Superimposed channel training algorithm for time-varying MIMO relay systems

Two-way relaying systems are known to be capable of providing higher spectral efficiency compared with one-way relaying systems. However, the channel estimation problem for two-way relaying systems becomes more complicated. In this paper, we propose a superimposed channel training scheme for two-way MIMO relay communication systems, where the individ-ual channel information for users-relay and relay-users links are estimated. The optimal structure of the source and relay training sequences are derived when the mean-squared error (MSE) of channel estimation is minimized. We also optimize the power allocation between the source and relay training sequences to improve the performance of the algorithm. Numerical examples are shown to demonstrate the performance of the proposed channel training algorithm.

Predictive motion planning for AUVs subject to strong time-varying currents and forecasting uncertainties

This paper presents a novel path planning method for minimizing the energy consumption of an autonomous underwater vehicle subjected to time varying ocean disturbances and forecast model uncertainty. The algorithm determines 4-Dimensional path candidates using Nonlinear Robust Model Predictive Control (NRMPC) and solutions optimised using A∗-like algorithms. Vehicle performance limits are incorporated into the algorithm with disturbances represented as spatial and temporally varying ocean currents with a bounded uncertainty in their predictions. The proposed algorithm is demonstrated through simulations using a 4-Dimensional, spatially distributed time-series predictive ocean current model. Results show the combined NRMPC and A∗ approach is capable of generating energy-efficient paths which are resistant to both dynamic disturbances and ocean model uncertainty.

Stability of two-dimensional Roesser systems with time-varying delays via novel 2D finitesum inequalities

This study considers the problem of stability analysis of discrete-time two-dimensional (2D) Roesser systems with interval time-varying delays. New 2D finite-sum inequalities, which provide a tighter lower bound than the existing ones based on 2D Jensen-type inequalities, are first developed. Based on an improved Lyapunov-Krasovskii functional, the newly derived inequalities are then utilised to establish delay-range-dependent linear matrix inequality-based stability conditions for a class of discrete time-delay 2D systems. The effectiveness of the obtained results is demonstrated by numerical examples.

A novel approach to exponential stability of continuous-time Roesser systems with directional time-varying delays

This paper addresses the problem of exponential stability analysis of two-dimensional (2D) linearcontinuous-time systems with directional time-varying delays. An abstract Lyapunov-like theorem whichensures that a 2D linear system with delays is exponentially stable for a prescribed decay rate is exploitedfor the first time. In light of the abstract theorem, and by utilizing new 2D weighted integral inequalitiesproposed in this paper, new delay-dependent exponential stability conditions are derived in terms oftractable matrix inequalities which can be solved by various computational tools to obtain maximumallowable bound of delays and exponential decay rate. Two numerical examples are given to illustrate theeffectiveness of the obtained results.

MMSE precoder for unitary space–time codes in correlated time-varying channels

This letter addresses the problem of the design of a precoder for multiple transmit antenna communication systems with spatially and temporally correlated fading channels. By using the asymptotic (high signal-to-noise ratio) mean-square error of the channel estimates, the letter derives a precoder for unitary space-time codes that can exploit the spatiotemporal correlation in the time-varying fading channels. Simulation results illustrate that significant performance gains can be achieved by using the new precoder.

Observer-based robust finite-time cooperative consensus control for multi-agent networks

This paper studies the finite-time consensus tracking control for multi-agent networks. The time-varying control input and the velocity of the leader is unknown to any follower. Only the position of the leader is known to its neighbors. We first propose a new finite-time multiple-surface sliding mode observer to estimate the leader's velocity. It is seen that the estimation error of the observer can converge to zero in a finite time. Then, we prove that finite-time consensus tracking of multi-agent networks can be achieved on a new terminal sliding mode surface. Simulation results are presented to validate the analysis.

Finite-time consensus algorithm of multi-agent networks

This paper is concerned with leader-follower finite-time consensus control of multi-agent networks with input disturbances. Terminal sliding mode control scheme is used to design the distributed control law. A new terminal sliding mode surface is proposed to guarantee finite-time consensus under fixed topology, with the common assumption that the position and the velocity of the active leader is known to its neighbors only. By using the finite-time Lyapunov stability theorem, it is shown that if the directed graph of the network has a directed spanning tree, then the terminal sliding mode control law can guarantee finite-time consensus even under the assumption that the time-varying control input of the active leader is unknown to any follower.

A new design of sliding mode control systems

A new sliding mode control technique for a class of SISO dynamic systems is presented in this chapter. It is seen that the stability status of the closed-loop system is first checked, based on the approximation of the most recent information of the first-order derivative of the Lyapunov function of the closed-loop system, an intelligent sliding mode controller can then be designed with the following intelligent features: (i) If the closed-loop system is stable, the correction term in the controller will continuously adjust control signal to drive the closed-loop trajectory to reach the sliding mode surface in a finite time and the desired closed-loop dynamics with the zero-error convergence can then be achieved on the sliding mode surface. (ii) If, however, the closed-loop system is unstable, the correction term is capable of modifying the control signal to continuously reduce the value of the derivative of the Lyapunov function from the positive to the negative and then drives the closed-loop trajectory to reach the sliding mode surface and ensures that the desired closed-loop dynamics can be obtained on the sliding mode surface. The main advantages of this new sliding mode control technique over the conventional one are that no chattering occurs in the sliding mode control system because of the recursive learning control structure; the system uncertainties are embedded in the Lipschitz-like condition and thus, no priori information on the upper and/or the lower bounds of the unknown system parameters and uncertain system dynamics is required for the controller design; the zero-error convergence can be achieved after the closed-loop dynamics reaches the sliding mode surface and remains on it. The performance for controlling a third-order linear system is evaluated in the simulation section to show the effectiveness and efficiency of the new sliding mode control technique.

New inequality-based approach to passivity analysis of neural networks with interval time-varying delay

This paper is concerned with the problem of passivity analysis of neural networks with an interval time-varying delay. Unlike existing results in the literature, the time-delay considered in this paper is subjected to interval time-varying without any restriction on the rate of change. Based on novel refined Jensen inequalities and by constructing an improved Lyapunov-Krasovskii functional (LKF), which fully utilizes information of the neuron activation functions, new delay-dependent conditions that ensure the passivity of the network are derived in terms of tractable linear matrix inequalities (LMIs) which can be effectively solved by various computational tools. The effectiveness and improvement over existing results of the proposed method in this paper are illustrated through numerical examples.

An improved stability criterion for time-delay power systems with electric vehicles and high voltage direct current power links

This paper presents an improved stability criterion for load frequency control (LFC) of time-delay power systems including AC/HVDC transmission links and EVs. By employing a novel refined Jensen-based inequality, an improved stability condition is derived in terms of feasible linear matrix inequalities (LMIs) which allow us to compute the maximal upper bounds of time-delay ensuring stability of the LFC scheme equipped with an embedded controller. Cases studies here are implemented for LFC scheme of a two-area power system, which is interconnected by parallel (AC/HVDC) links, with embedded proportional integral (PI) controller for discharged EVs. The relationships between the parameters of PI controller, supplementary control of HVDC links and delay margins of the LFC scheme are also discussed. As a consequence of facts, the results of delay margins can be used as a guideline to tune PI controller and set-up parameters for HVDC control.

Reachable sets bounding for generalized neural networks with interval time-varying delay and bounded disturbances

This paper deals with the problem of finding outer bound of forwards reachable sets and interbound of backwards reachable sets of generalized neural network systems with interval nondifferentiable time-varying delay and bounded disturbances. Based on constructing a suitable Lyapunov–Krasovskii functional and utilizing some improved Jensen integral-based inequalities, two sufficient conditions are derived for the existence of: (1) the smallest possible outer bound of forwards reachable sets and (2) the largest possible interbound of backwards reachable sets. These conditions are delay dependent and in the form of matrix inequalities, which therefore can be efficiently solved by using existing convex algorithms. Three numerical examples with simulation results are provided to demonstrate the effectiveness of our results.

Agency theory, national culture and management Control Systems

Management control system of an organization is the structured facet of management, the formal vehicle by which the management process is executed. In most organizations, systems exist for planning, organizing, directing, controlling and motivating. Depending on the level of appropriateness and quality of the management control systems, the task of management is either facilitated or hindered. The end goal of a management control system is achieving organizational objectives. Because employees (agents) do not always give their best efforts for achieving organizational objectives, management control systems need to strive for aligning goals of agents (e.g., employees, subordinates) with that of principals (e.g., senior management, owners). Agency theory and its extension, principal agent model, provide insights to the problem of goal congruence and suggest remedies, at least in the Western cultural context. Whether the agency theory presumptions, predictions and prescriptions are universally applicable is an important issue in management. Their validity in different cultural contexts is largely unknown. The available literature to date indicates the possibility that agency theory may not be valid in non-western cultures. However, further empirical research is needed in non-western cultures to shed more light to this issue.

Agency theory and culture : implications for research in management control systems

The objective of this paper is to encourage further research into the applicability of agency theory for the study of management control issues of organisations in Asian societies.

Time-varying dependence in the intraday AUS/USD spot market

Using a high-frequency data set of the spot Australian dollar/US dollar this study examines the distribution of quotes and returns across the 24 hour trading "day". Employing statistical methods for measuring long-tenn dependence in time-series we find evidence of time-varying dependence and volatility that aligns with the opening and closing of markets. This variation is attributed to the effects of liquidity and the price-discovery actions of dealers.

Time-varying hedge ratios: an application to the Indian stock futures market

This paper investigates time-varying optimal hedge ratios in individual stock futures markets in India. The analysis employs data on individual stock futures from an unexplored but highly traded (both in terms of volume and quantity) emerging market. The hedge ratios derived in this study incorporate mean reversion in volatility, which is an important extension of the bivariate BEKK-GARCH model of Engle and Kroner. This extension generates improved optimal hedge ratios over the traditional BEKK-GARCH model and static error correction type alternatives.