State estimation and parameter identification via sliding-mode techniques: pendulum-cart system

Automatica ◽  
2015 ◽  
Vol 62 ◽  
pp. 139-147 ◽  
Author(s):  
Héctor Ríos ◽  
Diego Mincarelli ◽  
Denis Efimov ◽  
Wilfrid Perruquetti ◽  
Jorge Davila

Author(s):  
Yaswanth Siramdasu ◽  
Farbod Fahimi

Sliding mode controller for trajectory tracking of a surface vessel is designed based on a 3DOF dynamic model. The model has six unknown parameters. For parameter identification, four special test scenarios are defined to isolate and identify one of the six parameters at a time. The identification tests are performed on a robotic boat which has an onboard PC104 computer and a navigation sensor providing vessel’s dynamic states in real-time. The data from experiments are used to determine the model parameters. A sliding mode controller is designed based on the identified model, and is implemented and tested on a real robotic boat. The experiments show the excellent performance of the controller.


2020 ◽  
Vol 42 (8) ◽  
pp. 1448-1460 ◽  
Author(s):  
Majid Parvizian ◽  
Khosro Khandani ◽  
Vahid Johari Majd

In this paper, state estimation and adaptive sliding mode control (SMC) of uncertain fractional-order Markovian jump systems (FO-MJSs) with time delay and input nonlinearity are considered. A non-fragile observer is proposed to estimate the system states, and an observer-based adaptive sliding mode controller is synthesized to ensure the reachability of the sliding surfaces in the state-estimation space in finite time. The sufficient condition for stochastic stability of the error system and sliding mode dynamics is derived in the form of linear matrix inequalities (LMIs). Finally, some numerical examples are presented to illustrate the effectiveness of the proposed method.


2005 ◽  
Vol 38 (1) ◽  
pp. 89-94 ◽  
Author(s):  
A. FILIPESCU ◽  
U. NUNES ◽  
S. STAMATESCU

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