Hybrid Type-2 Fuzzy-Sliding Mode Controller for Navigation of Mobile Robot in an Environment Containing a Dynamic Target

Abstract

We are interested in developing a new control architecture to command a mobile robot in a partially known environment. For that purpose, a hybrid control architecture is adopted, combining the reactive and the deliberative method. The reactive method consists of the hierarchical fuzzy controllers based on Type-2 Fuzzy Logic System (T2-FLS), dedicated to commanding the robot towards a mobile target while avoiding unexpected obstacles. A comparative study is made to show the efficiency of T2-FLS against Type-1 Fuzzy Logic System (T1-FLS). Additionally, the used deliberative method is the sliding mode, allowing the robot to track the mobile goal trajectory. Simulation results are given finally to test the proposed architecture.

Analytical Synthesis of Regulators for Nonlinear Systems with a Terminal State Method on Examples of Motion Control of a Wheeled Robot and a Vessel

“…The only difference between the models is that control actions in (9) have the form of robot wheels angular velocities, and in [16] the form of robot wheels linear velocities , . Replacing linear velocities with expressions = ( /2) 1 , = ( /2) 2 makes the model from [16] coincide with (9).…”

“…A common drawback of these methods, as well as others based on the use of linear feedback from the state coordinates [14,15], is that they contain indeterminate coefficients that are unknown in advance and may depend on the operating conditions. To adapt to the operation conditions, principles of adaptive and intelligent control are used [16,17]. To a lesser extent, such drawbacks are inherent in methods based on the use of control object mathematical models [18,19].…”

Obstacles Avoidance for Mobile Robot Using Type-2 Fuzzy Logic Controller

“…Hierarchical fuzzy controllers based on Type-2 Fuzzy Logic System for mobile robot in a partially known environment with eight sensors were presented by Ref. [12]. A sliding mode was used to make the mobile robot chase the dynamic target and avoid obstacles simultaneously.…”

Design of a robust interval type-2 fuzzy adaptive super twisting control for a given class of disturbed MIMO nonlinear systems

“…However, type-1 FSs (T1-FSs), in the presence of linguistic uncertainties and measurement errors, are not able to process excellently such perturbations. Therefore, to overcome this constraint, type-2 FSs (T2-FSs), which constitute a generalization of T1-FSs, show appreciable and attractive features in taking into account such uncertainties [33][34][35][36]. The key feature is the so called footprint of uncertainty (FOU), which allows incorporating directly the uncertainties in the membership functions (MFs).…”

“…The key feature is the so called footprint of uncertainty (FOU), which allows incorporating directly the uncertainties in the membership functions (MFs). In [35], to show the superiority of a reactive proposed control approach based on T2-FSs to drive a robot mobile towards a mobile target, it is compared against its counterpart using T1-FSs instead of T2-FSs. And, in [36], the proposed method, which is used to describe and control an underactuated mobile two wheeled inverted pendulum in the presence of modelling errors and external disturbances, shows that when it is based on T2-FSs rather than T1-FSs, it is more effective in achieving the desired performance of control.…”