Trajectory tracking of differential drive mobile robots using fractional-order proportional-integral-derivative controller design tuned by an enhanced fruit fly optimization

Abstract

This work proposes a new kind of trajectory tracking controller for the differential drive mobile robot (DDMR), namely, the nonlinear neural network fractional-order proportional integral derivative (NNFOPID) controller. The suggested controller’s coefficients comprise integral, proportional, and derivative gains as well as derivative and integral powers. The adjustment of these coefficients turns the design of the proposed NNFOPID control further problematic than the conventional proportional-integral-derivative control. To handle this issue, an Enhanced Fruit Fly Swarm Optimization algorithm has been developed and proposed in this work to tune the NNFOPID’s parameters. The enhancement achieved on the standard fruit fly optimization technique lies in the increased uncertainty in the values of the initialized coefficients to convey a broader search space. subsequently, the search range is varied throughout the updating stage by beginning with a big radius and declines gradually during the course of the searching stage. The proposed NNFOPID controller has been validated its ability to track specific three types of continuous trajectories (circle, line, and lemniscate) while minimizing the mean square error and the control energy. Demonstrations have been run under MATLAB environment and revealed the practicality of the designed NNFOPID motion controller, where its performance has been compared with that of a nonlinear Neural Network Proportional Integral Derivative controller on the tracking of one of the aforementioned trajectories of the DDMR.

433Mhz based Robot using PID (Proportional Integral Derivative) for Precise Facing Direction

“…This control system comprises three distinct parameters, namely proportional, integral, and derivative, each exhibiting unique characteristics [2]. The formulation of the PID control system is denoted by the equation where u(t) denotes the resultant value [4], [15], [16].…”

“…The integral component possesses the property of introducing system order, which can potentially lead to instability. However, a drawback of the integral component is its tendency to produce sluggish reactions [3], [5], [9], [10], [16]. The formulation of this control system is as follows:…”

“…The testing involved evaluating the wireless modules' distance coverage, power consumption, and transmission speed. The error formula, which captures the discrepancies between the test results of NRF24 and LoRa E32, is presented below [16]. The test results presented in Table II pertain to the Line of Sight (LOS) conditions.…”

Document Clustering in the Age of Big Data: Incorporating Semantic Information for Improved Results

“…Search engines come in all shapes and sizes. Human editors are responsible for compiling online directories, while search engines rely on either algorithms or a mix of human and machine curation to choose which results to return [83].…”

Fractional-order PID controller tuned by particle swarm optimization algorithm for a planar CDPR control

“…For additional details, readers are referred to [20]. Consequently, in the field of robotics, a diverse range of robots, such as parallel robots [21], [22], serial robot manipulators [23]− [25], cable-driven continuum robots [26], flexible-link robot manipulators [27], and mobile robots [28], [29], have been successfully controlled. Notably, the FOPID controller's application to cable-driven parallel robots has not been explored extensively.…”