A Comparison Between the ILOS Guidance and the Vector Field Guidance

Caharija, Walter; Pettersen, Kristin Y.; Calado, Pedro; Braga, Juan C.

doi:10.1016/j.ifacol.2015.10.263

Cited by 26 publications

(26 citation statements)

References 10 publications

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“…Ideal feedback linearizing controllers such as the ones given in Section III-C are used in the simulations and the gains of the ILOS guidance low from Section II-B (the look ahead distance ∆ and the integral gain σ) are chosen according to the bounds (7)(8). Some preliminary results of these tests are shown in [50] and [61]. In this paper additional data are presented and a back-to-back comparison between simulations and experimental results is given.…”

Section: Simulations and Experimentsmentioning

confidence: 99%

“…Moreover, the LOS used outside this corridor has a horizontal look-ahead distance ∆ = 5.6 [m]. A longer ∆ is used compared to the in-corridor situation to make the tested ILOS guidance scheme comparable in its gains to other guidance laws that were tested on the same day [61]. It is straightforward to show mathematically through Lemma II.2 that a LOS guidance without integral action in presence of current with Vmax = 0.2 [m/s] and U rd = 1.2 [m/s] will make the vehicle enter the corridor.…”

Section: Lauv Vehicle Simulationsmentioning

confidence: 99%

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Integral Line-of-Sight Guidance and Control of Underactuated Marine Vehicles: Theory, Simulations, and Experiments

Caharija

Pettersen

Bibuli

et al. 2016

IEEE Trans. Contr. Syst. Technol.

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264

158

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Abstract-This paper presents an extensive analysis of the integral line-of-sight (ILOS) guidance method for path following tasks of underactuated marine vehicles, operating on and below the sea surface. It is shown that due to the embedded integral action, the guidance law makes the vessels follow straight lines by compensating for the drift effect of environmental disturbances such as currents, wind and waves. The ILOS guidance is first applied to a 2D model of surface vessels that includes the underactauted sway dynamics of the vehicle as well as disturbances in the form of constant irrotational ocean currents and constant dynamic, attitude dependent, forces. The actuated dynamics are not taken into account at this point. A Lyapunov closed loop analysis yields explicit bounds on the guidance law gains to guarantee uniform global asymptotic stability (UGAS) and uniform local exponential stability (ULES).The complete kinematic and dynamic closed loop system of the 3D ILOS guidance law is analyzed next, hence extending the analysis to underactuated AUVs for 3D straight-line path following applications in the presence of constant irrotational ocean currents. The actuated surge, pitch and yaw dynamics are included in the analysis where the closed loop system forms a cascade, and the properties of UGAS and ULES are shown. The 3D ILOS control system is a generalization of the 2D ILOS guidance. Finally, results from simulations and experiments are presented to validate and illustrate the theoretical results, where the 2D ILOS guidance is applied to the CART and the LAUV vehicles.

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Section: Simulations and Experimentsmentioning

confidence: 99%

Section: Lauv Vehicle Simulationsmentioning

confidence: 99%

Integral Line-of-Sight Guidance and Control of Underactuated Marine Vehicles: Theory, Simulations, and Experiments

Caharija

Pettersen

Bibuli

et al. 2016

IEEE Trans. Contr. Syst. Technol.

Self Cite

264

158

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“…In order to improve the dynamic characteristics of tracking errors, the LOS guidance law with time-varying lookahead distance 2 of 19 was presented in [5,6]. Alternatively, the vector field (VF) methodis also a popular guidance law [7,8]. Similar to the guidance problem, a lot of work has been done on the design of a dynamic controller in path following.…”

Section: Introductionmentioning

confidence: 99%

Path Following Based on Waypoints and Real-Time Obstacle Avoidance Control of an Autonomous Underwater Vehicle

Yao

Wang

et al. 2020

Sensors

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This paper studies three-dimensional (3D) straight line path following and obstacle avoidance control for an underactuated autonomous underwater vehicle (AUV) without lateral and vertical driving forces. Firstly, the expected angular velocities are designed by using two different methods in the kinematic controller. The first one is a traditional method based on Line-of-sight (LOS) guidance law, and the second one is an improved method based on model predictive control (MPC). At the same time, a penalty item is designed by using the obstacle information detected by onboard sensors, which can realize the real-time obstacle avoidance of the unknown obstacle. Then, in order to overcome the uncertainty of the dynamics model and the saturation of actual control input, the dynamic controller is designed by using sliding mode control (SMC) technology. Finally, in the simulation experiment, the performance of the improved control method is verified by comparison with two traditional control methods based on LOS guidance law. Since the constraint of an AUV’s angular velocities are considered in MPC, simulation results show that the improved control method uses MPC, and SMC not only improves the tracking quality of the AUV when switching paths near the waypoints and realizes real-time obstacle avoidance but also effectively reduces the mean square error (MSE) and saturation rate of the rudder angle. Therefore, this control method is more conducive to the system stability and saves energy.

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“…There are many possible approaches to solving this problem: the guidance methods using the Serret-Frenet representation at a projective point (Samson, 1992), virtual target (Soetanto et al, 2003), line-of-sight guidance (Fossen and Pettersen, 2014;Caharija et al, 2015) and differentialgeometric methods for invariant sets stabilization (Akhtar et al, 2015). Compared to these approaches, the methods based on the tracking of vector fields (Nelson et al, 2007;Lawrence et al, 2008) demonstrate better, in many aspects, performance (Caharija et al, 2015;Sujit et al, 2014). The vector field algorithms are widely used in many applications of robotics, such as path-planning (Pamosoaji and Hong, 2013), obstacle avoidance (Hoy et al, 2015) and extremum seeking (Matveev et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…In particular, path following is a typical motion control task which requires an autonomous robotic vehicle to converge to a predefined path and follow it at a prescribed speed (Siciliano and Khatib, 2008). There are many possible approaches to solving this problem: the guidance methods using the Serret-Frenet representation at a projective point (Samson, 1992), virtual target (Soetanto et al, 2003), line-of-sight guidance (Fossen and Pettersen, 2014;Caharija et al, 2015) and differentialgeometric methods for invariant sets stabilization (Akhtar et al, 2015). Compared to these approaches, the methods based on the tracking of vector fields (Nelson et al, 2007;Lawrence et al, 2008) demonstrate better, in many aspects, performance (Caharija et al, 2015;Sujit et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Guiding vector field algorithm for a moving path following problem

et al. 2017

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This paper presents a guidance algorithm solving the problem of moving path following, that is, steering a mobile robot to a curvilinear path attached to a moving frame. The nonholonomic robot is described by the unicycle-type model under the influence of some constant exogenous disturbance. The desired path may be an arbitrary smooth curve in its implicit form, that is, a level set of some known smooth function. The path following algorithm employs a guiding vector field, whose integral curves converge to the trajectory. Experiments with a real fixed wing unmanned aerial vehicle (UAV) as well as numerical simulations are presented, illustrating the performance of the proposed path following control algorithm.

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A Comparison Between the ILOS Guidance and the Vector Field Guidance

Cited by 26 publications

References 10 publications

Integral Line-of-Sight Guidance and Control of Underactuated Marine Vehicles: Theory, Simulations, and Experiments

Integral Line-of-Sight Guidance and Control of Underactuated Marine Vehicles: Theory, Simulations, and Experiments

Path Following Based on Waypoints and Real-Time Obstacle Avoidance Control of an Autonomous Underwater Vehicle

Guiding vector field algorithm for a moving path following problem

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