Flatness-based control in successive loops for robotic manipulators and autonomous vehicles

Rigatos, G.; Abbaszadeh, M.; Pomares, J.; Wira, P.; Cuccurullo, G.

doi:10.1080/00207721.2023.2301040

Cited by 2 publications

(1 citation statement)

References 72 publications

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“…This special form simplifies the concept of a feedback controller capable of achieving exact trajectory tracking. In fact, controlling a linear system is easier than controlling an underactuated nonlinear system, and this feature has encouraged researchers to use the properties of flatness in several application domains, such as the control of hydraulic systems [11], exoskeleton robots [12], microgrid [13], underwater robot [14], and quadrotor [15,16].…”

Section: Introductionmentioning

confidence: 99%

Robust Tracking Control of Wheeled Mobile Robot Based on Differential Flatness and Sliding Active Disturbance Rejection Control: Simulations and Experiments

Abadi,

Ayeb,

Labbadi

et al. 2024

Sensors

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This paper proposes a robust tracking control method for wheeled mobile robot (WMR) against uncertainties, including wind disturbances and slipping. Through the application of the differential flatness methodology, the under-actuated WMR model is transformed into a linear canonical form, simplifying the design of a stabilizing feedback controller. To handle uncertainties from wheel slip and wind disturbances, the proposed feedback controller uses sliding mode control (SMC). However, increased uncertainties lead to chattering in the SMC approach due to higher control inputs. To mitigate this, a boundary layer around the switching surface is introduced, implementing a continuous control law to reduce chattering. Although increasing the boundary layer thickness reduces chattering, it may compromise the robustness achieved by SMC. To address this challenge, an active disturbance rejection control (ADRC) is integrated with boundary layer sliding mode control. ADRC estimates lumped uncertainties via an extended state observer and eliminates them within the feedback loop. This combined feedback control method aims to achieve practical control and robust tracking performance. Stability properties of the closed-loop system are established using the Lyapunov theory. Finally, simulations and experimental results are conducted to compare and evaluate the efficiency of the proposed robust tracking controller against other existing control methods.

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Section: Introductionmentioning

confidence: 99%

Robust Tracking Control of Wheeled Mobile Robot Based on Differential Flatness and Sliding Active Disturbance Rejection Control: Simulations and Experiments

Abadi,

Ayeb,

Labbadi

et al. 2024

Sensors

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Application of Particle Swarm Optimization to a Hybrid H∞/Sliding Mode Controller Design for the Triple Inverted Pendulum System

Shafeek,

Ali

2024

Algorithms

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The robotics field of engineering has been witnessing ra advancements and becoming widely engaged in our lives recently. Its application has pervaded various areas that range from household services to agriculture, industry, military, and health care. The humanoid robots are electro–mechanical devices that are constructed in the semblance of humans and have the ability to sense their environment and take actions accordingly. The control of humanoids is broken down to the following: sensing and perception, path planning, decision making, joint driving, stability and balance. In order to establish and develop control strategies for joint driving, stability and balance, the triple inverted pendulum is used as a benchmark. As the presence of uncertainty is inevitable in this system, the need to develop a robust controller arises. The robustness is often achieved at the expense of performance. Hence, the controller design has to be optimized based on the resultant control system’s performance and the required torque. Particle Swarm Optimization (PSO) is an excellent algorithm in finding global optima, and it can be of great help in automatic tuning of the controller design. This paper presents a hybrid H∞/sliding mode controller optimized by the PSO algorithm to control the triple inverted pendulum system. The developed control system is tested by applying it to the nominal, perturbed by parameter variation, perturbed by external disturbance, and perturbed by measurement noise system. The average error in all cases is 0.053 deg and the steady controller effort range is from 0.13 to 0.621 N.m with respect to amplitude. The system’s robustness is provided by the hybrid H∞/sliding mode controller and the system’s performance and efficiency enhancement are provided by optimization.

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Flatness-based control in successive loops for robotic manipulators and autonomous vehicles

Cited by 2 publications

References 72 publications

Robust Tracking Control of Wheeled Mobile Robot Based on Differential Flatness and Sliding Active Disturbance Rejection Control: Simulations and Experiments

Robust Tracking Control of Wheeled Mobile Robot Based on Differential Flatness and Sliding Active Disturbance Rejection Control: Simulations and Experiments

Application of Particle Swarm Optimization to a Hybrid H∞/Sliding Mode Controller Design for the Triple Inverted Pendulum System

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