Network-based control of nonlinear large-scale systems composed of identical subsystems

This paper deals with a control of coupled nonlinear identical systems that admit full exact feedback input-output linearization. The subsystems are linearized using this nonlinear transformation. In the next step, an auxiliary low-dimensional system is derived whose stability implies stability of the original large-scale system. The control law is designed so that the control loops are only local, no information exchange between subsystems is required. Unknown time delay in the feedback are allowed. Two cases are studied: equal time delay for all subsystems or different delay in all subsystems. Results are illustrated by two examples.     

A cyclic pursuit framework for networked mobile agents based on vector field approach

This paper proposes a pursuit formation control scheme for a network of double-integrator mobile agents based on a vector field approach. In a leaderless architecture, each agent pursues another one via a cyclic topology to achieve a regular polygon formation. On the other hand, the agents are exposed to a rotational vector field such that they rotate around the vector field centroid, while they keep the regular polygon formation. The main problem of existing approaches in the literature for cyclic pursuit of double-integrator multiagent systems is that under those approaches, the swarm angular velocity and centroid are not controllable based on missions and agents capabilities. However, by employing the proposed vector field approach in this paper, while keeping a regular polygon formation, the swarm angular velocity and centroid can be determined arbitrary. The obtained results can be extended to achieve elliptical formations with cyclic pursuit as well. Simulation results for a team of eight mobile agents verify the accuracy of the proposed control scheme.     

Output regulation for a class of positive switched systems

In this paper, a complete procedure for the study of the output regulation problem is established for a class of positive switched systems utilizing a multiple linear copositive Lyapunov functions scheme. The feature of the developed approach is that each subsystem is not required to has a solution to the problem. Moreover, two types of controllers and switching laws are devised. The first one depends on the state together with the external input and the other depends only the error. The conditions ensuring the solvability of the problem for positive switched systems are presented in the form of linear matrix equations plus linear inequalities under some mild constraints. Two examples are finally given to show the performance of the proposed control strategy.     

Integrated guidance and control with partial state constraints and actuator faults

In this paper, a novel adaptive integrated guidance and control (IGC) scheme is proposed for skid-to-turn (STT) missile with partial state constraints and actuator faults. Considering the strict-feedback form of the IGC model, the dynamic surface control (DSC) approach is adopted to design the IGC scheme. To prevent the attack angle, sideslip angle and velocity deflection angle from violating the constraints, the barrier Lyapunov function (BLF) and modified saturation function are employed in the IGC design procedure. Moreover, an auxiliary system is constructed to remove the adverse effects that caused by the modified saturation function. The adaptive laws are constructed to estimate the actuation effectiveness of actuators and the upper bounds of lumped uncertainties in the IGC model. It is theoretically shown that all signals in the closed-loop system are bounded while the state constraints are not violated in presence of actuator faults and uncertainties. Numerical simulation results are presented to verify the effectiveness and robustness of the proposed IGC scheme.     

Spacecraft output feedback attitude control based on extended state observer and adaptive dynamic programming

This paper investigates spacecraft output feedback attitude control problem based on extended state observer (ESO) and adaptive dynamic programming (ADP) approach. For the plant described by the unit quaternion, an ESO is first presented in view of the property of the attitude motion, and the norm constraint on the unit quaternion can be satisfied theoretically. The practical convergence proof of the developed ESO is illustrated by change of coordinates. Then, the controller is designed with an involvement of two parts: the basic part and the supplementary part. For the basic part, a proportional-derivative control law is designed. For the supplementary part, an ADP method called action-dependent heuristic dynamic programming (ADHDP) is adopted, which provides a supplementary control action according to the differences between the actual and the desired system signals. Simulation studies validate the effectiveness of the proposed scheme.     

Neural dynamic sliding mode control of nonlinear systems with both matched and mismatched uncertainties

Mismatched uncertainty and chattering appear as two challenges in sliding mode control. To overcome the problem of mismatched uncertainty, multiple sliding surfaces with virtual inputs are proposed. Accordingly, we have proposed two new methods based on designed neural observer: sliding mode control (SMC) and dynamic sliding mode control (DSMC) methods. Although, the proposed SMC can significantly cope with the mismatched uncertainties, but it suffers from chattering phenomenon. The chattering problem can be removed in DSMC, because an integrator is placed before the system. This results in increased number of the system states. This new state can be identified with the proposed neural observer. Note that in both proposed approaches, the robust performance (invariance property) of system is reserved, even in the presence of mismatch uncertainties. Then, to have a valid comparison the proposed DSMC is also designed using loop transfer recovery observer (LTRO). This comparison shows the good performance of the DSMC based neural networks. Moreover, the upper bound of uncertainties is not used in SMC and DSMC controllers and also in the neural observer and LTRO, which is important in practical implementation. Finally, comparing the equations, one can see the simplicity of DSMC in concept and also in realization.     

New modeling approach of secondary control layer for autonomous single-phase microgrids

In a microgrid (MG) topology, the secondary control is introduced to compensate for the voltage amplitude and frequency deviations, mainly caused by the inherent characteristics of the droop control strategy. This paper proposes an accurate approach to derive small signal models of the frequency and amplitude voltage at the point of common coupling (PCC) of a single-phase MG by analyzing the dynamics of the second-order generalized integrator-based frequency-locked loop (SOGI-FLL). The frequency estimate model is then introduced in the frequency restoration control loop, while the derived model of the amplitude estimate is introduced for the voltage restoration loop. Based on the obtained models, the MG stability analysis and proposed controllers’ parameters tuning are carried out. Also, this study includes the modeling and design of the synchronization control loop that enables a seamless transition from island mode to grid-connected mode operation. Simulation and practical experiments of a hierarchical control scheme, including traditional droop control and the proposed secondary control for two single-phase parallel inverters, are implemented to confirm the effectiveness and the robustness of the proposal under different operating conditions. The obtained results validate the proposed modeling approach to provide the expected transient response and disturbance rejection in the MG.     

Parallel access by butterfly networks for any degree permutation polynomial and ARP interleavers

Using more processors for parallel turbo decoding is an important issue to speed up the processing at the receiver of a communication system. Butterfly networks used to map the addresses of extrinsic values represent an elegant and simple solution in parallel turbo decoding. Recently, it has been shown that quadratic permutation polynomial (QPP) interleavers allow an easy way to compute the control bits for a butterfly network. In this paper we show that not only QPP interleavers, but any degree permutation polynomial (PP) interleavers and almost regular permutation (ARP) interleavers also allow the same easy way to compute the control bits required in butterfly networks. As a consequence, it is useful to apply the butterfly networks in parallel turbo decoding when using these performant algebraic interleavers.     

Novel integral sliding mode control for small-scale unmanned helicopters

Integral sliding mode (ISM) control which consists of a nominal control and a sliding-mode motion control, provides a nice framework for high tracking performance and good disturbance reduction. Our work develops ISM to attenuate the adverse effect of mismatched perturbations. By properly choosing sliding-manifold surface, the elimination of disturbances on control outputs enables to be achieved. Additionally, the chattering of sliding-mode control part is attenuated based on second-order sliding mode idea. Then, the proposed novel ISM control scheme is applied to address trajectory tracking problem for helicopters under perturbations. Approximated input-output linearization is implemented, such that the obtained linearized model is suitable for applying the proposed ism control. The stability of the closed-loop system for helicopter and its convergence to zeros of tracking errors are demonstrated by Lyapunov theory analysis. Several comparison simulations illustrate the effectiveness and superiority of the proposed methods.     

Dynamics of a stochastic multigroup SIQR epidemic model with standard incidence rates

In this paper, we consider a stochastic multigroup SIQR epidemic model with standard incidence rates. By using the stochastic Lyapunov function method, we establish sufficient conditions for the existence of a stationary distribution of the positive solutions to the model. Then we establish sufficient conditions for extinction of the diseases. A stationary distribution means that all the individuals can be coexistent and persistent in the long term. Finally, some examples and numerical simulations are introduced to illustrate our theoretical results.