Software/Hardware-Based Hierarchical Finite-Time Sliding-Mode Control With Input Saturation for an Omnidirectional Autonomous Mobile Robot

Abstract

To track the desired pose of the omnidirectional autonomous mobile robot (OAMR) in finite time, the finite-time virtual desired trajectory (FTVDT) is designed by the 1st sliding surface with the linear dynamics and fractional order of pose's tracking error. To track the FTVDT in finite time, the finite-time sliding-mode saturated control (FTSMSC) is designed by the second sliding surface with the linear dynamics and fractional order of the FTVDT's tracking error. In short, the proposed hierarchical finite-time slidingmode control with input saturation (HFTSMCIS) contains the FTVDT and the FTSMSC. As compared with previous studies, the finite-time trajectory tracking with the reduced chattering control input is achieved by the suitable selection of control parameters. The HFTSMCIS algorithm is executed in the CPU, and then it is transformed to a PWM signal using FPGA hardware and the motor velocity is simultaneously decoded by the FPGA hardware for feedback control. In contrast, the other state signals are achieved from the mathematical model such that the feedback control system is simple and effective. It is so-called software/hardwarebased HFTSMCIS (SHB-HFTSMCIS). Finally, three experiments, including two different process time and obstacle avoidance, are presented to validate the effectiveness and robustness of the proposed control system.

Regulating Constraint-Following Bound for Uncertain Mechanical Systems: An Indirect Control Approach

“…for performance comparison. Figure 5 shows the performance of the constructed system (23) under the action of the robust control (29). It can be seen that state δ of the constructed system (23) approaches to a desirable neighborhood close to 0 before t = 0.26.…”

“…It can be seen that state δ of the constructed system (23) approaches to a desirable neighborhood close to 0 before t = 0.26. Figure 6 shows the performance comparison of the original system (1) with the robust control (29) control inputs F toF and τ toτ . By comparison, we find that although these two controls give out almost the same maximum control input of F = 10, the control effect is very different: with the robust control, the constraint-following error β always keeps in the previously given range ofβ = 1.5, and approaches to a desirable neighborhood close to 0 at the same time as δ approaches to its desired range (i.e., before t = 0.26) eventually; whereas, with the nominal control, the constraint-following error β goes out of that given range.…”

“…Note that, we choose ρ as in (90). Recalling the definition of g, we havē Lastly, we obtain the control as (29) as…”

Fractional-Order Adaptive Integral Hierarchical Sliding Mode Control Method for High-Speed Linear Motion of Spherical Robot

“…By bringing (34) into (35), we can obtain one derivative of V with respect to time, as shown in (36).…”

“…According to (36),V ≤ 0, andV = 0 if and only if S = 0. According to the Lasalle's invariance principle, the linear motion of the spherical robot is asymptotically stable under the control law (34).…”