Modeling Introduction: Control System Design

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Optimization Techniques: Convexity and Algorithms in Machine Learning

Covers optimization techniques in machine learning, focusing on convexity, algorithms, and their applications in ensuring efficient convergence to global minima.

Energy optimization strategies

Covers brainstorming options for smart operation changes, heat recovery, and PV panel performance.

Mixing Tank: Process Control

Covers the process control of a mixing tank and optimizing its performance.

Optimization Methods: Theory Discussion

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Connect Four: Alpha-Beta Pruning and Monte-Carlo Tree Search

Explores solving Connect Four using game theory algorithms and compares Alpha-Beta pruning with Monte-Carlo tree search.

Suspension Optimisation: Performance Analysis and Optimization

Explores the design and optimization of car suspensions for improved performance.

System Identification and Stability

Explores system identification, stability criteria, and challenges in stabilizing cameras on moving platforms.

Multi-Agent Systems: Traffic Management and Pricing Strategies

Covers multi-agent systems in traffic management and dynamic pricing strategies using game theory.

Optimization with Constraints: KKT Conditions

Covers the optimization with constraints, focusing on the Karush-Kuhn-Tucker (KKT) conditions.

Boolean Algebra: Properties and Optimization

Explores Boolean algebra properties and optimization techniques using Karnaugh diagrams and De Morgan's theorems.