Design of CMAC Neural Network-Based Robotic Arm Control with MATLAB Source Code

MATLAB source code for designing CMAC neural network-based robotic arm control. CMAC (Cerebellar Model Articulation Controller) is a neural network controller based on the cerebellar model that simulates the structure and function of cerebellar cortical neuronal networks, possessing excellent nonlinear mapping and pattern recognition capabilities. The design objective utilizes CMAC neural networks to control robotic arm movement by inputting position and velocity information to achieve precise control and operation. The MATLAB source code provides implementation including key functions for weight adaptation, basis function calculation, and control signal generation. The code architecture typically consists of three main modules: input preprocessing for sensor data normalization, CMAC network implementation using hash-coding techniques for efficient memory addressing, and control output generation through weighted summation of activated memory cells. This design enables researchers to study and apply CMAC-based control strategies, potentially expanding the field of robotic arm control while improving precision and flexibility through adaptive learning mechanisms. Further development could incorporate real-time learning algorithms and multi-layer CMAC structures for enhanced performance.