Fuzzy Sliding Mode Control for DC Motors: Algorithm and Implementation Approach

Fuzzy Sliding Mode Control for DC Motors

DC motor control requires precision, robustness, and adaptability to handle uncertainties including load variations and external disturbances. Traditional Sliding Mode Control (SMC) offers strong disturbance rejection but exhibits chattering—high-frequency oscillations that compromise system performance. Fuzzy Sliding Mode Control (FSMC) integrates SMC's robustness with fuzzy logic's adaptability to mitigate this issue.

### Why Combine Fuzzy Logic and Sliding Mode Control? Sliding Mode Control drives the system trajectory toward a predefined sliding surface, ensuring stability against disturbances. However, its discontinuous control law induces chattering. Fuzzy Logic dynamically adjusts control parameters using rule-based inference, smoothing control signals while preserving robustness through real-time gain optimization.

### Implementation Approach 1. Define sliding surface s(t) = λ·e(t) + de(t)/dt, where e(t) is tracking error and λ is a positive constant 2. Design fuzzy inference system with inputs (s, ds/dt) and output (switching gain K) 3. Implement membership functions for linguistic variables (e.g., Negative Large, Zero, Positive Large) 4. Apply rule base such as: "IF s is Positive Big AND ds/dt is Negative Small THEN K is Medium" 5. Combine SMC control law u(t) = -K·sign(s) with fuzzy-tuned gain to reduce chattering

### Advantages of FSMC for DC Motors Adaptability: Fuzzy logic automatically adjusts to motor parameter variations and load changes Chattering Reduction: Continuous approximation of sign function minimizes mechanical wear Robustness: Maintains performance against unmodeled dynamics and disturbances

This method is particularly effective in industrial automation and robotics applications where DC motors operate under dynamic conditions requiring reliable torque and speed control.