A semi-active control strategy for suspension systems of passenger cars is presented employing Magnetorheological (MR) dampers. The vehicle is modeled with seven DOFs including the, roll pitch and bounce of car body, and the vertical motion of the four tires. In order to design an optimal controller based on the actuator constraints, a Linear-Quadratic Regulator (LQR) is designed. The design pr...

This paper studies the trade-off between degree of decentralization and performance a distributed controller in linear-quadratic control setting. We study system interconnected agents over graph controller, called -distributed control, which lets make decisions based on state information within distance underlying graph. can tune its using parameter thus allows characterization relationship per...

The state-of-the-art robust H∞ linear parameter-varying controller is designed for wide speed operating range non-linear mathematical model of permanent magnet synchronous machines (PMSM) in d-q reference frame fully electric vehicle. This study propose polytopic approach using rotor as scheduling variable to reformulate PMSM into parameter varying (LPV) form. weights were optimized sensitivity...

In this paper, new non-quadratic stability conditions are derived based on the parallel distributed compensation scheme to stabilize Takagi-Sugeno (T-S) fuzzy systems. We use a non-quadratic Lyapunov function as a fuzzy mixture of multiple quadratic Lyapunov functions. The quadratic Lyapunov functions share the same membership functions with the T-S fuzzy model. The stability conditions we prop...

This paper suggests to replace PIs and PIDs, which play a key role in control engineering, by intelligent Proportional-Derivative feedback loops, or iPDs, are derived from model-free control. standpoint is enhanced laboratory experiment.

The purpose of this short note is to provide an alternative derivation of the optimal controller for the linear quadratic optimization problem in Section 2. Consider the linear time-varying system dynamics ˙ x(t) = A(t)x(t) + B(t)u(t), x(t 0) = x 0 , (1) where x(t) ∈ R n , u(t) ∈ R n i , ∀t ∈ [t 0 ,t 1 ]. Define the quadratic cost function J(u) = 1 2 t 1 t 0 u(t) 2 2 + C(t)x(t) 2 2 dt + x(t 1) ...

Today, we are witnessing an increasing trend in the number of soft pneumatic actuator solutions industrial environments, especially due to their human-safe interaction capabilities. An interesting solution this frame is a vacuum muscle (PMA) with bellow structure, which characterized by high contraction ratio and ability generate forces considering its relatively small dimensions. Moreover, suc...