Penerapan Sistem Kendali PID Cascade Pada Robot Two Wheeled Self Balancing

Brilian Aulia Ananditya, Jans Hendry, S.T., M.Eng.

2026 | Tugas Akhir | D4 Teknologi Rekayasa Instrumentasi dan Kontrol

Two-Wheeled Self-Balancing Robot (TWR) merupakan robot dengan dua roda koaksial yang menerapkan prinsip inverted pendulum sehingga secara alami bersifat tidak stabil dan memerlukan sistem kendali aktif secara real-time. Penelitian ini menerapkan metode Cascaded Proportional-Integral-Derivative (PID) sebagai sistem kendali untuk menjaga keseimbangan dan mengatur pergerakan robot. Sistem kendali dirancang dalam dua lapis, yaitu inner loop untuk menjaga kestabilan sudut pitch dan outer loop untuk menghasilkan referensi gerak atau kecepatan translasi. Optimasi parameter PID inner loop dilakukan menggunakan tiga metode metaheuristik, yaitu Genetic Algorithm (GA), Particle Swarm Optimization (PSO), dan Grey Wolf Optimizer (GWO), dengan fungsi objektif ITAE (Integral Time Absolute Error) pada respons impuls. Parameter PID outer loop dioptimasi menggunakan GA. Seluruh proses dilakukan dalam simulasi MATLAB karena implementasi pada perangkat keras mengalami kendala teknis berupa noise pada PCB dan ground loop. 

Hasil simulasi menunjukkan bahwa ketiga metode tuning berhasil menstabilkan sistem dengan seluruh pole berada di dalam lingkaran satuan (|z|<1 Kp=75,6073, Ki=7,2965, Kd=5,7256 Kp=2,6120, Ki=0,0029, Kd=0,0010>

Two-Wheeled Self-Balancing Robot (TWR) is a robot with two coaxial wheels that applies the inverted pendulum principle, making it inherently unstable and requiring real-time active control. This research implements a Cascaded Proportional-Integral-Derivative (PID) method as a control system to maintain balance and regulate robot movement. The control system is designed in two layers: an inner loop to maintain pitch angle stability and an outer loop to generate motion references or translational velocity. Optimization of the inner loop PID parameters was performed using three metaheuristic methods: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO), with the ITAE (Integral Time Absolute Error) objective function on impulse response. The outer loop PID parameters were optimized using GA. The entire process was conducted in MATLAB simulation due to technical constraints in hardware implementation, including PCB noise and ground loop issues. 

Simulation results show that all three tuning methods successfully stabilized the system with all poles located within the unit circle (|z| < 1 xss=removed xss=removed xss=removed xss=removed xss=removed xss=removed>

Kata Kunci : Cascade, Discrete PID, Roll, Pitch