Modeling and distributed gain scheduling strategy for load frequency control in smart grids with communication topology changes

In this paper, we investigate the modeling and distributed control problems for the load frequency control (LFC) in a smart grid. In contrast with existing works, we consider more practical and real scenarios, where the communication topology of the smart grid changes because of either link failures or packet losses. These topology changes are modeled as a time-varying communication topology matrix. By using this matrix, a new closed-loop power system model is proposed to integrate the communication topology changes into the dynamics of a physical power system. The globally asymptotical stability of this closed-loop power system is analyzed. A distributed gain scheduling LFC strategy is proposed to compensate for the potential degradation of dynamic performance (mean square errors of state vectors) of the power system under communication topology changes. In comparison to conventional centralized control approaches, the proposed method can improve the robustness of the smart grid to the variation of the communication network as well as to reduce computation load. Simulation results show that the proposed distributed gain scheduling approach is capable to improve the robustness of the smart grid to communication topology changes.     

Hierarchical control strategy for a three-phase 4-wire microgrid under unbalanced and nonlinear load conditions

This paper proposes an improved hierarchical control strategy consists of a primary and a secondary layer for a three-phase 4-wire microgrid under unbalanced and nonlinear load conditions. The primary layer is comprised of a multi-loop control strategy to provide balanced output voltages, a harmonic compensator to reduce the total harmonic distortion (THD), and a droop-based scheme to achieve an accurate power sharing. At the secondary control layer, a reactive power compensator and a frequency restoration loop are designed to improve the accuracy of reactive power sharing and to restore the frequency deviation, respectively. Simulation studies and practical performance are carried out using the DIgSILENT Power Factory software and laboratory testing, to verify the effectiveness of the control strategy in both islanded and grid-connected mode. Zero reactive power sharing error and zero frequency steady-state error have given this control strategy an edge over the conventional control scheme. Furthermore, the proposed scheme presented outstanding voltage control performance, such as fast transient response and low voltage THD. The superiority of the proposed control strategy over the conventional filter-based control scheme is confirmed by the 2 line cycles decrease in the transient response. Additionally, the voltage THDs in islanded mode are reduced from above 5.1% to lower than 2.7% with the proposed control strategy under nonlinear load conditions. The current THD is also reduced from above 21% to lower than 2.4% in the connection point of the microgrid with the offered control scheme in the grid-connected mode.     

Stabilizing model predictive control for constrained nonlinear distributed delay systems

In this paper, a model predictive control scheme with guaranteed closed-loop asymptotic stability is proposed for a class of constrained nonlinear time-delay systems with discrete and distributed delays. A suitable terminal cost functional and also an appropriate terminal region are utilized to achieve asymptotic stability. To determine the terminal cost, a locally asymptotically stabilizing controller is designed and an appropriate Lyapunov-Krasoskii functional of the locally stabilized system is employed as the terminal cost. Furthermore, an invariant set for locally stabilized system which is established by using the Razumikhin Theorem is used as the terminal region. Simple conditions are derived to obtain terminal cost and terminal region in terms of Bilinear Matrix Inequalities. The method is illustrated by a numerical example.     

Sampled-data control for linear time-delay distributed parameter systems

Some real systems have spatiotemporal dynamics and are time-delay distributed parameter systems (DPSs). The existence of time-delay may lead to system instability. The analysis and design of DPSs with time-delay is essentially more complicated. To take into account the factor of time-delay and fully enjoy the benefits of the digital technology in control engineering, it is a theoretical and practical value to consider the sampled-data control (SDC) problem of DPSs with time-delay. However, there are few attempts to solve the SDC problem of time-delay DPSs. In this paper, we introduce a SDC for linear time-delay DPSs described by parabolic partial differential equations (PDEs). A SDC design is developed in the formulation of spatial linear matrix inequalities (LMIs) by constructing an appropriate Lyapunov functional, which can stabilize exponentially the time-delay DPSs. This stabilization condition can be applied to either slowing-varying time delay or fast-varying one. Finally, simulation results of a numerical example are provided to illustrate the effectiveness of the proposed method.     

Robust output feedback distributed model predictive control of networked systems with communication delays in the presence of disturbance

In this work, an output feedback cooperative distributed model predictive control is developed for a class of networked systems composed of interacting subsystems interconnected through their states, in which it handles bounded disturbances and time varying communication delays. A distributed buffer based prediction strategy is used to compensate bounded delays and predict those states, which are coupled between subsystems that their actual values may not available due to delays. In the design of robust distributed model predictive control, distributed moving horizon estimation is employed so that convergence and boundedness of the estimation error are ensured. Furthermore, robust exponential stability of the closed loop system is established. The effectiveness of the proposed method is illustrated using two interconnected continuous stirred tank reactors.     

Function modules demanded for production control in distributed manufacturing system

This paper deals with the function modules demanded for production control in a distributed cellular manufacturing system. Cells are the distributed components of any manufacturing system. A proposed multipassing distributed simulating scheduling system (MPDSSS) deals with the production control functions regarding process planning (working-cell selection), scheduling, rescheduling, and real-time dispatching. The process planning function aims at selecting a good route for each job. The multipassing scheduling aims at providing a scheduling bidding strategy in a distributed fashion. The rescheduling aims at dealing with the large-effort change of the system with updating the precedence schedule to run in a new manufacturing period. The real-time scheduling deals with the small-effort change of the system with a real-time dispatching rule. All the production controlling functions have been implemented in distributed fashions. A simulation experiment demonstrates that the proposed MPDSSS leads to good results in the following criteria: minimum mean flow time, minimum waiting time, maximum machine utilisation, and minimum imbalance of cell utilisation.Nomenclature {A} grouping set ofA _i - A _i function-identical set of celli - BC _i the weighted bidding cost for the operation in celli - {C} performance criteria set - C _i ith element of {C} - CU _{f avg} average cell utilisation inA _f - CU _{f max} maximum cell utilisation inA _f - CU _i average cell utilisation of celli - CU_max maximum CU _i - CU_min minimum CU _i - {D} dispatching rule base - D _i ith rule in {D} - EFT earliest finishing time - EFT_max maximum EFT - ICU _f the imbalance of cell utilisation inA _f - P _m previously actual system performance for criterionC _m - RC _i rescheduling cost when using ruleD _i - SC _i improvement rate for system cost using ruleD _i - SP _a actual system performance - SP _m preceding simulation performance of theC _m with ruleD _i - SP _p ideally predictable system performance - SPD _a actual system performance deviation - TICU _i total imbalance of cell utilisation using ruleD _i - W weighting factor     

Neural network disturbance observer-based distributed finite-time formation tracking control for multiple unmanned helicopters

The distributed finite-time formation tracking control problem for multiple unmanned helicopters is investigated in this paper. The control object is to maintain the positions of follower helicopters in formation with external interferences. The helicopter model is divided into a second order outer-loop subsystem and a second order inner-loop subsystem based on multiple-time scale features. Using radial basis function neural network (RBFNN) technique, we first propose a novel finite-time multivariable neural network disturbance observer (FMNNDO) to estimate the external disturbance and model uncertainty, where the neural network (NN) approximation errors can be dynamically compensated by adaptive law. Next, based on FMNNDO, a distributed finite-time formation tracking controller and a finite-time attitude tracking controller are designed using the nonsingular fast terminal sliding mode (NFTSM) method. In order to estimate the second derivative of the virtual desired attitude signal, a novel finite-time sliding mode integral filter is designed. Finally, Lyapunov analysis and multiple-time scale principle ensure the realization of control goal in finite-time. The effectiveness of the proposed FMNNDO and controllers are then verified by numerical simulations.