Product Overview

The Horstman adaptive learning technology enables the active suspension controller to optimize the ride performance of the suspension system, whilst driving the vehicle, and uses the sensing package on the vehicle. This system requires no operator input to optimise the suspension performance, speeding up the development and improvement of the vehicle platform suspension performance. 

The adaptive learning technology combines sliding mode control (SMC) and systematic Lyapunov design approaches. These two approaches are as follows: 

1. SMC design approach consists of two phases: (i) selection of a sliding (switching) surface so as to achieve the desired system behavior (e.g., asymptotic stability), when restricted to the surface; and (ii) selection of a control law such that the existence of sliding mode can be guaranteed.  

2. Systematic Lyapunov design approach consists of three phases: (i) selection of a control law with variable parameters or terms; (ii) selection of an updated law for adjusting the variable terms; and (iii) analysis of the convergence properties of the designed controller. Using this two approaches enables Horstman to converge the control algorithm to achieve a stable platform performance.

Nonlinear control modeAll the operating points of the system can be considered.
No need to linearize the nonlinear system about some operating points.
Sliding-mode controllersCapability to deal with uncertainties, good performance, and very fast response.
Systematic Lyapunov design approachAsymptotic robust stability of the closed-loop system in the presence of model uncertainties and disturbances.
End travel impact forceFunction smoothly decrease the actuator force  when it approaches the maximum allowable maximum force, preventing sudden jarring end of travel stops.
AdaptabilityAdaptable to semi-active and active suspension for vehicle, seat and active track tensioner.
Wheeled Application Tracked Application
6x6 8x8