Design of Generalized Predictive Control for an Active Suspension System

Abstract

Designing new vehicles presents considerable challenges within the automotive industry, especially with the growing demand for driving safety, comfort, and efficiency. Advanced suspension systems and drive dynamics control systems are emerging as potential solutions to address these issues. This paper discusses the advanced control problems of active suspension concepts. Hence, the Generalized predictive control (GPC) structure is analyzed to determine the control configuration with adequate comfort and optimal energy use. The overall vehicle performance can be optimized in response to the increasing market demands by thoroughly examining the active suspension systems (ASS). This paper proposes a GPC strategy for an active suspension system based on a quarter-car model, evaluated against passive and PID benchmarks. The GPC predicts future control signals to stabilize the system and minimize the worst-case gain from disturbance inputs into system outputs. A passive suspension system and a proportional-integral-derivative (PID) controller were thus used. As evaluated through the integral square error (ISE) and root mean square error (RMSE) indices, the proposed controller can stabilize the suspension system and improve ride comfort.