Joint swing-up and stabilization of the Reaction Wheel Pendulum using Discontinuous Integral algorithm

In this paper, a third-order discontinuous integral controller is designed to jointly swing-up and robustly stabilize in finite-time the upright position of the Reaction Wheel Pendulum (RWP) system, despite some uncertainties and perturbations. To show this, a numerical estimation of the domain of attraction of the controller is used. The control algorithm produces a continuous control signal, thus reducing the usual chattering effect of the sliding-mode controllers. The theoretical results of the paper are verified by simulations and experiments in a laboratory setup.     

A robust and efficient estimation method for single-index varying-coefficient models

A new estimation procedure based on modal regression is proposed for single-index varying-coefficient models. The proposed method achieves better robustness and efficiency than that of Xue and Pang (2013). We establish the asymptotic normalities of proposed estimators and evaluate the performance of the proposed method by a numerical simulation.     

Robust SMES controller design for stabilization of inter-area oscillation considering coil size and system uncertainties

It is well known that the superconducting magnetic energy storage (SMES) is able to quickly exchange active and reactive power with the power system. The SMES is expected to be the smart storage device for power system stabilization. Although the stabilizing effect of SMES is significant, the SMES is quite costly. Particularly, the superconducting magnetic coil size which is the essence of the SMES, must be carefully selected. On the other hand, various generation and load changes, unpredictable network structure, etc., cause system uncertainties. The power controller of SMES which is designed without considering such uncertainties, may not tolerate and loses stabilizing effect. To overcome these problems, this paper proposes the new design of robust SMES controller taking coil size and system uncertainties into account. The structure of the active and reactive power controllers is the 1st-order lead-lag compensator. No need for the exact mathematical representation, system uncertainties are modeled by the inverse input multiplicative perturbation. Without the difficulty of the trade-off of damping performance and robustness, the optimization problem of control parameters is formulated. The particle swarm optimization is used for solving the optimal parameters at each coil size automatically. Based on the normalized integral square error index and the consideration of coil current constraint, the robust SMES with the smallest coil size which still provides the satisfactory stabilizing effect, can be achieved. Simulation studies in the two-area four-machine interconnected power system show the superior robustness of the proposed robust SMES with the smallest coil size under various operating conditions over the non-robust SMES with large coil size.     

Equality Constraints in Multiobjective Robust Design Optimization: Decision Making Problem

Robust design optimization (RDO) problems can generally be formulated by incorporating uncertainty into the corresponding deterministic problems. In this context, a careful formulation of deterministic equality constraints into the robust domain is necessary to avoid infeasible designs under uncertain conditions. The challenge of formulating equality constraints is compounded in multiobjective RDO problems. Modeling the tradeoffs between the mean of the performance and the variation of the performance for each design objective in a multiobjective RDO problem is itself a complex task. A judicious formulation of equality constraints adds to this complexity because additional tradeoffs are introduced between constraint satisfaction under uncertainty and multiobjective performance. Equality constraints under uncertainty in multiobjective problems can therefore pose a complicated decision making problem. In this paper, we provide a new problem formulation that can be used as an effective multiobjective decision making tool, with emphasis on equality constraints. We present two numerical examples to illustrate our theoretical developments.     

On improving optimal oblivious routing

In this paper a generalization of the robust network design problem with oblivious routing is investigated, where the (uncertain) demands are served through two alternative routing templates. A mathematical programming model leading to tractable cases is presented, together with related algorithmic approaches. The proposed special cases strictly generalize the standard oblivious routing model.     

Combining passivity and classical frequency-domain methods: An insight into decentralised control

A novel approach to tackle passivity-related issues in the frequency domain for linear multiple-input multiple-output (MIMO) cross-coupled systems is given. The aim is to design passivity-based stabilising diagonal controllers within the framework of Individual Channel Analysis and Design (ICAD). Two main results are presented. First, the ICAD is reinterpreted in terms of the passivity-related properties of either the channels or the closed-loop system. The notion of practical passivity is introduced. Second, for linear MIMO systems, a novel frequency-domain passification procedure is proposed. This procedure is used in the design process of the diagonal controllers. Furthermore, an indicator of how far the system is from being passive is defined. This indicator is stated in terms of gain and phase margins, with the consequent statement of robustness. Such a passivity indicator has not been established so far, and for practical applications can be more useful than setting the passivity of the system. Classical frequency-domain control techniques based on Bode and Nyquist plots are used. The results are applied to a 2-input-2-output system modelling an induction motor.     

Improved stability analysis on delayed neural networks with linear fractional uncertainties

The paper is concerned with robust stability for generalized neural networks (GNNs) with both interval time-varying delay and time-varying distributed delay. Through partitioning the time-delay, choosing one augmented Lyapunov-Krasovskii functional, employing free-weighting matrix method and convex combination, the sufficient conditions are obtained to guarantee the robust stability of the concerned systems. These stability criteria are presented in terms of linear matrix inequalities (LMIs) and can be easily checked. Finally, three numerical examples are given to demonstrate the effectiveness and reduced conservatism of the obtained results.     

Risk quantification and validation for Bitcoin

This paper introduces a semi-nonparametric approach for modeling Bitcoin risk relatively to other parametric distributions and volatility models. Model performance is assessed through different backtesting techniques, including multinomial test, for three risk measures: Value-at-Risk, Expected Shortfall and Median Shortfall. Our results show that the ‘large’ semi-nonparametric expansion is a good alternative to measure Bitcoin risk according to recommendations of Basel Committee on Banking Supervision, but also that 99%-Median Shortfall seems to be an accurate and robust risk measure for Bitcoin.