Design and experimental validation of an adaptive fast-finite-time observer on uncertain electro-hydraulic systems

Razmjooei, Hamid; Palli, Gianluca; Abdi, Elahe; Terzo, Mario; Strano, Salvatore

doi:10.1016/j.conengprac.2022.105391

Cited by 16 publications

(6 citation statements)

References 33 publications

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“…The number of routers will depend on the indoor space size that needs to be explored. Several new frameworks designed a finite time that may be utilized to make the robot’s observation error uniformly constrained, as well as to reach a finite time convergence and reconstruct its external disturbances and uncertainties [ 53 , 54 , 55 ].…”

Section: Resultsmentioning

confidence: 99%

Multi-Robot Exploration of Unknown Space Using Combined Meta-Heuristic Salp Swarm Algorithm and Deterministic Coordinated Multi-Robot Exploration

Romeh

Mirjalili

2023

Sensors

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Multi-robot exploration means constructing a finite map using a group of robots in an obstacle chaotic space. Uncertainties are reduced by distributing search tasks to robots and computing the best action in real time. Many previous methods are based on deterministic or meta-heuristic algorithms, but limited work has combined both techniques to consolidate both classes’ benefits and alleviate their drawbacks. This paper proposes a new hybrid method based on deterministic coordinated multi-robot exploration (CME) and the meta-heuristic salp swarm algorithm (SSA) to perform the search of a space. The precedence of adjacent cells around a robot is determined by deterministic CME using cost and utility. Then, the optimization process of the search space, improving the overall solution, is achieved utilizing the SSA. Three performance measures are considered to evaluate the performance of the proposed method: run time, percentage of the explored area, and the number of times when a method failed to continue a complete run. Experimental results compared four different methods, CME-GWO, CME-GWOSSA, CME-SCA, and CME, over seven maps with extra complexity varying from simple to complex. The results demonstrate how the proposed CME-SSA can outperform the four other methods. Moreover, the simulation results demonstrate that the proposed CME-SSA effectively distributes the robots over the search space to run successfully and obtain the highest exploration rate in less time.

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Section: Resultsmentioning

confidence: 99%

Multi-Robot Exploration of Unknown Space Using Combined Meta-Heuristic Salp Swarm Algorithm and Deterministic Coordinated Multi-Robot Exploration

Romeh

Mirjalili

2023

Sensors

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“…It is noticed that the chattering phenomenon in the torque shown in Figure 8 is due to the noise added to the outputs. To remove this issue observers, like the ones designed in References 50 and 51 and implemented in Reference 52, could be applied to provide the control system with smooth estimated signals. Moreover, according to Figures 9 and 10, the absolute value of the velocity of the responses of control system designed in Reference 27 is bigger then that of the control system designed in this work which indicates that the latter system has a smoother performance compared to the other.…”

Section: Numerical Examplementioning

confidence: 99%

Tip position control of flexible single‐link manipulators in the frequency domain without model reduction

Mohsenipour,

Liu

2024

Intl J Robust & Nonlinear

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This article develops the fundamentals of the tip position control of flexible single‐link robotic manipulators in the frequency domain without approximating the model. Analytic transfer functions of the hub angle and tip position are derived without any model order reduction. Conditions for the stability of the transfer functions are presented by considering the payload mass change as an uncertain parameter. Using the D‐decomposition method, a simple procedure is introduced to design an output feedback controller which guarantees the stability and a desired tracking performance. The introduced design method leads to less conservatism comparing with design methods established upon model reduction. The controller structure includes two proportional‐derivative and integral loops and needs only two measurements of joint angle and tip position which are easily implementable. A numerical example is provided to demonstrate the merit of the achieved results.

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“…Model predictive control (MPC) is an advanced control technique that has been widely studied and successfully applied in many applications, including active battery cell balancing [1][2][3][4][5][6][7][8]. MPC determines control actions by using a model of the system in combination with a cost function to determine the optimal sequence of control actions that minimizes the cost function over a future time horizon.…”

Section: Introductionmentioning

confidence: 99%

Reinforcement Learning-Based Event-Triggered Active-Battery-Cell-Balancing Control for Electric Vehicle Range Extension

Flessner,

Chen,

Xiong

2024

Electronics

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Optimal control techniques such as model predictive control (MPC) have been widely studied and successfully applied across a diverse field of applications. However, the large computational requirements for these methods result in a significant challenge for embedded applications. While event-triggered MPC (eMPC) is one solution that could address this issue by taking advantage of the prediction horizon, one obstacle that arises with this approach is that the event-trigger policy is complex to design to fulfill both throughput and control performance requirements. To address this challenge, this paper proposes to design the event trigger by training a deep Q-network reinforcement learning agent (RLeMPC) to learn the optimal event-trigger policy. This control technique was applied to an active-cell-balancing controller for the range extension of an electric vehicle battery. Simulation results with MPC, eMPC, and RLeMPC control policies are presented along with a discussion of the challenges of implementing RLeMPC.

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Design and experimental validation of an adaptive fast-finite-time observer on uncertain electro-hydraulic systems

Cited by 16 publications

References 33 publications

Multi-Robot Exploration of Unknown Space Using Combined Meta-Heuristic Salp Swarm Algorithm and Deterministic Coordinated Multi-Robot Exploration

Multi-Robot Exploration of Unknown Space Using Combined Meta-Heuristic Salp Swarm Algorithm and Deterministic Coordinated Multi-Robot Exploration

Tip position control of flexible single‐link manipulators in the frequency domain without model reduction

Reinforcement Learning-Based Event-Triggered Active-Battery-Cell-Balancing Control for Electric Vehicle Range Extension

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