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Modeling and control of a 4-wheel skid-steering mobile robot

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Kozłowski K., Pazderski D.
International Journal of Applied Mathematics and Computer Science
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2004
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tom 14
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nr 4
477-496
EN
A mathematical model of a 4-wheel skid-steering mobile robot is presented in a systematic way. The robot is considered as a subsystem consisting of kinematic, dynamic and drive levels. Next, a designing process of a kinematic controller based on the algorithm introduced by (Dixon et al., 2001) is shown. An extension of the kinematic control law at the dynamic and motor levels using the Lyapunov analysis and the backstepping technique is developed. To validate the designed algorithm, extensive simulation results for trajectory tracking and set-point cases are discussed. Some deliberations concerning the tuning of the controller are presented, too.
2
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A backstepping approach to ship course control

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Witkowska A., Tomera M., Smierzchalski R.
International Journal of Applied Mathematics and Computer Science
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2007
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tom 17
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nr 1
73-85
EN
As an object of course control, the ship is characterised by a nonlinear function describing static manoeuvring characteristics that reflect the steady-state relation between the rudder deflection and the rate of turn of the hull. One of the methods which can be used for designing a nonlinear ship course controller is the backstepping method. It is used here for designing two configurations of nonlinear controllers, which are then applied to ship course control. The parameters of the obtained nonlinear control structures are tuned to optimise the operation of the control system. The optimisation is performed using genetic algorithms. The quality of operation of the designed control algorithms is checked in simulation tests performed on the mathematical model of a tanker. In order to obtain reference results to be used for comparison with those recorded for nonlinear controllers designed using the backstepping method, a control system with the PD controller is examined as well.
3
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Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems

100%
Tong S., Liu C., Li Y.
International Journal of Applied Mathematics and Computer Science
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2010
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tom 20
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nr 4
637-653
EN
In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.
4
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Designing a ship course controller by applying the adaptive backstepping method

100%
Witkowska A., Śmierzchalski R.
International Journal of Applied Mathematics and Computer Science
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2012
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tom 22
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nr 4
985-997
EN
The article discusses the problem of designing a proper and efficient adaptive course-keeping control system for a seagoing ship based on the adaptive backstepping method. The proposed controller in the design stage takes into account the dynamic properties of the steering gear and the full nonlinear static maneuvering characteristic. The adjustable parameters of the achieved nonlinear control structure were tuned up by using the genetic algorithm in order to optimize the system performance. A realistic full-scale simulation model of the B-481 type vessel including wave and wind effects was applied to simulate the control algorithm by using time domain analysis.
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