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• W133026534 abstract "Abstract – A nonlinear predictive controller (NMPC) is developed to control a unicycle-like mobile robot for trajectory tracking. Dynamic model of PIONNER 3-DX mobile robot is used, where external forces and wheels sliding have been considered. Restrictions on control actions and system states are also considered. Simulations results at both tracking and regulation (positioning) are shown, these results show the good performance of developed controller. Finally, this paper shows that the controller can be implemented in real-time by using an analysis of compute times of NMPC algorithm. Key words – mobile robot, predictive nonlinear control (NMPC), trajectory tracking, dynamic model I. INTRODUCTION The trajectory tracking control for mobile robots is a fundamental problem, which has been investigated exhaustively by the scientific community. Several papers deal about the design of control laws for mobile robot with its dynamic model, for instance in trajectory tracking (De la Cruz et al., 2006; Dong et al., 2005; Albagul et al., 2004; Yang et al., 1999; Zhang et al., 1998). One of first investigation results for this problem was deal in Kanayama et al. (1990), where author uses the Lyapunov theory to design the tracking controller. Nevertheless, this and others controllers do not take in count the restrictions in the control signals because it is a hard task to implement. Nonlinear predictive control (NMPC) is a most frequently control-optimization technique used in industry. This methodology has been designed to deal with optimization problems with restrictions. NMPC is an optimization algorithm online to predict output system based on current states and model system, and also, to find a control feature in open loop by using numeric optimization and to apply the first control signal of this optimized feature to system. In model based predictive control due to use the receding horizon, the stability analysis is one of the main problems (Pena, 2002). Previous works have demonstrated that a finite receding horizon can guarantee NMPC stability even for nonlinear systems (Camacho et al., 1998; Pena, 2002), although this strategy is considered heavy due to its computational effort in practice. The NMPC stability analysis with finite receding horizon has been studied in Mayne et al. (2000) and Fontes (2001). Recently, the qualities of predictive control have been explored and applied in robotics, woks like Dongbing et al. (2006), Hedjar et al. (2005), Kunhe et al. (2005) and Ramirez et al. (1999) show different approaches and strategies in MPC with good results for tracking control and regulation. This paper applies NMPC to dynamic model of mobile robot and makes an analysis by computes times for optimization algorithm so that to be able to implement the controller in experimental works. The paper is organized as follows: Section II describes the NMPC algorithm and the programming schemes used. Section III shows the dynamic model of mobile robot. Section IV describes the simulation results. Conclusions and future works are detailed in last Section." @default.
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• W133026534 date "2007-01-01" @default.
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• W133026534 title "DYNAMIC MODEL BASED PREDICTIVE CONTROL FOR MOBILE ROBOTS" @default.
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