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npx versuz@latest install hiyenwong-ai-collection-collection-skills-complex-kuramoto-controlgit clone https://github.com/hiyenwong/ai_collection.gitcp ai_collection/SKILL.MD ~/.claude/skills/hiyenwong-ai-collection-collection-skills-complex-kuramoto-control/SKILL.md---
name: complex-kuramoto-control
description: "Unified control framework for synchronization in coupled oscillator networks using complex-valued Kuramoto extensions. Use when designing synchronization controllers, phase-locking mechanisms, oscillator network control, or when real-valued Kuramoto model fails. Keywords: Kuramoto, synchronization, complex-valued control, oscillator networks, phase locking, sliding-mode control."
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# Complex-Valued Kuramoto Networks: Unified Control Framework
Synchronization control in oscillator networks through complex-valued extensions that embed nonlinear phase dynamics into linear state space.
## Problem: Classical Kuramoto Limitations
Real-valued Kuramoto model:
- Intrinsic nonlinearity limits analytical tractability
- Complicates control design
- Fails for heterogeneous networks with different natural frequencies
## Solution: Complex-Valued Extension
Embed phase dynamics into higher-dimensional **linear state space**:
- Regulating complex-state moduli to common value → recovers Kuramoto phase behavior
- Enables linear control techniques for inherently nonlinear problem
## Control Strategies
### 1. Switched Feedforward Law
- Ensures exact phase correspondence at all times
- No spectral gain tuning required
### 2. Feedforward + Sliding-Mode Law
- Finite-time convergence
- Robust to perturbations
### 3. Non-autonomous MIMO Sliding-Mode Controller
- Enforces phase locking at prescribed frequency in finite time
- Independent of natural frequencies and coupling strengths
- Works for heterogeneous networks where real-valued Kuramoto fails
## Key Insight
**Phase → Complex state → Control moduli → Recover phase**
The transformation: $\theta \rightarrow z = e^{i\theta}$
Control $|z|$ to converge → $\theta$ synchronizes
## Design Procedure
1. Map oscillator phases to complex plane
2. Design controller for complex state convergence
3. Verify phase behavior recovered from complex-state behavior
4. Handle heterogeneity through robust control design
## Applications
- Power grid synchronization
- Neural network synchronization
- Circadian rhythm control
- Chemical oscillator networks
- Distributed clock synchronization
- Robot swarm coordination
## When Classical Kuramoto Fails
Heterogeneous networks:
- Different natural frequencies
- Varying coupling strengths
- Non-uniform topology
Complex-valued approach handles these through robust control design.
## Code Pattern (Conceptual)
```python
# Classical Kuramoto: nonlinear phase dynamics
dθ/dt = ω - K * sin(θ_j - θ_i) # Hard to control
# Complex-valued: linear complex dynamics
z = exp(iθ) # Transform
dz/dt = iωz - K*(z_j - z_i) # Now design control for z
# Control moduli
|z| → target # Drive all |z| to common value
# Phase θ synchronizes as consequence
```
## Performance Benefits
- Improved transient response
- Better steady-state accuracy
- Enhanced robustness
- Handles heterogeneity
## References
- arXiv:2604.07249v1 - "Complex-Valued Kuramoto Networks: A Unified Control-Theoretic Framework"
- Kuramoto, Y. (1984) - Original model
- Acebrón et al. (2005) - Kuramoto review