A Discrete-Time Sliding Mode Control Method for Multi-Cylinder Hydraulic Press

Fault‐tolerant control strategy for multicylinder hydraulic press machine based on dynamic control allocation and adjustable multiobjective optimization

“…For the MCHPM with redundant actuator [10], the dynamic model of the slider can be described by $$$$ E\ddot{x}=A\dot{x}+ B\eta +d $$$$ where $$$ E\in {\mathbb{R}}^{n\times n} $$$ is the system inertia matrix, $$$ A\in {\mathbb{R}}^{n\times n} $$$ is the system state matrix, $$$ B\in {\mathbb{R}}^{n\times m}n<m $$$ is the control efficiency matrix, and $$$ x\in {R}^n $$$ is the state vector of the system (), which contain displacement and deflection angles. $$$ \eta \in {R}^m $$$ is a vector of the hydraulic driving force generated from hydraulic cylinders, and $$$ d\in {R}^n $$$ is the external disturbance vector.…”

“…However, most of the current researches focus on single‐cylinder hydraulic press machine rather than overactuated MCHPM. Fortunately, control allocation (CA) is a salient approach to distribute the desired total control demand to the individual actuators within the corresponding performance requirements and constraints for overactuated MCHPM [10]. In the field of overactuated systems, a number of CA algorithms [11] have been developed in the literature: Direct CA [12], daisy chaining [13], quadratic programming (QP) [14], numerical CA [15], dynamic control allocation [16, 17], and dynamic adaptive control allocation [18].…”

“…To the best of our knowledge, only some articles about single‐objective optimization (SOO) rather than MOO are considered in the allocation process of MCHPM. Aiming at optimizing the minimum driving force of the hydraulic cylinder, Jia et al [10] adopted the control allocation method to solve the overactuated problem presented in the MCHPM for the first time and used a combined controller to reduce energy consumption for meeting the actual actuator limit. Considering the limitation on the energy cost of subsystem, Zhang et al [19] developed a control allocation algorithm, which can turn constrained and convex optimization into the LMIs form, which also consider the dynamics and variations of the subsystems.…”

Position Output Adaptive Backstepping Control of Electro-Hydraulic Servo Closed-Pump Control System

“…As shown in Equation ( 27), the semi-positive Lyapunov function V 3 is constructed using Equations ( 13) and (20), separately. When we adopt Equations ( 29) and (32) as the input and parameter adaptive law of the system, its derivative .…”

“…An electro-hydraulic position servo system is a typical uncertain nonlinear system [7] that exhibits many nonlinear characteristics and model uncertainties [8]. At present, to address the problems due to of transient parameter time variation and nonlinear factors [9][10][11][12] Processes 2021, 9, 2209 2 of 18 in electro-hydraulic position servo system [13][14][15], researchers worldwide primarily adopt feedback linearization [16], sliding mode control [17][18][19][20][21][22][23], adaptive control [24][25][26][27], fuzzy control [28,29], and other technologies. As a systematic and structured design method is adopted in backstepping, uncertainties and unknown parameters can be addressed easily in the system [30].…”