Robust Un-coupled Fuzzy Controller for
Longitudinal and Lateral Control of an AGV
K R S Kodagoda,W S Wijesoma and E K Teoh
School of Electrical and Electronic Engineering
Nanyang Technological University
Singapore 639798.
pml453P77@ntu. edu. Sg
Abstract. The primary focus is on the development of an intelligent control scheme, which is insensitive to parametric uncertainty, load and parameter fluctuations and most importantly amenable for real time implementation. In this paper, we present an effective uncoupled direct fuzzy PD/PI control scheme for an outdoor AGV, which is a converted electrically powered golf-car. The controller performance is assessed against the required performance criteria and also against another effective nonlinear control method known as computed torque technique (CTT). It is established through simulations that the fuzzy logic controller (FLC) yields good performance even under uncertain and variable parameters in the model, unlike the CTT. And in terms of real-time implementation the availability of custom fuzzy chips and the reduced computational complexity of the fuzzy controller as against the CTT, makes the fuzzy controller, an ideal choice amongst the two schemes.
1、Introduction
The development of techniques for lateral and longitudinal control of vehicles has become an important and active research topic in the face of emerging markets for advanced AGVs and mobile robots. The particular car-like AGV, as is the case with other similar types of AGVs, is characterized by highly non-linear and complex dynamics [1]. Extraneous forces, such as those due to head winds, turning and static friction, typical of harsh outdoor environments, further complicates the modeling process and the determination of model parameters. Even if the model and the parameters are known accurately for an AGV, there are the variations in the amount of cargo in the AGV, that need be accounted for. Thus any control strategy to be useful for outdoor AGV control must able to deal with the above effectively. Linear controllers, for lateral control of AGVs, based on PD/PID, state space methods, and pole placement have been reported [2],[3],[4],[5]. However, linear controllers based on linearized models about the operating points are found to be very ineffective through simulations.
Fuzzy logic has found useful applications in control among other areas. One useful characteristic of a fuzzy controller is its applicability to nonlinear systems with model uncertainty or even unknown models. Another useful characteristic of a fuzzy logic controller is that it provides a framework for the incorporation of domain knowledge in terms of heuristic rules. Given the complexity of the AGV dynamics, the difficulty of obtaining the actual vehicle dynamic parameters, the variability of certain model parameters and the human-knowledge available on speed and steering control motivates the use of a fuzzy logic approach to control law synthesis.
Wu, et. al. [6] have developed an FLC for a vehicle to follow a lane and maintain it in the middle of the lane. It is shown that the tracking accuracy of FLC and the adaptability to parameter variations are superior to a PID controller. Hessburg and Tomizuka [7] has demonstrated through real time implementations the efficacy of an FLC for lateral control of an AGV.
In the rest of the paper we describe the particular AGV and its dynamics comprising of the driving and steering subsystems. Thereafter, a suitable intelligent control structure is proposed for drive and steering to achieve longitudinal and lateral control of the vehicle. The CTT controller is also derived for decoupled longitudinal and lateral control of the AGV. Finally we compare fuzzy un-coupled controller with CTT through simulations.
2、Vehicle Model
The vehicle considered is a Carryalll golf-car. It is a front wheel steerable, rear wheel drive, electrically powered car and is suitably modified for autonomous control. A DC servomotor drives the steer system while the drive system is powered by a DC series motor (see Appendix for more details). The detailed dynamic model of the golf-car excluding the actuation motor dynamics is as follows:
Where, v is the speed of the vehicle, w is the rate of change of steer angle (7 ), tau;d and tau;s are the driving and steering torques respectively. For a detailed derivation of the above model and the definitions of the parameters , （Mv,Mw.N.Cs1,Cs2,Cd1,Cd2,Tsf and Fdf）, please refer [1]. It may be noted that the model is complex, of third order, coupled and the parameters are configuration dependent.
3、Fuzzy Longitudinal and Lateral Controller
Fuzzy logic has found useful applications in control among other areas. One useful characteristic of a fuzzy controller is its applicability to systems with model uncertainty and/or unknown models. Another useful characteristic of a fuzzy logic controller is that it provides a framework for the incorporation of domain knowledge in terms of heuristic rules. Given the complexity of the AGV dynamics, the difficulty of obtaining the actual vehicle dynamic parameters, the variability of certain model parameters and the human-knowledge available on speed and steering control motivates the use of a fuzzy logic approach to control law synthesis. The structure of the uncoupled direct fuzzy control system for longitude and lateral control is shown in Fig. 1.
Fig. 1. Uncoupled longitudinal and lateral fuzzy controller
It may be noted that longitudinal and lateral control is achieved through the use of two separate controllers for steering and driving actuation systems. Using two separate direct fuzzy controllers instead of a single fuzzy controller can significantly reduce the complexity of the fuzzy rule base. T
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