Robust path tracking control of nonholonomic wheeled mobile robot: Experimental validation

Roy, S.; Nandy, Sambhunath; Ray, R.K.; Shome, Sankar Nath

doi:10.1007/s12555-014-0178-1

Cited by 83 publications

(48 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• Problem 1: The stability analysis of TDC, as provided in [7], [26]- [27], [34], [35] [7], [26]- [27], [34], [35]), velocity and acceleration feedback are necessary to compute the control law. While in [6], only velocity feedback is required and acceleration term is approximated numerically using time delay.…”

Section: B Problem Definitions and Contributionsmentioning

confidence: 99%

“…In [7], [8], [26]- [27], [34], [35], TDC is used to provide robustness against uncertainties. In this process, all the uncertain terms are represented by a single function which is then approximated using control input and state information of the immediate past time instant.…”

mentioning

confidence: 99%

“…The series of publications [2], [15]- [20] regarding ARC, estimates the uncertain terms online based on predefined projection function, but predefined bound on uncertainties is still a requirement. The work reported in [21], [33] attempts to estimate the maximum uncertainty bound but the integral adaptive law makes the controller susceptible to very high switching gain and consequent chattering [34]. The adaptive sliding mode control (ASMC) as presented in [22]- [23] proposed two laws for the switching gain to adapt itself online according to the incurred error.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Adaptive-Robust Control of a Class of EL Systems With Parametric Variations Using Artificially Delayed Input and Position Feedback

Roy

Kar

Lee

et al. 2019

IEEE Trans. Contr. Syst. Technol.

Self Cite

View full text Add to dashboard Cite

In this paper, the tracking control problem of a class of Euler-Lagrange systems subjected to unknown uncertainties is addressed and an adaptive-robust control strategy, christened as Time-Delayed Adaptive Robust Control (TARC) is presented. The proposed control strategy approximates the unknown dynamics through time-delayed logic, and the switching logic provides robustness against the approximation error. The novel adaptation law for the switching gain, in contrast to the conventional adaptive-robust control methodologies, does not require either nominal modelling or predefined bounds of the uncertainties. Also, the proposed adaptive law circumvents the overestimation-underestimation problem of switching gain. The state derivatives in the proposed control law is estimated from past data of the state to alleviate the measurement error when state derivatives are not available directly. Moreover, a new stability notion for time-delayed control is proposed which in turn provides a selection criterion for controller gain and sampling interval. Experimental result of the proposed methodology using a nonholonomic wheeled mobile robot (WMR) is presented and improved tracking accuracy of the proposed control law is noted compared to time-delayed control and adaptive sliding mode control.

show abstract

Section: B Problem Definitions and Contributionsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Adaptive-Robust Control of a Class of EL Systems With Parametric Variations Using Artificially Delayed Input and Position Feedback

Roy

Kar

Lee

et al. 2019

IEEE Trans. Contr. Syst. Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In another work, a robust control algorithm is presented for a WMR to track a reference signal. 30 The algorithm provides an estimation for unknown lumped disturbances and unmodeled dynamics plus an estimation for the inertia matrix. The estimations are based on the past input-output data and the second derivative of the reference signal is incorporated.…”

Section: Application 1: Wheeled Mobile Robotmentioning

confidence: 99%

Optimal model‐free control for a generic MIMO nonlinear system with application to autonomous mobile robots

Safaei

Mahyuddin

2018

Adaptive Control & Signal

View full text Add to dashboard Cite

In this paper, the design procedure for optimal model-free control algorithm is presented for the tracking problem of completely unknown nonlinear dynamic systems operating under unknown disturbances. The procedure includes a new structure in the context of model-free control and data-driven control algorithms. In the new structure, the unknown nonlinear functions are segmented into 1 unknown linear-in-states part and another unknown nonlinear part. The adaptive laws proposed for estimating the unknown system dynamics are regressor-free estimation methods in which there is no need for regressor parameters and, consequently, the persistent excitation condition is not required anymore. Moreover, the main controller gains are updated online, incorporating the adapted values of linear terms in the system dynamics. A comparative study is presented to show that the proposed optimal model-free control outperforms the state-of-the-art model-free control algorithms. In addition, the simulation results for the application of the algorithm on autonomous mobile robots are provided.

show abstract

“…Nevertheless, the adaptive laws reported in [9]- [13] make the switching gain a monotonically increasing function. Thus, the controllers become susceptible to very high switching gain and consequent chattering [16].…”

Section: Introductionmentioning

confidence: 99%

Time-Delayed Control for a Class of EL Systems with Only Position Feedback

Roy

Kar

2019

Studies in Systems, Decision and Control

Self Cite

View full text Add to dashboard Cite

In this paper, the tracking control problem of an Euler-Lagrange system is addressed with regard to parametric uncertainties, and an adaptive-robust control strategy, christened Time-Delayed Adaptive Robust Control (TARC), is presented. TARC approximates the unknown dynamics through the timedelayed estimation, and the adaptive-robust control provides robustness against the approximation error. The novel adaptation law of TARC, in contrast to the conventional adaptive-robust control methodologies, requires neither complete model of the system nor any knowledge of predefined uncertainty bounds to compute the switching gain, and circumvents the over-and underestimation problems of the switching gain. Moreover, TARC only utilizes position feedback and approximates the velocity and acceleration terms from the past position data. The adopted state-derivatives estimation method in TARC avoids any explicit requirement of external low pass filters for the removal of measurement noise. A new stability notion in continuous-time domain is proposed considering the time delay, adaptive law, and state-derivatives estimation which in turn provides a selection criterion for gains and sampling interval of the controller.

show abstract

Robust path tracking control of nonholonomic wheeled mobile robot: Experimental validation

Cited by 83 publications

References 21 publications

Adaptive-Robust Control of a Class of EL Systems With Parametric Variations Using Artificially Delayed Input and Position Feedback

Adaptive-Robust Control of a Class of EL Systems With Parametric Variations Using Artificially Delayed Input and Position Feedback

Optimal model‐free control for a generic MIMO nonlinear system with application to autonomous mobile robots

Time-Delayed Control for a Class of EL Systems with Only Position Feedback

Contact Info

Product

Resources

About