Internal Model Design Research Articles

Design of Internal Supervision Model for Educational Fund Management at the First-Level Middle School in Mamuju Regency

This study is a Research and Development (R&D) study developed by Borg and Gall, aiming to design a model for Internal Supervision in Educational Fund Management at the First-Level Middle School (SMP) in Mamuju Regency. The aspects discussed are the consulting aspect with indicators of socialization of School Operational Assistance (BOS) funds and community complaint services. The internal control system aspect of educational units (SPISP) with indicators of planning, process, and evaluation. The assurance aspect with indicators of review and audit. The research location is all SMPs in Mamuju Regency, consisting of 65 schools, and 30 school principals were selected as respondents. The research data was obtained by providing instruments/ questionnaires through focus group discussions (FGD) with the SMP School Committee, with emphasis on the pre-test and post-test processes. The data analysis technique used is descriptive quantitative and qualitative statistics, as well as N-Gain increase analysis, which shows that the effectiveness of this model design is quite effective with a value of 0.7.

Data-driven Output Regulation via Gaussian Processes and Luenberger Internal Models

This paper deals with the problem of adaptive output regulation for multivariable nonlinear systems by presenting a learning-based adaptive internal model-based design strategy. The approach builds on the recently proposed adaptive internal model design techniques based on the theory of nonlinear Luenberger observers, and the adaptation side is approached as a probabilistic regression problem. Unlike the previous approaches in the field, here only coarse assumptions about the friend structure are required, making the proposed approach suitable for applications where the exosystem is highly uncertain. The paper presents performance bounds on the attained regulation error and numerical simulations showing how the proposed method outperforms previous approaches.

Top management team internal social capital, market dynamics and business model design: a dynamic managerial capability perspective

PurposeDrawing on the dynamic managerial capability perspective and the dynamic capability perspective of business model (BM) literature, this paper aims to investigate how top management team internal social capital (TISC) promotes BM design and how such effects are moderated by market dynamics (i.e. demand uncertainty and competitive intensity).Design/methodology/approachThe proposed hypotheses were tested by a questionnaire-based survey. The empirical study was conducted on a sample of 210 firms in China. The model was tested via hierarchical regression analysis.FindingsTISC has a positive effect on BM efficiency but an inverted U-shaped effect on BM novelty. The effects of TISC on BM efficiency and novelty are contingent on demand uncertainty and competitive intensity in different ways. Specifically, this study finds that demand uncertainty strengthens the inverted U-shaped effect of TISC on BM novelty. This study also finds that competitive intensity strengthens the positive effect of TISC on BM efficiency but weakens the inverted U-shaped effect of TISC on BM novelty.Originality/valueThe conclusion contributes to the dynamic capability perspective of BM literature in two ways. First, it offers a dynamic managerial capability perspective for understanding the antecedents of BM design. It highlights TISC, a root of dynamic managerial capability, as an important internal antecedent of BM design. Second, it provides a more nuanced understanding of the role of TISC in BM design. The findings show the distinct effects of TISC on BM efficiency and novelty. This study also discusses the contingency role market dynamics play in the TISC–BM design relationship.

Adaptive Control on SE(3) for Spacecraft Pose Tracking With Harmonic Disturbance and Input Saturation

This article investigates the coupled attitude and orbit tracking maneuver control problem of a spacecraft system in close space missions with model uncertainty, unknown disturbance, and input saturation. An adaptive compact control scheme with featuring of disturbance rejection and antiwindup is reported. First, the exponential coordinates on Lie group SE(3) are employed to describe the relative pose, which includes the relative position and attitude, and the tracking error system is established by introducing an instrumental error variable, which contains exponential coordinates and velocity tracking error. Then, a dynamic disturbance compensator is constructed based on the idea of internal model design to finely compensate for a class of unknown harmonic disturbances. Furthermore, a nonsingular auxiliary system is proposed to overcome input saturation, in which a time-varying parameter is introduced to improve the performance of the antiwindup auxiliary system. This parameter makes the closed-loop system possess two properties: the timeliness of saturation compensation and the asymptotic convergence of tracking errors. With the developed control law, the stability of the obtained feedback system is strictly proved by means of Lyapunov stability theory. Finally, the numerical simulation is carried out for an on-orbit servicing mission, which validates the effectiveness of the proposed integrated controller in solving the pose tracking control problem.

An internal‐model‐based event‐triggered strategy for rendezvous with connectivity preservation problem of multi‐agent systems

AbstractIn this article, an internal‐model‐based event‐triggered control is proposed for the rendezvous problem of linear uncertain multi‐agent systems. Our approach is not only robust to parametric uncertainty and external disturbances, but also capable of preserving the connectivity of the position‐dependent time‐varying communication network. The event‐triggered mechanism is in a piecewise constant form and thus can be directly implemented in the digital platform. Technically, different from traditional internal model design, a class of distributed dynamic compensators are designed based on sampled relative position and velocity signals to convert the rendezvous problem into a stabilization with connectivity problem of a special augmented system, which is then solved by a piecewise constant stabilizer. Finally, it is proved that the rendezvous problem of the original system is solvable by stabilizing such augmented system and excluding Zeno behavior.

Nonlinear exogeneous system and internal model design

Nonlinear exogeneous system and internal model design

Managerial Internal Social Capital, Environmental Dynamism, and Business Model Design

Drawing on business model and dynamic managerial capability literature, this paper explores how managerial internal social capital impacts business model design under environmental dynamism. Based ...

A Novel Connectivity-Preserving Control Design for Rendezvous Problem of Networked Uncertain Nonlinear Systems.

This article proposes a novel and robust connectivity-preserving rendezvous control design for a group of uncertain nonlinear multiagent systems with communication constraint where each agent has a limited sensing range. The control design can work under the assumption that the communication network is initially connected and is characterized by two distinguishing features. First, a new potential function is provided not only to maintain the existing and newly added links by the hysteresis rule but also to overcome the difficulty imposed by the nonlinear terms from system dynamics. Second, by constructing a series of lemmas, a connectivity-preserving stabilizing control law is presented to solve the robust stabilization problem with connectivity preservation for a time-varying nonlinear system, which is a special case of the augmented system with both dynamic and static uncertainties obtained via internal model design. After further incorporating the adaptive control technique, regardless of uncertain parameters and external disturbances in the multiple nonlinear subsystems, the leader-following rendezvous with connectivity preservation problem is finally solved by a distributed connectivity-preserving controller with parameter update law.

“Class-Type” Identification-Based Internal Models in Multivariable Nonlinear Output Regulation

The paper deals with the problem of output regulation in a "non-equilibrium" context for a special class of multivariable nonlinear systems stabilizable by high-gain feedback. A post-processing internal model design suitable for the multivariable nature of the system, which might have more inputs than regulation errors, is proposed. Uncertainties in the system and exosystem are dealt with by assuming that the ideal steady state input belongs to a certain "class of signals" by which an appropriate model set for the internal model can be derived. The adaptation mechanism for the internal model is then cast as an identification problem and a least square solution is specifically developed. In line with recent developments in the field, the vision that emerges from the paper is that approximate, possibly asymptotic, regulation is the appropriate way of approaching the problem in a multivariable and uncertain context. New insights about the use of identification tools in the design of adaptive internal models are also presented.

Internal models for deposits: Effects on banks' capital and interest rate risk of assets

This study first investigates why only some banks use the internal models (IMs) introduced by Basel II that lead to more risk-sensitive capital ratios than standardized approaches (SA). I predict that banks opt for an IM if it allows economizing on capital requirements, given their underlying risk. I find support for this hypothesis by analyzing Mexican banks’ adoption of an IM for deposit maturity, a key input to measure interest rate risk, between 2006 and 2016. Secondly, I examine whether banks increase the duration of assets after IM adoption—high-maturity assets can be offset with deposits, leading to a lower risk exposure and additional capital savings. For the average maturity of total assets, I find no support for this conjecture. However, when a flattening of the yield curve spurs firms’ demand for high-maturity debt, micro data reveal that banks using the IM increase the duration of commercial loans more than those using the SA. These findings have broad implications for the design of internal risk models and of capital regulation.

Robust Output Regulation of Linear Systems by Event-Triggered Dynamic Output Feedback Control

In this article, we study the robust output regulation problem of linear systems by an event-triggered output feedback control law. We first summarize the solvability of the linear robust output regulation problem by the internal model design. Then, we implement this continuous-time control law by an event-triggered output feedback control law together with an output-based triggering mechanism. We show that, under almost the same solvability conditions as those for the linear robust output regulation problem, the robust output regulation problem can also be solved by an event-triggered output feedback control law without incurring Zeno phenomenon. Furthermore, we show that, it is possible to solve the robust output regulation problem practically while preventing the interevent time from approaching zero as time tends to infinity.

Output regulation by postprocessing internal models for a class of multivariable nonlinear systems

SummaryIn this paper we propose a new design paradigm, which employs a postprocessing internal model unit, to approach the problem of output regulation for a class of multivariable minimum‐phase nonlinear systems possessing a partial normal form. Contrary to previous approaches, the proposed regulator handles control inputs of dimension larger than the number of regulated variables, provided that a controllability assumption holds, and can employ additional measurements that need not to vanish at the ideal error‐zeroing steady state, but that can be useful for stabilization purposes or to fulfill the minimum‐phase requirement. Conditions for practical and asymptotic output regulation are given, underlying how in postprocessing schemes the design of internal models is necessarily intertwined with that of the stabilizer.

Rendezvous problem of multiple linear uncertain systems under state-dependent dynamic networks

This paper studies the rendezvous problem for a class of linear systems with uncertain parameters and external disturbances under the state-dependent dynamic network, which is also called rendezvous network here. By combining potential function technique, distributed internal model design and adaptive control technique, a distributed adaptive state feedback control law is proposed to solve the rendezvous problem by completing the tasks of maintaining the connectivity of the rendezvous network, achieving asymptotic tracking, rejecting unknown external disturbances as well as handling uncertain parameters in the system dynamics, the leader system and the exosystem simultaneously.

Digital Noninterleaved High-Power Totem Pole PFC Based on Internal Model Design

When the control signal u(t) of totem pole PFC with GaN HEMTs is a function of measurable state variables, the state feedback gain matrix can be determined by applying state variable feedback control with Ackerman formula, so that the poles of closed-loop system can be allocated to the desired position. This correction method is especially beneficial to optimal system control according to performance requirements. By introducing the internal model of reference input, a state space function including the first-order and second-order differential of error is constructed; this novel controller makes controlled system track the reference input signal progressively with zero steady-state error. A 4 kW PFC prototype is designed to verify this design method.

Design of Adaptive Internal Control Model on Binary Distillation Column

The binary distillation column is one of the most important operating units in chemical engineering. Wood & Berry binary distillation columns separate feed streams (F, XF) into top products (D, XD) and bottom products (B, XB). The control design in the binary distillation column has several constraints caused by non-linearity of the process, multivariable interactions, and presence of a disturbance. Based on that constraints, it needs a modern control method that can make the system response to track the set point change and reduce or eliminate the disturbances, so the product composition output as desired. Adaptive Internal Model Control 2 Degree of Freedom (AIMC 2 DoF) method is one of the modern control methods that are capable of controlling multivariable plants and reduce or eliminate existing disturbances. Based on all the tests performed, the AIMC 2 DoF controller using Skogestad filter parameter tuning method has the smallest IAE value compared to the other methods.

Modelling Demand Deposits and Interest Rate Risk Sharing: Lessons from the Mexican Banking Regulation

This study first investigates why only some banks use the internal models (IMs) introduced by Basel II that lead to more risk-sensitive capital ratios than standardized approaches (SA). I predict that banks opt for an IM if it allows economizing on capital requirements, given their underlying risk. I find support for this hypothesis by analyzing Mexican banks' adoption of an IM for deposit maturity, a key input to measure interest rate risk, between 2006 and 2016. Secondly, I examine whether banks increase the duration of assets after IM adoption—high-maturity assets can be offset with deposits, leading to a lower risk exposure and additional capital savings. For the average maturity of total assets, I find no support for this conjecture. However, when a flattening of the yield curve spurs firms' demand for high-maturity debt, micro data reveal that banks using the IM increase the duration of commercial loans more than those using the SA. These findings have broad implications for the design of internal risk models and of capital regulation.

Speed Tracking Control of Permanent Magnet Synchronous Motor by a Novel Two-step Internal Model Control Approach

The control problem of permanent magnet (PM) synchronous motor has attracted extensive attentions in both control society and industrial applications. Much recently, a local speed tracking and nonlinear disturbance rejection problem of PM synchronous motor was investigated by nonlinear internal model design. In this paper, we propose a novel two-step controller design strategy to achieve speed tracking and nonlinear disturbance rejection of PM synchronous motor with wide speed range, which combines the advantages of classical double-loop control and nonlinear internal model control. It is worth mentioning that the proposed two-step controller design strategy can not only guarantee exact speed tracking with wide speed range, but also reject small nonlinear external disturbances in the load torque, generated by a so-called nonlinear exosystem. Simulation results demonstrate the effectiveness of our design.

Cooperative global robust output regulation for a class of nonlinear multi-agent systems by distributed event-triggered control

This paper studies the event-triggered cooperative global robust output regulation problem for a class of nonlinear multi-agent systems via a distributed internal model design. We show that our problem can be solved practically in the sense that the ultimate bound of the tracking error can be made arbitrarily small by adjusting a design parameter in the proposed event-triggered mechanism. Our result offers a few new features. First, our control law is robust against both external disturbances and parameter uncertainties, which are allowed to belong to some arbitrarily large prescribed compact sets. Second, the nonlinear functions in our system do not need to satisfy the global Lipschitz condition. Thus our systems are general enough to include some benchmark nonlinear systems that cannot be handled by existing approaches. Finally, our control law is a specific distributed output-based event-triggered control law, which lends itself to a direct digital implementation.

A nonlinear internal model design for heterogeneous second-order multi-agent systems with unknown leader

This paper focuses on robust nonlinear coordination of heterogeneous uncertain second-order multi-agent systems subject to directed communication topologies. We develop a nonlinear internal model principle based approach for the problem in a framework of cooperative global robust output regulation, independent of the a priori of the leader dynamics information except its order. As a major consequence, this study assures, by means of establishing a strict-Lyapunov function for the closed-loop system, not only a specified exponential convergence rate but also tolerable bounds of unmodeled disturbances. Hence, the former guarantees an appealing performance and the latter an important robustness property.

Internal model approach to cooperative robust output regulation for linear uncertain time‐delay multiagent systems

SummaryIn this paper, we study the cooperative robust output regulation problem for linear uncertain multiagent systems with both communication delay and input delay by the distributed internal model approach. The problem includes the leader‐following consensus problem of linear multiagent systems with time delay as a special case. We first generalize the internal model design method to systems with both communication delay and input delay. Then, under a set of standard assumptions, we have obtained the solution to the problem via both the state feedback control law and the output feedback control law. In contrast to the existing results, our results apply to general linear uncertain multiagent systems, accommodate a large class of leader signals, and achieve asymptotic tracking and disturbance rejection at the same time.