Adaptive Fuzzy Command Filtered Tracking Control for Flexible Robotic Arm with Input Dead-Zone

Abstract

In this paper, an adaptive fuzzy tracking control method is proposed to address the issues of dead-zone and unobservable states in a flexible robotic arm system. The control design process begins with the utilization of a fuzzy logic system to approximate the nonlinear functions present in the flexible robotic arm system. To estimate the unobservable states of the system, a state observer is then designed. To alleviate the computational complexity during controller design, the command filtering technique is introduced. Additionally, the Nussbaum function is incorporated to address the unknown control gain problem. The stability of the system can be verified through the design of a Lyapunov function. This study’s simulation results demonstrate that the designed control system can closely track the specified reference signals. The closed-loop system effectively controls the flexible robotic arm, as verified through experimentation.

Research on Obstacle Avoidance Replanning and Trajectory Tracking Control Driverless Ferry Vehicles

“…The fuzzy PID acceleration controller designed in this article uses a combination of fuzzy control [16] and PID control to realize the real-time online adjustment of PID parameters, thereby realizing the adjustment of the motor torque of the ferry vehicle, so as to achieve the real-time speed regulation of the vehicle. Figure 3 shows the fuzzy PID controller's structure diagram.…”