Search

This paper focuses on the behavior of a linear quadratic Gaussian (LQG) controller for discrete-time systems utilizing industrial communication protocols. A new design of LQG problem is investigated for constrained networked control systems by using a new class of a quadratic cost function with a communication cost. This paper is considered two industrial communication protocols namely: the transportation control protocol (TCP), in which the sender should receive an acknowledgment regarding the delivery of the sending packets and the user datagram protocol (UDP) where the acknowledgment signal is absence. In the latter one, the driver (actuation) does not afford acknowledgment to inform the controller/estimator regarding the reception of the action packets. In such setting, the UDP-like protocol can react nonlinearly, where the absence of the acknowledgment creates a nonlinear optimization control law. In this sense, a LQG with standard Kalman filtering is failed because the separation principle can not reached. Under this setting, a suboptimal methodology can be successfully implemented to compensate the absence of communication and acknowledgment packets. The prescribed performance of networked system is sustained in the presence of communication constraints. The probabilities of the data signal dropouts are expressed in terms of random Bernoulli processes. Then, simulation results are provided to demonstrate the validity of the proposed schemes and to compare them with others from literature.

This paper addresses an infinite horizon distributed H2&#x002F H&#x221E filtering for discrete-time systems under conditions of bounded power and white stochastic signals. The filter algorithm is designed by computing a pair of gains namely the estimator and the coupling. Herein, we implement a filter to estimate unknown parameters such that the closed-loop multi-sensor accomplishes the desired performances of the proposed H2 and H&#x221E schemes over a finite horizon. A switched strategy is implemented to switch between the states once the operation conditions have changed due to disturbances. It is shown that the stability of the overall filtering-error system with H2&#x002F H&#x221E performance can be established if a piecewise-quadratic Lyapunov function is properly constructed. A simulation example is given to show the effectiveness of the proposed approach.

In this paper, we implement an output-feedback L1 adaptive controller for islanded distributed generation systems (DGs) with communication, load and generation constraints. The L1 adaptive controll...

This paper introduces novel cooperative control scheme based on adaptive critics for islanded Microgrids in the presence of disturbances. The interactions between the distributed generation sources are governed by a communication graph. Synchronization ideas are used to couple the dynamics of the distributed generation sources. A utility function is selected to reflect the objectives of the optimization problem. An online adaptive learning technique based on particle filtering is developed to estimate the dynamics of the distributed generation sources. Once the separation principle is held, the control input of every generation source and the estimator can be designed independently. The online adaptive learning technique uses incomplete knowledge about the dynamics of the distributed generation sources. Means of adaptive critics are used to implement the solution in real-time.

This paper introduces a survey on the adaptive and intelligent methods that have been applied to microgrids systems. Interestingly, the adaptive technique is effectively exercised in various control issues including stability, tracking error, and parameter uncertainties. Adaptive control has been extremely developed by using intelligent algorithms to automatically tune the control parameters namely fuzzy logic, particle swarm optimization, bacterial search algorithm, and etc. The objective is to evaluate and classify the design control methods and evaluation algorithms for the microgrid systems to maintain stability, reliability, and load variations by adjusting the controller parameters especially in standalone operation mode. The stability of islanded microgrids are constantly impacted by the related loads. A significant part of the research on an islanded microgrid involves droop control technique. In normal operation, distributed generation units and storage units provide power quality control. Once a shutdown is occurred, microgrid can be isolated from the main grid and operate in a local grid to support the local loads. Thus, distributed generations co-operate storage units to sustain the stability of the islanded microgrid.

We study the design problem of dynamic event-triggered (ET) fuzzy control methodology for discrete-time Takagi–Sugeno (T–S) systems in this work. The observed-state error is utilized to derive the event condition. Sufficient condition for the asymptotic stability of the closed-loop fuzzy system and the observer error system under the event-triggered fuzzy control is provided by linear matrix inequality (LMI). Moreover, the corresponding self-triggered (ST) fuzzy control is developed where the following control action is estimated in terms of the current sampled data. Furthermore, simulations are given to represent the feasibility and efficiency of the achieved results.

Overhead crane systems play a vital role in different factories to transport heavy loads. This paper provides an overview of recent developments in the modeling and control of three-dimensional overhead crane systems. It provides a categorized survey of the published work. Different control methodologies when applied to overhead crane are examined, outlined and assessed to aid for future work.

This paper investigates the problem of linear-quadratic Gaussian feedback control over unreliable communication channels with observation noise. We consider the problems of estimation and control under two different protocols. In one protocol, the transfer control protocol-like protocol, the estimation/control unit provides acknowledgments to successfully deliver the packets. In the other protocol, the user datagram protocol (UDP)-like protocol, no acknowledgments are permitted. We address the nonlinearity for the UDP protocol using the suboptimal approach. It is shown that there is a critical value at which the system becomes unstable. These unstable properties do not only depend on the rates of the control packets but also on the eigenvalues for the considered system. Simulation of two numerical examples is carried out in detail to illustrate the theoretical analysis.

This paper presents system identification and control of unmanned helicopter(UH) with ducted fan. The plant is an unstable multi-input multi-output (MIMO) system. Four identification methods have been considered in this work. Two of these methods studied the identification of the system as a set of transfer functions relating different inputs and outputs namely least square with QR-factorization (LS-QR) and recursive least square method (RLS). On the other hand, subspace method and observer/Kalman filter identification (OKID) methods have been used to identify the system in state space representation. The results of the identifications are presented and benchmarked based on degree of fitness. Comparison between output and methods are conducted and analyzed. OKID proves to be the best method for such system and subsequently serves as the basis for the design of LQGI-based velocities tracking controllers.

This paper presents the system identification and control of an unmanned helicopter(UH) with ducted fan. The plant is an unstable multi-input-multi-output (MIMO) system. First, four identification methods have been considered in this work. Two of these methods studied the identification of the system as a set of transfer functions relating different inputs and outputs, namely the least square method with QR-factorization (LS-QR) and the recursive least square method (RLS). The other two methods are state-space identification method. Indeed, the classical subspace identification method and the observer-Kalman filter identification (OKID) method have been used to identify the system in state space representation. Analytical formulations of these methods as well as comparison of their performances based on their degree of fitness are presented for the special case of UH system. The results show that OKID out-performs the other methods. Based on this result, an OKID-LQGI-based controller for velocities tracking controller is proposed. The simulation results show excellent tracking performance.

The feedback load is an important parameter with a large impact in Orthogonal Frequency Division Multiple Access (OFDMA) techniques, as a feedback over each one of the subcarriers will induce a non-acceptable signalling load in the system, so that some optimization and feedback reduction strategies are required to meet practical systems demands. The decision over the best strategy for feedback optimization highly depends on the number of available users in the system. We obtain the users' effect on the system through a feedback strategy over a subset of the subcarriers showing the best channel conditions, where a closed form expression of the obtained data rate is formulated to exactly indicate the effect of the number of users, the operating SNR and/or the available number of feedback bits in the system. The performance of the presented scheme is compared to the One-bit feedback strategy in terms of the resultant data rate, where interesting conclusions are obtained.