Lyapunov‐stable Discrete‐time Model Reference Adaptive Control

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solidThinking Embed em projetos de controle para sistemas

(Model Reference Adaptive Control - MRAC). O principal objetivo dessa metodologia é desenvolver um controlador em malha-fechada que faça com que uma planta, cujos parâmetros podem não ser conhecidos, se comporte como um modelo de referência de parâmetros conhecidos e cuja dinâmica é projetada. Os parâmetros

On Direct Adaptive Control for Uncertain Dynamical Systems

There were considerable amount of discrete-time adaptive results have been published. For example, discrete-time neural net adaptive controller was de-picted in (Levin & Narendra, 1996), the MIT rule for adaptive control refers to the combination of model reference cont rol together with a gradient type pa-

Safe learning and control in complex systems

Safe learning and control in complex systems called tube-based model predictive control and then combine it with an adaptive reducing the model mismatch. Our

Lyapunov-stable discrete-time model reference adaptive control

Lyapunov-stable discrete-time model reference adaptive control S. Akhtarn,y and D. S. Bernstein Department of Aerospace Engineering, The University of Michigan, Ann Arbor, MI 48109-2140, U.S.A. SUMMARY Discrete-time model reference adaptive control (MRAC) is considered with both least squares and projection algorithm parameter identification.

A Lyapunov-based adaptive control framework for discrete-time

time adaptive control theory. As a result, most of the discrete-time adaptive model reference and tracking control results are based on the classical key technical lemma which does not guarantee Lyapunov stability. In this paper, using a logarithmic Lyapunov function we develop a Lyapunov-based direct adaptive control

Robust Sampled-Data Adaptive Control of the Rohrs Counterexamples

3]. Nevertheless, adaptive control continued to be develop ed and applied to a vast range of applications [4 6]. The purpose of the present paper is to revisit both Rohrs counterexamples using retrospective cost adaptive contro l (RCAC). RCAC is a discrete-time, direct adaptive control technique that can be used for plants that are possibly

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Received:7May2019 Revised:4February2020 Accepted:16March2020 DOI:10.1002/acs.3114 RESEARCH ARTICLE Improving transient performance of discrete-time model reference adaptive contro

Lyapunov-Stable Discrete-Time Model Reference Adaptive Control

Lyapunov-Stable Discrete-Time Model Reference Adaptive Control Suhail Akhtar 1and Dennis S. Bernstein Department of Aerospace Engineering, The University of Michigan, Ann Arbor, MI 48109-2140, [email protected] Abstract Discrete-time model reference adaptive control (MRAC) has been studied extensively. Although the framework

Quadrotor Flight Controller Design Using Classical Tools

An adaptive sliding mode control design has been addressed in, e.g. [11,12]. A self-tuning attitude and altitude control scheme has been derived in [13]. In [14] an H ¥ based feedback linearisa-tion control scheme has been discussed. Lyapunov ap-proach to control system design has been used in [15]. A robust (Lyapunov stable) proportional

DISCRETE-TIME FUZZY MODELLING AND PARALLEL DISTRIBUTED

reference trajectory, and feedback control law, e.g. in [5]. Lyapunov stable time-varying state-tracking control laws were also used [11], where the system s equations are linearised with respect to the reference trajectory, and by defining the desired parameters of the characteristic polynomial the controller parameters are calculated.

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Plant model Control Objective Implementation Controller No model Stability Analogue (Cont. Time) Loop Shaping (e.g., lead / lag) SISO LTI Performance Digital (Discrete Time) PID MIMO LTI Robust Stability (RS) State feedback LTV (SISO/MIMO) Robust Performance (RP) LQR Nonlinear LQG Hinf MPC Lyapunov Learning Adaptive (many more) Italic: treated

Design, Implementationand Testing of a Bio-Inspired

model can be rewritten as is the command. This (6) where (7) and (8) (9) 3.2 Reference System The referencesystem can be written as (10) where is the referenceinput. matrixes and is the referencestate, are constant The reference system is composed of six uncoupled sec-ond order oscillators. Each oscillator is characterized by a damping coefficient

912 IEEE TRANSACTIONS ON AUTOMATIC CONTROL, VOL. 53, NO. 4

Index Terms Adaptive control, discrete time, Lyapunov stability. I. INTRODUCTION T HE ADAPTIVE control literature focuses primarily on adaptive stabilization, adaptive tracking, and model refer-ence adaptive control. These adaptive control problems have been approached using parameter-estimation-based adaptive

Tracking-error model-based predictive control for mobile

reference robot; therefore, all the kinematic constraints are implicitly considered by the reference trajectory. The control inputs are mostly obtained by a combination of feedforward inputs, calculated from reference trajectory, and feedback control law, as in [22,10,16,1]. Lyapunov stable time-varying

A new model reference adaptive control with the disturbance

REGULAR PAPER A new model reference adaptive control with the disturbance observer-based adaptation law for the Nonlinear Servomechanisms: SISO and MIMO Systems Kun-Yung Chen Depa

Retrospective Cost Adaptive Control Using Composite FIR/IIR

tive control. In particular, we consider retrospective cost adaptive control (RCAC), which is a direct adaptive discrete-time control law that can be used for stabilization, command following (including model reference adaptive control), and disturbance rejection [8 11]. As shown in [11], RCAC controllers are similar to LQG controllers