Bacteria foraging optimized and modified PSO optimized PD-SMC and PID-SMC controller for inverted pendulum system

Bordoloi, Nitisha; Buragohain, Mrinal

doi:10.1109/icspace.2017.8343424

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…Proof of Lyapunov stability analysis, parameter values obtained from the PSO tuning are in Table 2. This is based on Lyapunov's stability analysis, that the system will be stable if it conforms to the conditions (21) and (22). In Table 2 it can be analyzed that the result of the parameter value is greater than zero.…”

Section: Results and Analysismentioning

confidence: 99%

“…But those optimizations need more delay because of complexity. One of the optimizations that need less delay is PSO [21,22]. Bordoloi N et al, PD-SMC parameters are optimized with PSO to solve high-frequency chat problems and track desired trajectories in a faster way [21].…”

Section: Introductionmentioning

confidence: 99%

“…One of the optimizations that need less delay is PSO [21,22]. Bordoloi N et al, PD-SMC parameters are optimized with PSO to solve high-frequency chat problems and track desired trajectories in a faster way [21]. Dehdarinejad M et al, the phase-shifted full-bridge (PSFB) SMC parameters optimized with PSO show robust results and to improve system speed and accuracy [22].…”

Section: Introductionmentioning

confidence: 99%

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Velocity control of ROV using modified integral SMC with optimization tuning based on Lyapunov analysis

et al. 2020

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Remotely Operated Vehicle also known as ROV is a vehicle with high nonlinearity and uncertainty parameters that requires a robust control system to maintain stability. The nonlinearity and uncertainty of ROV are caused by underwater environmental conditions and by the movement of the vehicle. SMC is one of the control systems that can overcome nonlinearity and uncertainty with the given robust system. This work aims to control velocity of the vehicle with proposes the use of modified integral SMC compensate error in ROV and the use of particle swarm optimization (PSO) to optimize the adjustment of SMC parameters. The ROV used in this paper has a configuration of six thrusters with five DoF movements that can be controlled. Modified integral sliding mode is used to control all force direction to increase the convergence of speed error. Adjustment optimization techniques with PSO are used to determine four values of sliding control parameters for five DoF. Using Lyapunov stability approach control law of sliding mode is derived and its global stability proved mathematically. Simulation results are conducted to evaluate the effectiveness of Modified Integral SMC and compared with nonlinear control.

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Section: Results and Analysismentioning

confidence: 99%