Yet Another Tutorial of Disturbance Observer: Robust Stabilization and Recovery of Nominal Performance

This paper presents a tutorial-style review on the recent results about the disturbance observer (DOB) in view of robust stabilization and recovery of the nominal performance. The analysis is based on the case when the bandwidth of Q-filter is large, and it is explained in a pedagogical manner that, even in the presence of plant uncertainties and disturbances, the behavior of real uncertain plant can be made almost similar to that of disturbance-free nominal system both in the transient and in the steady-state. The conventional DOB is interpreted in a new perspective, and its restrictions and extensions are discussed

Robust nonlinear control of vectored thrust aircraft

An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations

Fuzzy control turns 50: 10 years later

In 2015, we celebrate the 50th anniversary of Fuzzy Sets, ten years after the main milestones regarding its applications in fuzzy control in their 40th birthday were reviewed in FSS, see [1]. Ten years is at the same time a long period and short time thinking to the inner dynamics of research. This paper, presented for these 50 years of Fuzzy Sets is taking into account both thoughts. A first part presents a quick recap of the history of fuzzy control: from model-free design, based on human reasoning to quasi-LPV (Linear Parameter Varying) model-based control design via some milestones, and key applications. The second part shows where we arrived and what the improvements are since the milestone of the first 40 years. A last part is devoted to discussion and possible future research topics.Guerra, T.; Sala, A.; Tanaka, K. (2015). Fuzzy control turns 50: 10 years later. Fuzzy Sets and Systems. 281:162-182. doi:10.1016/j.fss.2015.05.005S16218228

A flexible mixed-optimization with H∞ control for coupled twin rotor MIMO system based on the method of inequality (MOI)- An Experimental Study

This article introduces a cutting-edge H∞ model-based control method for uncertain Multi Input Multi Output (MIMO) systems, specifically focusing on UAVs, through a flexible mixed-optimization framework using the Method of Inequality (MOI). The proposed approach adaptively addresses crucial challenges such as unmodeled dynamics, noise interference, and parameter variations. Central to the design is a two-step controller development process. The first step involves Nonlinear Dynamic Inversion (NDI) and system decoupling for simplification, while the second step integrates H∞ control with MOI for optimal response tuning. This strategy is distinguished by its adaptability and focus on balancing robust stability and performance, effectively managing the intricate cross-coupling dynamics in UAV systems. The effectiveness of the proposed approach is validated through simulations conducted in MATLAB/Simulink environment. Results demonstrated the efficiency of the proposed robust control approach as evidenced by reduced steady-state error, diminished overshoot, and faster system response times, thus significantly outperforming traditional control methods

Output feedback control and robustness in the gap metric

Zusammenfassung Mueller, Markus: Output feedback control and robustness in the gap metric Ilmenau : Univ.-Verl. Ilmenau, 2009. - 254 S. ISBN 978-3-939473-60-2 Die vorgelegte Arbeit behandelt den Entwurf und die Robustheit von drei verschiedenen Regelstrategien für lineare Differentialgleichungssysteme mit mehrdimensionalen Ein- und Ausgangssignalen (MIMO): Stabilisierung durch Ausgangs-Ableitungs-Rückführung, Lambda-tracking und Funnel-Regelung. Damit diese Regler bei der Anwendung auf ein lineares System die gewünschten Stabilisierung/Regelung erbringen, ist eine explizite Kenntnis der Systemmatrizen nicht notwendig. Es müssen nur strukturelle Eigenschaften des Systems bekannt sein: der Relativgrad, dass das System minimalphasig ist, und dass die sogenannte "high-frequency gain" Matrix positiv definit ist. Diese stukturellen Eigenschaften werden für MIMO-Systeme in den ersten Kapiteln der Arbeit ausführlich behandelt. Für MIMO-Systeme mit nicht striktem Relativgrad wird eine Normalform hergeleitet, die die gleichen Eigenschaften wie die bekannte Normalform für SISO-Systeme oder MIMO-Systeme mit striktem Relativgrad aufweist. Die Normalform sowie Minimalphasigkeit und Positivität der "high-frequency gain" Matrix bilden die Grundlage dafür, dass die oben genannten Regelstrategien Systeme mit diesen Eigenschaften im jeweiligen Sinn stabilisieren. Robustheit bzw. robuste Stabilisierung beschreibt folgendes Prinzip: falls ein geschlossener Kreis aus einem linearen System und einem Regler in gewissem Sinne stabil ist und die Gap-Metrik (der Abstand) zwischen dem im geschlossenen Kreis betrachteten System und einem anderen "neuen" System hinreichend klein ist, so ist der geschlossene Kreis aus dem "neuen" System und dem gleichen Regler wieder stabil. Die gleiche Aussage stimmt auch für den Fall, dass man den Regler und nicht das System austauscht. Für Ausgangs-Ableitungs-Rückführung wird gezeigt, dass, falls diese ein System stabilisiert, die auftretenden Ableitungen des Ausgangs durch Euler-Approximationen der Ableitungen ersetzt werden können, falls diese hinreichend genau sind. Für Lambda-tracking und Funnel-Regelung wird gezeigt, dass beide Regler auch für die Stabilisierung linearer Systeme verwendet werden können, die einen geringen Abstand zu einem System haben, dass die o.g. Voraussetzungen erfüllt, selbst diese Voraussetzungen aber nicht erfüllen.Abstract: This dissertation considers the design and robustness analysis of three different control strategies for linear systems of differential equations with multidimensional input and output signals (MIMO): high-gain output derivative feedback control, lambda-tracking and funnel control. To apply these control strategies to linear systems and achieve the desired control objectives (stabilization or tracking), the explicit system's data needs not to be known, but certain structural properties of the systems are required. The system's relative degree must be known, the system must be minimum phase and the so-called "high-frequency gain" matrix must be positive definite. These properties are considered in detail for linear MIMO-systems with non-strict relative degree. A normal form is developed which has the same properties as the well-known normal form for SISO-systems or MIMO-systems with strict relative degree. Normal form, minimum phase property and positivity of the high-frequency gain matrix are the crucial assumptions for the application of the control strategies mentioned above. It is shown that each controller achieves certain control objectives when applied to any system which satisfies these assumptions. The result on robustness and robust stability are as follows: if a closed-loop system represented by the application of a controller to a linear plant is stable (in some sense), and the gap metric (i.e. the distance) between the stabilised system and a different "new" system is sufficiently small, then the closed-loop system represented by the application of the controller to the "new" system is again stable. This conclusion holds also true when changing the roles of system and controller. For high-gain output derivative feedback control it is shown that the controller still stabilizes a system when the derivatives of the output are replaced by Euler approximations of the derivatives, provided the approximation is sufficiently precise. For lambda-tracking and funnel control it is shown that both controllers may be applied to systems which are "close" (in terms of a small gap) to any system from the class of minimum phase systems, with relative degree one and positive definite high-frequency gain matrix, but not necessarily satisfy any of these assumptions

Optimal Output Modification and Robust Control Using Minimum Gain and the Large Gain Theorem

When confronted with a control problem, the input-output properties of the system to be controlled play an important role in determining strategies that can or should be applied, as well as the achievable closed-loop performance. Optimal output modification is a process in which the system output is modified in such a manner that the modified system has a desired input-output property and the modified output is as similar as possible to a specified desired output. The first part of this dissertation develops linear matrix inequality (LMI)-based optimal output modification techniques to render a linear time-invariant (LTI) system minimum phase using parallel feedforward control or strictly positive real by linearly interpolating sensor measurements. H-ininifty-optimal parallel feedforward controller synthesis methods that rely on the input-output system property of minimum gain are derived and tested on a numerical example. The H2- and H-infinity-optimal sensor interpolation techniques are implemented in numerical simulations of noncolocated elastic mechanical systems. All mathematical models of physical systems are, to some degree, uncertain. Robust control can provide a guarantee of closed-loop stability and/or performance of a system subject to uncertainty, and is often performed using the well-known Small Gain Theorem. The second part of this dissertation introduces the lessor-known Large Gain Theorem and establishes its use for robust control. A proof of the Large Gain Theorem for LTI systems using the familiar Nyquist stability criterion is derived, with the goal of drawing parallels to the Small Gain Theorem and increasing the understanding and appreciation of this theorem within the control systems community. LMI-based robust controller synthesis methods using the Large Gain Theorem are presented and tested numerically on a robust control benchmark problem with a comparison to H-infinity robust control. The numerical results demonstrate the practicality of performing robust control with the Large Gain Theorem, including its ability to guarantee an uncertain closed-loop system is minimum phase, which is a robust performance problem that previous robust control techniques could not solve.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143934/1/caverly_1.pd