feat: Graph Network Controllability Engine - autonomous structural controllability analysis

Add GraphControllabilityEngine with 7 analysis engines based on structural
controllability theory (Liu et al. 2011):

1. Maximum Matching Engine (Hopcroft-Karp algorithm)
2. Driver Node Identifier - minimum external control set
3. Control Centrality Calculator - reachability-based ranking
4. Controllability Robustness Analyzer - Monte Carlo node removal
5. Control Category Classifier - CRITICAL/REDUNDANT/INTERMITTENT
6. Control Profile Generator - source/internal/sink classification
7. Insight Generator - autonomous controllability recommendations

Features:
- Hopcroft-Karp bipartite matching for minimum driver node identification
- Driver node density (nD/N) computation
- Control centrality via BFS reachability
- Robustness curve under random node failure
- Per-node category classification across multiple matchings
- Interactive HTML dashboard with charts
- Health scoring 0-100

Usage: GraphControllabilityEngine engine = new GraphControllabilityEngine();
       ControllabilityReport report = engine.analyze(graph);

Includes 59 comprehensive JUnit tests.

Author: sauravbhattacharya001