Event‐triggered model predictive control for multi‐vehicle systems with collision avoidance and obstacle avoidance

Abstract

In this article, event-triggered model predictive control is used for simultaneous tracking and formation of a multi-vehicle system with collision avoidance and obstacle avoidance. An event-triggered mechanism is established to reduce computational burden in the model predictive control strategy. A compatibility constraint is proposed to guarantee collision avoidance and convergence for the multi-vehicle system by limiting an uncertainty deviation of each vehicle.Between each vehicle and obstacles, a safe distance is ensured by a robust obstacle avoidance constraint. Finally, effectiveness and advantages of the proposed strategy are shown by two simulation examples.

Nonlinear switched model predictive control with multiple Lyapunov functions for trajectory tracking and obstacle avoidance of nonholonomic systems

“…Note that stable trajectory tracking and smooth obstacle avoidance are realized under the nonlinear switched MPC strategy. For the standard MPC strategy without an artificial potential field function in Reference 40, the trajectory are shown in Figure 11.…”

Event-triggered H∞ coordinated control based mode transition system of DM-PHEV

“…Applying Theorem 1 with the state feedback gain k calculated in equation (32), d and t M , the corresponding O can be acquired.…”

“…The combination effectively reduces the computational burden of model predictive control strategy. 32…”

“…The combination effectively reduces the computational burden of model predictive control strategy. 32 However, most studies focus on the application of event-triggered mechanism to suspensions and autonomous vehicles, few results have been reported in the literature about applying the event-triggered control to MTP system of PHEVs. There are many actuators in hybrid electric vehicles, and the controller of PHEV is responsible for the torque distribution of multiple actuators, so the computing resources and network communication resources of the controller are more scarce than other vehicles.…”

Enclosing control for nonholonomic mobile agents with a moving target of unknown velocity

“…𝜀 𝑖 ) ε𝑖 𝜀 𝑖 )(𝜉 𝑖 − 𝜉 𝑗 ).From the definition of 𝜉 in(15), it is noted that 𝜉 𝑖 converges to zero as 𝑡 → ∞.Then one has ∫ 𝑗∈𝑁 𝑖 𝑎 𝑖𝑗 𝜇(|𝜉 𝑖 | + |𝜉 𝑗 |)𝑑 𝜏 is bounded. According to (16), both 𝑉 2 (𝑡) and ∫ 𝑗∈𝑁 𝑖 𝑎 𝑖𝑗 [𝑔(𝜀 𝑖 ) − 𝑔(𝜀 𝑗 )] 2 are bounded.…”