Robotic Control Systems
Study the principles of robot dynamics and control theory. Learn to design controllers like PID and LQR, and explore modern adaptive and learning-based control methods for precise robot motion.
79 courses
Learn how smart sensors, data, and adaptive controls are used to create self-optimizing manufacturing processes.
Build, simulate, and analyze dynamic system models using MATLAB and Simulink through practical written explanations and step-by-step conceptual exercises.
Learn to model, analyze, and design stable feedback systems for switching power converters using small-signal AC modeling and compensation techniques.
Master the core principles of rotational dynamics, coordinate transformations, and control systems to analyze and design modern spacecraft missions.
Learn how everyday automated devices think and react by mastering the core principles of feedback loops, sensors, and digital control systems.
Learn to analyze Linear Time-Invariant systems, sketch Bode plots, and design stable feedback controllers to meet precise performance specifications.
Learn to model, analyze, and design feedback control loops for power converters to build stable and efficient energy conversion systems.
Master the fundamentals of classical and modern control theory to design, analyze, and simulate stable engineering systems.
Learn to translate physical laws into mathematical models to analyze and control the behavior of dynamic systems.
Master classical control theory by learning to analyze system stability, sketch root locus plots, and design lead-lag compensators to meet precise performance targets.
Master multi-degree of freedom systems, continuous beam dynamics, and modern numerical simulation techniques for practical engineering analysis.
Master the basics of modeling, analyzing, and simulating dynamic control systems using MATLAB to design stable and efficient feedback loops.
Learn to program autonomous mobile robots by mastering wheel kinematics, sensor integration, state machines, and path tracking in simulated environments.
Learn to build, configure, and analyze dynamic system models using Simulink, starting from basic blocks to hierarchical subsystems and state-machine logic.
Learn to build, simulate, and analyze dynamic system models in Simulink to test your engineering designs before moving to hardware.
Write MATLAB scripts for data analysis and build your first simulation models in Simulink from the ground up.
Learn to model, analyze, and control dynamic systems using modern state-space techniques for engineering and automation.
Learn to design artificial systems that evolve and respond to change by applying core principles from biology and cybernetics.
Master the art of simulation-driven design to create optimized, lightweight, and high-performance engineering solutions using advanced optimization techniques.
Master the fundamentals of feedback loops, stocks, and flows to build and analyze robust system dynamics models using AnyLogic.
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