Objectives: Intelligent Controller Design \& Evaluation. An electrical wheelchair has two DC motors and set of sensors for speed, position and obstacle avoidance detection. It is required to replace a conventional controller by an intelligent controller. The controller will calculate the accurate duty cycle of the PWM signal sent to the drive unit of each DC motor. If a fuzzy controller is used to adjust the speed of each motor according to the input commands and feedback signals. [A]. If each variable has FIVE fuzzy sets, develop a fuzzy control system that can effectively maintain the wheelchair's speed and avoid any obstacle in its path: 1. Show graphically the fuzzy sets for input and output variables, fuzzification, rule evaluation and aggregation? 2. For the given system, what is the maximum number of rules? Give your rule matrix? 3. What should the crisp output for the given inputs (50% error and 25% change of error) according to the selected rule matrix? 4. Suggest an optimization method to find the optimal parameters of the proposed fuzzy controller? Explain briefly the proposed method? [B]. It is required to replace the fuzzy controller with a neural controller: 1. Develop a suitable set of neural network training parameters using the same set of system parameters used for the fuzzy controller design? Give the proposed neural network architecture? 2. Compare the neural network performance with the fuzzy control performance?

Intelligent control

Objectives: Intelligent Controller Design \& Evaluation. An electrical wheelchair has two DC motors and set of sensors for speed, position and obstacle avoidance detection. It is required to replace a conventional controller by an intelligent controller. The controller will calculate the accurate duty cycle of the PWM signal sent to the drive unit of each DC motor. If a fuzzy controller is used to adjust the speed of each motor according to the input commands and feedback signals. [A]. If each variable has FIVE fuzzy sets, develop a fuzzy control system that can effectively maintain the wheelchair's speed and avoid any obstacle in its path: 1. Show graphically the fuzzy sets for input and output variables, fuzzification, rule evaluation and aggregation? 2. For the given system, what is the maximum number of rules? Give your rule matrix? 3. What should the crisp output for the given inputs (50% error and 25% change of error) according to the selected rule matrix? 4. Suggest an optimization method to find the optimal parameters of the proposed fuzzy controller? Explain briefly the proposed method? [B]. It is required to replace the fuzzy controller with a neural controller: 1. Develop a suitable set of neural network training parameters using the same set of system parameters used for the fuzzy controller design? Give the proposed neural network architecture? 2. Compare the neural network performance with the fuzzy control performance