lBest-HS algorithm based concurrent <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e1346" altimg="si8.svg"><mml:msub><mml:mrow><mml:mi>L</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:math> adaptive control for non-Linear systems

Maiti, Roshni; Sharma, Kaushik Das; Sarkar, Gautam

doi:10.1016/j.isatra.2019.07.007

Cited by 9 publications

(3 citation statements)

References 24 publications

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“…But, in many cases, the transient performance, stability, and optimal control of the system is not guaranteed in PID based schemes without a precise parametric model. Several soft computational techniques, like fuzzy logic based control [21], artificial neural network based techniques [24], stochastic optimisation based approaches [31] etc., are also prominently utilised for the control of multi-link manipulators to achieve robust transient, and steadystate performances along with improved stability [24]. The performance of a two-link manipulator (TLM) based on voltage control technique achieved better transient, and steady-state behaviour with the application of harmony search blended 1 L adaptive control strategy [31].…”

Section: Introductionmentioning

confidence: 99%

“…Several soft computational techniques, like fuzzy logic based control [21], artificial neural network based techniques [24], stochastic optimisation based approaches [31] etc., are also prominently utilised for the control of multi-link manipulators to achieve robust transient, and steadystate performances along with improved stability [24]. The performance of a two-link manipulator (TLM) based on voltage control technique achieved better transient, and steady-state behaviour with the application of harmony search blended 1 L adaptive control strategy [31]. A fuzzy parallel distributed compensation (PDC) based 1 L adaptive control system achieves better tracking performance in [21].…”

Section: Introductionmentioning

confidence: 99%

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Real-time fractional order L 1 adaptive control strategy for fractional order two link manipulator

Biswas,

Das Sharma

2024

Phys. Scr.

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Position controlled industrial robots are used for trajectory tracking with fast and precise motion. The modelling and control technique in such a case depends on manipulator structure, material, servo control and inertial force. This paper proposes a scheme of fractional order modelling of a two-link manipulator (TLM) system with non-linearities, parametric uncertainties and disturbances, in joint space. A newly developed L 1 adaptive control ( L 1 AC) strategy is modified by introducing a fractional-order predictor and fractional order adaptation laws to achieve desired variations of joint angles of the TLM. The novelty of this paper lies in the fact that the proposed FO- L 3 AC scheme works in synchronism with the FOTLM system to deal with the non-linearities, parametric uncertainties and disturbances during real-life experimentation. The stability of the overall close loop system is precisely guaranteed utilizing the Lyapunov theory, and all the closed-loop variables are bounded employing L 1 norm-based conditions. Real-life experimental studies demonstrate the superiority of the proposed control strategy.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Real-time fractional order L 1 adaptive control strategy for fractional order two link manipulator

Biswas,

Das Sharma

2024

Phys. Scr.

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“…Nevertheless, the gradient search is suitable for the nonlinear case but it still has an issue about dynamic limitation 31 . To improve this disadvantage, concurrent learning is currently developed such as the function approximation 32 and the adaptive controller 33 . Unfortunately, the compromise between previous gradients with respect to current learning parameters is very intricate especially when the dynamic model is unknown.…”

Section: Introductionmentioning

confidence: 99%

Data‐driven optimal fault‐tolerant‐control and detection for a class of unknown nonlinear discrete‐time systems

Treesatayapun

2021

Optim Control Appl Methods

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The design of optimal fault-tolerant control with actuator and sensor faults is investigated. The system dynamics and faults are considered as a class of unknown nonlinear discrete-time systems when the data-driven equivalent model is formulated by a multi-input fuzzy rule emulated network (MiFREN).The multi-gradient learning law is developed with the proposed fault-detection algorithm to enchant the performance of MiFREN. By employing only pieces of information from the equivalent model, the proposed controller is designed and the closed-loop performance is analyzed through the rigorous theorem. Simulation systems and comparison results are provided to validate the performance of the proposed scheme.

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