Designed a dual-motor continuously variable transmission system that dynamically allocates torque through a differential-based architecture under varying load conditions.

The system models real-time allocation under stochastic demand.

The system demonstrates how dynamic allocation under uncertainty can be achieved through feedback control rather than static distribution.
At its core, it behaves like a real-time allocator of constrained capacity responding to changing external demand signals.

- Dual-motor differential architecture for variable torque output
- Real-time load detection and adaptive power redistribution (Arduino / C++)
- Feedback-based control loop adjusting motor contribution under stress
- Simulation of load-dependent system response under varying torque regimes
- Mechanical design + CAD-based system architecture (SolidWorks)

Motor 1:             High-speed / low-torque input stream
Motor 2:            Low-speed / high-torque stabilizer
Differential:     Aggregation layer balancing competing inputs
Output:            Stabilized system response under external load shocks

Torque demand                                      Order flow pressure
Dual motors                                             Multiple liquidity sources
Differential                                               Execution layer
Load variation                                         Volatility regime shifts
Feedback control                                  Adaptive execution logic

Benchmarks and system outputs demonstrating real-time torque balancing, feedback-driven motor coordination, and dynamic load adaptation in a dual-motor differential system under varying mechanical stress conditions.

Designed an embedded access control system for shared mobility assets, integrating authentication, locking mechanics, and real-time state tracking through an app-based interface.

The system models state transition under multi-agent contention, where access, locking, and validation operate as a deterministic state machine under competing requests.

State transition system under competing requests, where system state evolves deterministically based on multi-agent inputs.

User request → authentication layer
Validation → state transition logic
Actuation → physical execution (lock / unlock)
Sensor feedback → state confirmation loop

Authentication                                  Order validation
Lock state                                           Position state
Actuator                                              Execution engine
Sensor feedback                               Post-trade confirmation
Shared resource system                 Liquidity pool under competing agents

Benchmarks and system outputs demonstrating embedded locking mechanisms, user authentication flow, and state-controlled actuation in a shared mobility system.

Designed an autonomous delivery trailer integrating mechanical design, embedded sensing, and feedback control to enable stable motion under dynamic and uncertain environmental conditions.

The system models real-time control under external noise and non-stationary conditions.

A mobile control system requiring:
- Continuous stability maintenance
- Adaptive directional response
- Feedback-driven correction under uncertainty

This reflects execution systems under volatility and noisy signals.

Steering subsystem → directional control
Chassis → structural stability under load
Sensors → environmental feedback loop
Actuation → real-time corrective response

Steering geometry                                  Directional bias
Sensor feedback                                      Market signals
Load distribution                                     Capital allocation
Chassis stability                                        Risk constraints
Environmental noise                              Market volatility

Benchmarks and system outputs demonstrating real-time steering control, sensor-driven feedback loops, and mechanical stability in a mobile embedded delivery system.

Designed and built a multi-actuator vehicular control system based on the Audi RS6, featuring distributed motor control, suspension dynamics, and steering coordination to replicate realistic vehicle behavior under constrained actuation.
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The system models coordinated multi-agent actuation in a closed mechanical environment.

A simplified model of:
- Distributed actuation systems
- Mechanical coordination across subsystems
- Stability under multi-degree-of-freedom control
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This reflects multi-factor allocation and coordination under bounded resources.

Steering system → directional control layer
Drive motors → execution / propulsion layer
Suspension → shock absorption / volatility buffering
Weight distribution → system equilibrium / balance

Distributed actuation system              Multi-strategy portfolio execution layer
Steering control                                       Signal direction
Suspension                                               Risk buffering
Weight distribution                                Capital allocation
Stability tuning                                        Portfolio optimization

Benchmarks and system outputs demonstrating multi-actuator coordination, steering dynamics, and suspension-based stability control in a distributed mechanical system.