Then, at the second level, a fuzzy coordinator will be used to predict the interaction between subsystems. The proposed fuzzy based coordination approach is applicable to all types of LSS. Although in this paper, an optimal control of a 2DOF robot manipulator, as a LSS, will be considered. The obtained results are compared with the centralized optimization  

This paper presents a robust dc-link voltage as well as a current control strategy for a bidirectional interlink converter (BIC) in a hybrid ac/dc microgrid. To enhance the dc-bus voltage control, conventional methods strive to measure and feedforward the load or source power in the dc-bus control scheme. However, the conventional feedforward-based approaches require remote measurement with communications. Moreover, conventional methods suffer from stability and performance issues, mainly due to the use of the small-signal-based control design method. To overcome these issues, in this paper, the power from DG units of the dc subgrid imposed on the BIC is considered an unmeasurable... 

This paper presents a robust dc-link voltage as well as a current control strategy for a bidirectional interlink converter (BIC) in a hybrid ac/dc microgrid. To enhance the dc-bus voltage control, conventional methods strive to measure and feedforward the load or source power in the dc-bus control scheme. However, the conventional feedforward-based approaches require remote measurement with communications. Moreover, conventional methods suffer from stability and performance issues, mainly due to the use of the small-signal-based control design method. To overcome these issues, in this paper, the power from DG units of the dc subgrid imposed on the BIC is considered an unmeasurable... 

This paper presents a distributed, robust, finite-time secondary control for both voltage and frequency restoration of an islanded microgrid with droop-controlled inverter-based distributed generators (DGs). The distributed cooperative secondary control is fully distributed (i.e., uses only the information of neighboring DGs that can communicate with one another through a sparse communication network). In contrast to existing distributed methods that require a detailed model of the system (such as line impedances, loads, other DG units parameters, and even the microgrid configuration, which are practically unknown), the proposed protocols are synthesized by considering the unmodeled... 

This paper proposes a new distributed cooperative secondary control for both frequency and voltage restoration of an islanded microgrid with droop-controlled, inverter-based distributed generations (DGs). Existing distributed methods commonly design secondary control based on the minimum real part of the nonzero Laplacian matrix eigenvalues related to the microgrid communication graph, which, however, is global information. In contrast to the existing distributed methods, in this paper we design a fully distributed adaptive control based on the dynamic model of DG units and on information from neighboring units. Therefore, the proposed control scheme increases the system reliability,... 

This paper presents a new nonlinear current control strategy based on backstepping control and high-order sliding mode differentiator in order to employ distributed generation (DG) unit interfacing converters to actively compensate harmonics/interharmonics of local loads. The converter-based DG unit is connected to a weak grid (with uncertain impedance) and local load (that can be parametrically uncertain and topologically unknown) through an LCL filter. The proposed strategy robustly regulates the inverter output currents and delivers pure sinusoidal, three-phase balanced currents to the grid. The new controller demonstrates the robust performance and robust stability of the DG unit system... 

This paper presents a new nonlinear voltage control strategy based on backstepping control and a high-order sliding mode differentiator for an islanded microgrid. The microgrid consists of multiple distributed generation (DG) units with an arbitrary configuration that can be parametrically uncertain or topologically unknown. The proposed controller robustly regulates the microgrid voltages in the presence of parametric uncertainties, unmodeled dynamics, load imbalances, and nonlinear loads with harmonic/interharmonic currents. In contrast to existing methods, the controller does not need to know the frequency of harmonic and interharmonic current of microgrid loads that lead to the reduction...