Movable Payload on Various Conditions of Two-Wheeled Double Links Wheelchair Stability Control Using Enhanced Interval Type-2 Fuzzy Logic

Abstract

This paper presents investigations of control strategies for a two-wheeled wheelchair with a movable payload on various conditions using a double-link inverted pendulum concept. The wheelchair system is modeled in the SimWise 4D (SW4D) with its optimized control parameters determined using the Spiral Dynamic Algorithm (SDA) while being controlled by the proposed Interval Type-2 Fuzzy Logic Controller (IT2FLC). The robustness of the proposed controller in terms of maintaining the system's stability while the wheelchair is standing in an upright position is tested under multiple circumstances. These included utilizing varying directions and applying magnitudes of external disturbances to the developed system with a movable payload (upward and downward) and testing the system's forward and backward motions on a flat surface and the motions on an inclined surface. Ultimately, the two-wheeled wheelchair which adopts the proposed controller had shown a 68% and 77% reduction in the angular positions of Link1 and Link2, a 94% reduction in torques for both Link1 and Link2, and more than 98% reduction in traveling distance compared to the Fuzzy Logic Control Type-1 (FLCT1) controller which was used in the previous design. Moreover, the current work has taken into consideration the heightened nonlinearities and complexity of an additional moving payload on various conditions to represent more degree of freedom (DOF), compared to the fixed payload in the previous design with less DOF. This further rectifies that the enhanced IT2FLC had outperformed FLCT1 in handling nonlinearities and uncertainties, for the case of a two-wheeled wheelchair system with a movable payload. INDEX TERMS Two-wheeled wheelchair, movable payload of a double-link inverted pendulum, optimized interval type-2 fuzzy logic, stability of the two-wheeled system.

Decoupled Multi-Loop Robust Control for a Walk-Assistance Robot Employing a Two-Wheeled Inverted Pendulum

“…Figure 9f shows the zoom-in position responses after settling, where the TWIP robot oscillated within about ±1 cm. Finally, the statistical data are shown in Table 2, where the mean absolutely error (MAE) and the root mean square error (RMSE) after the settling time are defined as (21) in which e indicates the corresponding error, T = 15 s, and t s is the settling time, when the error of the pitch angel is less than 0.475 o (i.e., 5% of the step from −9.5 • to 0 • ) afterwards. From the table, in place 1 and place 2, the rise time were 0.4 s, while the MAE and RMSE of ψ were less than 0.178 • and 0.224 • , respectively.…”

“…Kim and Kwon [20] discussed the influence of inertia and applied a state-dependent Riccati equation to balance the TWIP system. Jamin et al [21] applied a fuzzy logic controller to a two-wheeled wheelchair with a movable payload, where the control parameters were optimized by the spiral dynamic algorithm. S'anchez et al [22] developed a full-order observer without using the unavailable state variables.…”

Optimal Type-3 Fuzzy System for Solving Singular Multi-Pantograph Equations

“…Recently, it has been shown in literature that FLSs, specially high-order FLSs have more capability than NNs. In various engineering applications the superiority of type-2 and type-3 FLSs have been shown such as: decision making [23], control systems [24], identification [25], chaotic synchronization [26], multi-agent control systems [27], among many others.…”