Single Chip Self-Tunable N-Input N-Output PID Control System with Integrated Analog Front-end for Miniature Robotics
Anindya Shankar Bhandari, Arjun Chaudhuri, Mrigank Sharad

TL;DR
This paper presents a compact, low-power, multi-channel PID control chip with integrated analog front-end and PSO-based tuning, designed for real-time control of miniature robotic systems with multiple sensors and actuators.
Contribution
It introduces a novel single-chip multi-channel PID controller with integrated analog front-end and adaptive biasing for low power, enabling efficient real-time tuning for miniature robotics.
Findings
Successful simulation with N=3 channels demonstrating control of motor, temperature, and gyroscope.
Low power consumption achieved through adaptive biasing in the analog front-end.
Effective PSO-based tuning for multiple channels in a compact, integrated system.
Abstract
In this work, we explore the design of an integrated, low power single chip multi-channel Proportional-Integral-Derivative (PID) controller for emerging miniature robotics, that includes N inputs and N corresponding outputs thereby resulting in N parallel channels in the control system. It includes analog front-end (AFE) and analog PID controllers for PID parameter tuning based on PSO algorithm. The AFE incorporates adaptive biasing to ensure low power. The PSO is optimized with respect to tuning precision, power and area. This makes it attractive for real-time tuning of multiple miniaturized robotic devices with a single PSO tuning algorithm block assigned for the task. For simulation and testing purposes, we take N as 3 with the channels being defined by their application-ends or plants, namely: dc motor, temperature sensor and gyroscope.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Control Systems Design · Advanced Control Systems Optimization · Experimental Learning in Engineering
