Funnel cruise control

Berger, Toby; Rauert, Anna-Lena

doi:10.1016/j.automatica.2020.109061

Cited by 37 publications

(22 citation statements)

References 30 publications

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“…If the funnel controller (9) is applied to a system (1), then the first issue is to prove the existence of solutions of the closed-loop initial-value problem and to establish the efficacy of the control. We stress that the proof is quite delicate-even in the case of linear systems of the form (13). The reason is that the function α used in the feedback (9) introduces a potential singularity on the right hand side of the closed-loop differential equation.…”

Section: Funnel Control: Main Resultsmentioning

confidence: 99%

“…The new funnel control strategy has a potential impact on various applications. Since its development in [30], the funnel controller proved an appropriate tool for tracking problems in various applications such as temperature control of chemical reactor models [33], control of industrial servo-systems [24] and underactuated multibody systems [9], speed control of wind turbine systems [21,23], current control for synchronous machines [22], DC-link power flow control [52], voltage and current control of electrical circuits [14], oxygenation control during artificial ventilation therapy [45], control of peak inspiratory pressure [46] and adaptive cruise control [12,13].…”

Section: Applicationsmentioning

confidence: 99%

“…We show that system (13) can be equivalently written in the form (1), if system (13) has (strict) relative degree r ∈ N, that is C A k B = 0, k = 0, . .…”

Section: Strict Relative Degreementioning

confidence: 99%

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Funnel control of nonlinear systems

Berger

Ilchmann

Ryan

2021

Math. Control Signals Syst.

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Tracking of reference signals is addressed in the context of a class of nonlinear controlled systems modelled by r-th-order functional differential equations, encompassing inter alia systems with unknown “control direction” and dead-zone input effects. A control structure is developed which ensures that, for every member of the underlying system class and every admissible reference signal, the tracking error evolves in a prescribed funnel chosen to reflect transient and asymptotic accuracy objectives. Two fundamental properties underpin the system class: bounded-input bounded-output stable internal dynamics, and a high-gain property (an antecedent of which is the concept of sign-definite high-frequency gain in the context of linear systems).

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Section: Funnel Control: Main Resultsmentioning

confidence: 99%

Section: Applicationsmentioning

confidence: 99%

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Funnel control of nonlinear systems

Berger

Ilchmann

Ryan

2021

Math. Control Signals Syst.

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“…The funnel controller was already successfully applied, e.g. in temperature control of chemical reactor models [40], DC-link power flow control [50], voltage and current control of electrical circuits [17], control of peak inspiratory pressure [48], adaptive cruise control [15,16] and control of industrial servo-systems [36] and underactuated multibody systems [14]. The present work is organized as follows.…”

Section: Control Methodologymentioning

confidence: 99%

“…where b 5 is some appropriate function,S(•) = S Φ −1 (0, •) , and the internal dynamics are completely decoupled in (16).…”

Section: The General Casementioning

confidence: 99%

Tracking control for underactuated non-minimum phase multibody systems

et al. 2021

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We consider tracking control for multibody systems which are modeled using holonomic and non-holonomic constraints. Furthermore, the systems may be underactuated and contain kinematic loops and are thus described by a set of differential-algebraic equations that cannot be reformulated as ordinary differential equations in general. We propose a control strategy which combines a feedforward controller based on the servo-constraints approach with a feedback controller based on a recent funnel control design. As an important tool for both approaches, we present a new procedure to derive the internal dynamics of a multibody system. Furthermore, we present a feasible set of coordinates for the internal dynamics avoiding the effort involved with the computation of the Byrnes–Isidori form. The control design is demonstrated by a simulation for a nonlinear non-minimum phase multi-input, multi-output robotic manipulator with kinematic loop.

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Neuro‐adaptive practical prescribed‐time control for pure‐feedback nonlinear systems without accurate initial errors

Tan

2023

Adaptive Control & Signal

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Summary This article studies the problem of practical prescribed‐time tracking for pure‐feedback nonlinear systems, where the transient behavior, steady‐state precision, settling time as well as the rate of convergence can be preset irrespective of initial conditions. With the help of a time‐dependent function and a state‐dependent function, a simple coordinate transformation is established to construct a neuro‐adaptive controller to achieve the tracking purpose. In particular, the proposed controller does not need to update the design parameters in accordance with different initial conditions, which makes the controller more versatile. The effectiveness of the proposed method is illustrated through two practical systems, namely, a continuous stirred tank reactor (CSTR), and a robotic system.

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Funnel cruise control

Cited by 37 publications

References 30 publications

Funnel control of nonlinear systems

Funnel control of nonlinear systems

Tracking control for underactuated non-minimum phase multibody systems

Neuro‐adaptive practical prescribed‐time control for pure‐feedback nonlinear systems without accurate initial errors

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