System Identification and Model Predictive Control using CVXGEN for Electro-Hydraulic Actuator

Hydraulics have been widely used in heavy industries for decades. The demand for intelligent hydraulic control system has been increasing as tough robotic researches are getting more popular. Despite the high power to weight ratio delivery, the hydraulic actuator suffers from nonlinearity properties that cause difficulties in applying precise position control.  In this paper we proposed Model Predictive Control (MPC) to control an Electro-Hydraulic Actuator (EHA) where its dynamic characteristics is obtained through system identification method.  Control signal generation optimisation and constraint handling are seldom included in the conventional control system design process. Therefore we introduce CVXGEN, a Code Generator for Embedded Convex Optimization that utilises the Quadratic Programming (QP) interior-point solver for MPC optimisation problem. Predictive Functional Control (PFC) is used to validate the CVXGEN-MPC and both algorithms are implemented in simulation and experiment of EHA position control to highlight the optimisation and constraint handling problem. Control performance, control effort, constraint handling and disturbance handling of both methods are discussed

Modeling and force control of thin soft McKibben actuator

This paper presents the modeling of a thin soft McKibben actuator using the system identification (SI) method and its force control. Procedures from the system identification method are used to create a mathematical model (transfer function) from the test data. The autoregressive with exogenous input (ARX)model was chosen as the model structure of the system. Next, a PSO-PID controller was proposed for the force control of the actuator. The simulation data were verified against the test data for the force control using PSOPID and conventional PID. Results showed that the developed model represents the actual system by giving the same characteristics in the force control analysis in step, multi-step, and sinusoidal input