Search

The Doing Business reports have evoked an intense policy debate about whether countries should simplify regulatory rules or make them more stringent. We argue that doing business in developing countries is based on deals struck between firms and the state, rather than rules. We show that there is a weak relationship between rules and deals, and at low levels of state capability, more stringent rules leading to less compliance, rather than more. We provide a diagnostic approach to rules reform where the appropriate reform depend on the level of stringency of the rules, and the level of its state capability. [ABSTRACT FROM AUTHOR]

Summary: Steer‐by‐wire (SBW) systems are considered as one of the most significant innovations among the technologies developed for advanced driver‐assistance systems and autonomous vehicles. The main control challenge in a SBW system is to follow the steering commands in the face of parametric uncertainties and external disturbances; crucially, perturbations in inertial parameters and damping forces give rise to state‐dependent uncertainties, which cannot be bounded a priori by a constant. However, the state‐of‐the‐art control methods of SBW system rely on a priori bounded uncertainties, and thus, become inapplicable when state‐dependent dynamics become unknown. This work, to the best of the authors' knowledge for the first time, proposes an adaptive control framework that can tackle the state‐dependent uncertainties and external disturbances in a typical SBW system without any a priori knowledge of their structures and of their bounds. The stability of the closed‐loop system is studied analytically via uniformly ultimately bounded notion and the effectiveness of the proposed solution is verified via simulations against the state‐of‐the‐art solution. [ABSTRACT FROM AUTHOR]

Artificial-delay control is a method in which state and input measurements collected at an immediate past time instant (i.e., artificially delayed) are used to compensate the uncertain dynamics affecting the system at the current time. This article formulates an artificial-delay control method with adaptive gains in the presence of nonlinear (Euler–Lagrange) underactuation. The appeal of studying Euler–Lagrange dynamics is to capture many robotics applications of practical interest, as demonstrated via stability and robustness analysis and via robotic ship and robotic aerial vehicle test cases. [ABSTRACT FROM AUTHOR]

A consideration of actuator saturation is an important aspect to study the effectiveness of a designed controller in practice. However, the conventional Lyapunov theory-based design is not always suitable to analyze the quantitative behavior of closed-loop system. This article presents a time-scale redesign-based saturated tracking controller for a class of feedback linearizable multi-input–multi-output (MIMO) nonlinear systems. The proposed controller is built upon the frameworks of contraction and partial contraction theories which ensures that bounded tracking performance as well as quantify the steady-state error bounds in terms of the various control design parameters. Notably, in contrast to the existing Lyapunov-method-based designs, the proposed approach allows to tune the controller performance without arbitrary reduction of singular perturbation parameters. Therefore, the vulnerability of the controller toward actuator saturation and noise, due to the ill-effects of high-gains stemming from the conventional high-gain controllers, are reduced. The extensive experimental results using a wheeled mobile robot are provided to demonstrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

Multi-area load frequency control (LFC) selects and controls a few generators in each area of the power system in an effort to dampen inter-area frequency oscillations. To effectively dampen such oscillations, it is required to enhance and lower the control activity dynamically during operation, so as to adapt to changing circumstances. Changing circumstances should cover not only parametric uncertainties and unmodelled dynamics (e.g. aggregated area dynamics and bus dynamics), but also the increasing structural flexibility of modern power systems (e.g. protection mechanisms against faults and cyber-attacks, or topology reconfiguration mechanisms for demand response). As formal stability guarantees around such an attractive adaptive multi-area LFC concept are still lacking, this work proposes framework in which adaptation and switching are combined in a provably stable way to handle parametric uncertainty, unmodelled dynamics, and dynamical interconnections of the power system. Stability is studied in the Lyapunov theory sense using the standard structure-preserving modelling approach, and the resulting adaptive multi-area LFC design is validated using an IEEE 39-bus benchmark. [ABSTRACT FROM AUTHOR]

By increasingly relying on network-based operation for control, monitoring, and protection functionalities, modern wide-area power systems have also become vulnerable to cyber-attacks aiming to damage system performance and/or stability. Resilience in state-of-the-art methods mostly relies on known characteristics of the attacks and static control loops (i.e., with fixed input/output channels). This work proposes a ‘dynamic loop’ wide-area damping strategy, where input/output channel pairs are changed dynamically. We study ‘reactive’ dynamic switching in case of detectable attack and ‘pro-active’ dynamical switching, in case of undetectable (stealth) attacks. Stability of the dynamic loop is presented via Lyapunov theory, under parametric perturbations, average dwell time switching and external perturbations. Using two- and five-area IEEE benchmarks, it is shown that the proposed strategy provides effective damping and robustness under various detectable (e.g., false data injection, denial-of-service) and stealth (replay, bias injection) attacks. [ABSTRACT FROM AUTHOR]

This article proposes an adaptive‐robust maneuvering control framework for a planar snake robot under the influence of parameter uncertainties. The entire control objective of maneuvering control can be viewed as the simultaneous establishments of two goals: one to maintain a time‐varying body shape of the snake robot for consistent motion (called the outer layer) and the other dealing with the velocity and head‐angle tracking of the same (called the inner layer). Unknown variations in the ground friction coefficients have been considered to be the primary source of time‐varying uncertainties which affects the control performance in both the layers. Accordingly, an artificial time delay‐based adaptive‐robust control (ARC) framework, dual adaptive‐robust time‐delayed control (ARTDC), is proposed. The term dual signifies simultaneous application of ARTDC for the outer as well as the inner layer. ARTDC comprises of two segments: an artificial time delay‐based time‐delayed estimation (TDE) part and an ARC part. While TDE approximates the completely unknown friction forces, the ARC tackles the approximation error arising from the TDE. More importantly, compared with the existing ARC methodologies, the proposed ARTDC neither presumes the overall uncertainty to be upper bounded by a constant nor requires any prior knowledge of the bound of uncertainty to implement the controller. A Lyapunov function‐based method has been adopted for analyzing the stability of the closed‐loop system. Simulation studies affirm the improved performance of the ARTDC in contrast to the classical artificial delay‐based methodology. [ABSTRACT FROM AUTHOR]

Mobile robots play a crucial role in cleaning, maintenance, and surveillance applications. This article advocates for the use of a novel robust output feedback based path following controller, for a class of self-reconfigurable mobile robot under actuator saturation. The reconfigurability property of such platforms is captured via an uncertain Euler–Lagrange dynamics. The proposed control framework estimates the unmeasurable states and the uncertain dynamics terms through two extended high gain observers, whereas the actuator limits are honored via a fast dynamic compensator. The closed-loop stability is analyzed via contraction theory, which, compared to the conventional Lyapunov based approaches, avoids the requirement of arbitrarily large controller and observer gains. Such a feature is of particular interest in view of actuator saturation. The experimental results with PANTHERA self-reconfigurable robot validate the effectiveness of the proposed technique over the state of the art. [ABSTRACT FROM AUTHOR]

The adaptive sliding mode control technique relaxes the assumption of known bound of the disturbance in discrete-time systems. However, the existing technique of gain adaptation in discrete-time sliding mode control has issues of gain overestimation and underestimation. Therefore, this paper proposes a technique to adapt the switching gain such that the adaptive gain can tackle the uncertainty without any knowledge of the bound of uncertainty while overcoming the over- and under-estimation problems of switching gain. [ABSTRACT FROM AUTHOR]

Summary: With the advent of intelligent transport, quadrotors are becoming an attractive solution while lifting or dropping of payloads during emergency evacuations, construction works, etc. During such operations, dynamic variations in (possibly unknown) payload cause considerable changes in the system dynamics. However, a systematic control solution to tackle such interchanging dynamical behavior is still missing. This paper proposes a switched dynamical framework to capture the interchanging dynamics of a quadrotor during vertical operations and a robust adaptive control solution to tackle such dynamics when it is unknown. The stability of the closed‐loop system is studied analytically and the effectiveness of the proposed solution is verified via simulations. [ABSTRACT FROM AUTHOR]

The actual performance of model-based path-following methods for unmanned aerial vehicles (UAVs) shows considerable dependence on the wind knowledge and on the fidelity of the dynamic model used for design. This study analyzes and demonstrates the performance of an adaptive vector field (VF) control law which can compensate for the lack of knowledge of the wind vector and for the presence of unmodeled course angle dynamics. Extensive simulation experiments, calibrated on a commercial fixed-wing UAV and proven to be realistic, show that the new VF method can better cope with uncertainties than its standard version. In fact, while the standard VF approach works perfectly for ideal first-order course angle dynamics (and perfect knowledge of the wind vector), its performance degrades in the presence of unknown wind or unmodeled course angle dynamics. On the other hand, the estimation mechanism of the proposed adaptive VF effectively compensates for wind uncertainty and unmodeled dynamics, sensibly reducing the path-following error as compared to the standard VF. [ABSTRACT FROM AUTHOR]

State-of-the-art adaptive or robust adaptive techniques for several classes of uncertain switched systems demand structural knowledge of the system dynamics in order to appropriately select the regressor terms in the adaptive law. As a result, the number of unknown parameters to be adapted increases with system complexity, which can lead to very complex adaptive laws. In this work we propose, for the relevant class of Euler–Lagrange systems subject to time-dependent slow switching, a switched robust adaptive control framework with reduced complexity: the number of unknown parameter to be adapted is independent on the system complexity, whereas the regressor terms in the adaptive laws do not require any structural knowledge of the system dynamics. Stability analysis is provided to illustrate the benefit of the proposed design, and the performance of the controller is verified using a switched system stemming from the combination of mooring and free-hanging operations in dynamic positioning of offshore ships. [ABSTRACT FROM AUTHOR]

Underestimation and overestimation problems are commonly observed in conventional adaptive sliding mode control (ASMC). These problems refer to the fact that the adaptive controller gain unnecessarily increases when the states are approaching the sliding surface (overestimation) or improperly decreases when the states are getting far from it (underestimation). In this paper, we propose a novel ASMC strategy that overcomes such issues. In contrast to the state of the art, the proposed strategy is effective even when an a priori constant bound on the uncertainty cannot be imposed. Comparative results using a two-link manipulator demonstrate improved performance as compared to the conventional ASMC. Experimental results on a biped robot confirm the effectiveness and robustness of the proposed method under various practical uncertainties. [ABSTRACT FROM AUTHOR]

One of the major issues in an interconnected power system is the low damping of inter-area oscillations. A proportional-derivative (PD) compensator is a popular control method which is extensively being used as an active damping control in various domains such as robotics, smart structure, etc. However, existence of noise in wide-area signal makes an ideal PD compensator unrealisable in power systems. In this endeavour, a new methodology christened as time-delayed control is proposed where artificial delay is used to provide derivative action which acts as a damping component of wide-area controller. The delay margin is computed for the closed loop system using Razumikhin approach. It is observed that the proposed controller is able to damp the oscillations adequately with reduced sensitivity to the noise in the signals. Further, the proposed controller is able to provide robustness against uncertainties arising from the system dynamics and inherent delay in communication channel. [ABSTRACT FROM AUTHOR]

Uncertainty and disturbance are common in a planar snake robot model due to its structural complexity and variation in system parameters. To achieve efficient head angle and velocity tracking with least computational complexity and unknown uncertainty bounds, a time-delayed control (TDC) scheme has been presented in this paper. A Serpenoid gait function is being tracked by the joint angles utilizing virtual holonomic constraints (VHCs) method. The first layer of TDC has been proposed for stabilizing the VHC dynamics to the origin. Once the VHCs are satisfied, the system is said to be on the constraint manifold. The second layer of TDC has been applied to an output system defined over the reduced order dynamics on the constrained manifold. To establish the robustness of the control approach through simulation, uncertainty in the friction coefficients is considered to be time-varying emulating change in the ground conditions. Simulation results and Lyapunov stability analysis affirm the uniformly ultimately bounded stability of the robot employing the proposed approach. [ABSTRACT FROM AUTHOR]

The concept of discrete-time higher order sliding mode (DHOSM) has received increased attention. However, because of the dearth of knowledge on bound of the external disturbance in the system, an adaptive control law is desirable. This brief presents a technique to design a DHOSM control with adaptive switching gains where the bound on the disturbance is considered to be unknown. [ABSTRACT FROM AUTHOR]

In this paper, the tracking control problem of an Euler–Lagrange system is addressed with regard to parametric uncertainties, and an adaptive-robust control (ARC) strategy, christened time-delayed ARC (TARC), is presented. TARC approximates the unknown dynamics through the time-delayed estimation, and the ARC provides robustness against the approximation error. The novel adaptation law of TARC, in contrast to the conventional ARC methodologies, requires neither complete model of the system nor any knowledge of predefined uncertainty bounds to compute the switching gain, and circumvents the overestimation and underestimation problems of the switching gain. Moreover, TARC only utilizes position feedback and approximates the velocity and acceleration terms from the past position data. The adopted state-derivatives estimation method in TARC avoids any explicit requirement of external low-pass filters for the removal of measurement noise. A new stability notion in the continuous-time domain is proposed considering the time delay, adaptive law, and state-derivatives estimation, which in turn provides a selection criterion for gains and sampling interval of the controller. Experimental results of the proposed methodology using a multiple degrees-of-freedom robot are presented, and improved tracking accuracy of the proposed control law is demonstrated compared with the conventional adaptive sliding mode control. [ABSTRACT FROM AUTHOR]

This brief proposes a new adaptive–robust control (ARC) architecture for a class of uncertain Euler–Lagrange (EL) systems where the upper bound of the uncertainty satisfies linear in the parameters structure. Conventional ARC strategies either require structural knowledge of the system or presume that the overall uncertainties or its time derivative are norm bounded by a constant. Due to the unmodeled dynamics and modeling imperfection, true structural knowledge of the system is not always available. Furthermore, for the class of systems under consideration, prior assumption, regarding the uncertainties (or its time derivative) being upper bounded by a constant, puts a restriction on the states beforehand. Conventional ARC laws invite overestimation–underestimation problem of switching gain. Toward this front, adaptive switching-gain-based robust control (ASRC) is proposed, which alleviates the overestimation–underestimation problem of switching gain. Moreover, ASRC avoids any presumption of constant upper bound on the overall uncertainties and can negotiate uncertainties regardless of being linear or nonlinear in parameters. Experimental results of ASRC using a wheeled mobile robot note improved control performance in comparison with the adaptive sliding mode control. [ABSTRACT FROM AUTHOR]

This paper proposes a new adaptive-robust control (ARC) strategy for a tracking control problem of a class of uncertain Euler–Lagrange systems. The proposed adaptive-robust time-delay control (ARTDC) amalgamates the ARC strategy with the time-delay control (TDC). It comprises three parts: a time-delay estimation part, a desired dynamics injection part, and an adaptive-robust part. The main feature of the proposed ARTDC is that it does not involve any threshold value in its adaptive law; thus, it allows the switching gain to increase or decrease whenever the error trajectories move away or close to the switching surface, respectively. Thus, compared with the existing ARC schemes, ARTDC is able to alleviate the over- and underestimation problems of the switching gain. Moreover, the stability analysis of ARTDC provides an upper bound for the selection of sampling interval and its relation with controller gains. The proposed ARTDC shows improved tracking performance compared with the TDC and the existing adaptive sliding-mode control in simulations as well as in experiments with a multiple-degree-of-freedom system. [ABSTRACT FROM PUBLISHER]

In this article, a robust hybrid control method is presented for efficient path tracking control of a nonholonomic wheeled mobile robotic system under parametric and nonparametric variations. The present control law is a paradigm shift to control a wheeled mobile robot over a predefined trajectory by fusing the best features of the switching control logic as well as time-delayed control logic. The proposed hybrid control strategy aims at reducing the effort required for modeling the complex wheeled mobile robotic systems by approximating the unknown dynamics using input and feedback information of past time instances. Furthermore, the proposed methodology significantly reduces the approximation error arising from finite time-delay through the switching logic without any prior knowledge of the uncertainty bound. A new stability analysis for the time-delayed control is proposed which establishes an analytical relation between the controller performance and the approximation error. Performance of the proposed hybrid controller is tested with a real-life wheeled mobile robot and improved tracking performance is observed compared to conventional robust control strategies even with the incorporation of dynamic parametric uncertainties. [ABSTRACT FROM AUTHOR]

Recursive least squares (RLS) for control, which is tackled by Baldi, Zhang, and Liu in the framework of Recursive Least Squares-Temporal Difference (RLS-TD), using an instrumental variable perspective. As compared to conventional adaptive control, robust adaptive control aims to provide robustness against unmodeled dynamics, coupling effects, and other endogenous and exogenous disturbances. State-dependent uncertainties without a priori bounds: Shukla, Roy, and Gupta consider an adaptive control problem in which the uncertainties cannot be bounded a priori by any constant, but should be tackled in their state-dependent nature. [Extracted from the article]

The literature has proven that attaining good transient behavior in leakage-based robust adaptive control of uncertain switched systems is intrinsically challenging. In fact, because the gains of the inactive subsystems must exponentially vanish during inactive times as an effect of leakage action, new learning transients will repeatedly arise at each switching instant. In this paper, a new leakage-based mechanism is designed for robust adaptive control of uncertain switched systems: in contrast to the available designs, the key innovation of the proposed one is that the adaptive gains of the inactive subsystems can be kept constant to their switched-off values, thus preventing vanishing gains. Bounded stability of the closed-loop switched system is guaranteed thanks to the introduction of an auxiliary gain playing the role of leakage. A benchmark example commonly adopted in adaptive switched literature shows that the proposed strategy can consistently improve the transient behavior under various families of switching signals. [ABSTRACT FROM AUTHOR]

Available control methods for underactuated Euler–Lagrange (EL) systems rely on structure-specific constraints that may be appropriate for some systems, but restrictive for others. A generalized (structure-independent) control framework is to a large extent missing, especially in the presence of uncertainty. This paper introduces an adaptive-robust control framework for a quite general class of uncertain underactuated EL systems. Compared to existing literature, the important attributes of the proposed solution are: (i) avoiding structure-specific restrictions, namely, symmetry condition property of the mass matrix, and a priori bounds on non-actuated states or state derivatives; (ii) considering Coriolis, centripetal, friction and gravity terms to be unknown, while only requiring the knowledge of maximum perturbation around a nominal value of the mass matrix; (iii) handling state-dependent uncertainties irrespective of their linear or nonlinear in parameters structure. These features significantly widen the range of underactuated EL systems the proposed solution can handle in comparison to the available methods. Stability is studied analytically and the performance is verified in simulation using offshore boom crane dynamics. [ABSTRACT FROM AUTHOR]

Adaptive Sliding Mode Control (ASMC) aims to adapt the switching gain in such a way to cope with possibly unknown uncertainty. In state-of-the-art ASMC methods, a priori boundedness of the uncertainty is crucial to ensure boundedness for the switching gain and uniformly ultimately boundedness. A priori bounded uncertainty might impose a priori bounds on the system state before obtaining closed-loop stability. A design removing this assumption is still missing in literature. A positive answer to this quest is given by this note where a novel ASMC methodology is proposed which does not require a priori bounded uncertainty. An illustrative example is presented to highlight the main features of the approach, after which a general class of Euler–Lagrange systems is taken as a case study to show the applicability of the proposed design. [ABSTRACT FROM AUTHOR]