Interacting multiple model-based adaptive control system for stable steering of distributed driver electric vehicle under various road excitations

Simultaneous estimation of state and packet-loss occurrences in networked control systems

“…To compute the covariance matrix Σ j,k in (21c), we first use (9) to write the following equations given that θ k−1 = j.…”

“…In the above equation, θ k−1 is estimated given Y k , because y(k) does not depend on θ k according to (9). As usual, the mean value estimators and the estimation error covariances for the state variable x in (9) are defined as below.…”

“…In order to use the above theorem, it is first needed to compute p(y k | θ k−1 = j, Y k−1 ). Combining the equations in (9), one can write…”

“…The existing methods for estimation of the MJS state mainly include the multiple model estimation techniques [7,8]. These methods are mainly applied to target tracking problems [7] while they also find other applications [9]. Multiple model estimation can be extended to nonlinear MJSs [10].…”

Optimization Transmission Efficiency with Driver Intention for Automotive Continuously Variable Transmission Under Slip Mode

“…Currently, multi-objective control problems of complex nonlinear system in automotive research are widely solved using model predictive control (MPC) [26][27][28], because of its online prediction [29], rolling in real-time optimization [30,31] and before and after feedback correction [32,33].…”