Consensus control of multi-agent systems has been intensively studied over the past two decades. Distributed consensus control of multi-agent systems are employed in various industrial applications such as sensors data fusions, cooperative robots, and vehicles. Event-triggered approaches usually reduce the frequency updates of input control signals as well as system resource consumption. In these methods, controller’s input signals are only calculated once and update moments is reduced in compare with time-triggered approaches. However, The bigger amplitude of applied demands, may result in more depreciation, damage and maintenance costs to the actuators. Therefore, the design of event detection mechanism and control strategy are very challenging. In this thesis, we proposed an event-triggered consensus control protocol and an event detection mechanism to decrease control signal variations. The distributed detection mechanism is defined based on control variations in each agent, measurement errors, and the state errors in respect to neighbors. In the proposed event-triggered consensus-based protocol, the difference between control signal of each agent and its latest update is used to reduce the amplitude of the steps that are generated in the input control. The controllers gain is computed by a Riccati equation for each agent, separately. In order to improve the efficiency of the proposed method, several coefficients of the proposed event detection functions have been fuzzified using the Takagi-Sugeno Fuzzy System. These coefficients have been shown to a greater impact on the event detection function compared to the non fuzzified case. To prove consensus for the proposed detection function, linear algebraic relations methods and graph theory have been used. To evaluate performance of the proposed methods, several simulations have been carried out and the results have been compared. The proposed methods decrease control signal variations as well as number of events resulting in reduction of system wear. The factor is great importance in systems comprising numerous agents. Key Words: Multi-Agent System , Event-Triggered Control , Consensus Problem , Takagi-Sugeno Fuzzy System
