scholarly journals A Semilinear Parameter-Varying Observer Method for Fabric-Reinforced Soft Robots

2021 ◽  
Vol 8 ◽  
Author(s):  
Phuc D.H. Bui ◽  
Joshua A. Schultz
Keyword(s):  
Configuration Space ◽  
Controller Design ◽  
Ground Truth ◽  
Rate Of Change ◽  
Contact Forces ◽  
Chamber Pressure ◽  
Soft Robot ◽  
Linear Parameter Varying ◽  
Final Model ◽  
Parameter Varying

This paper presents an observer architecture that can estimate a set of configuration space variables, their rates of change and contact forces of a fabric-reinforced inflatable soft robot. We discretized the continuum robot into a sequence of discs connected by inextensible threads; this allows great flexibility when describing the robot’s behavior. At first, the system dynamics is described by a linear parameter-varying (LPV) model that includes a set of subsystems, each of which corresponds to a particular range of chamber pressure. A real-world challenge we confront is that the physical robot prototype exhibits a hysteresis loop whose directions depend on whether the chamber is inflating or deflating. In this paper we transform the hysteresis model to a semilinear model to avoid backward-in-time definitions, making it suitable for observer and controller design. The final model describing the soft robot, including the discretized continuum and hysteresis behavior, is called the semilinear parameter-varying (SPV) model. The semilinear parameter-varying observer architecture includes a set of sub-observers corresponding to the subsystems for each chamber pressure range in the SPV model. The proposed observer is evaluated through simulations and experiments. Simulation results show that the observer can estimate the configuration space variables and their rate of change with no steady-state error. In addition, experimental results display fast convergence of generalized contact force estimates and good tracking of the robot’s configuration relative to ground-truth motion capture data.

scholarly journals Output feedback controller design for polynomial linear parameter varying system via parameter-dependent Lyapunov functions

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401769032 ◽  
Author(s):  
Xiaobao Han ◽  
Zhenbao Liu ◽  
Huacong Li ◽  
Xianwei Liu
Keyword(s):  
Output Feedback ◽  
Optimization Problem ◽  
Controller Design ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Output Feedback Controller ◽  
Parameter Varying ◽  
Parameter Dependent

This article presents a new output feedback controller design method for polynomial linear parameter varying model with bounded parameter variation rate. Based on parameter-dependent Lyapunov function, the polynomial linear parameter varying system controller design is formulated into an optimization problem constrained by parameterized linear matrix inequalities. To solve this problem, first, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameter-dependent Lyapunov function, controller, and object coefficient matrices. Then, the control solving problem was reduced to a normal convex optimization problem with linear matrix inequalities constraint on a newly constructed convex polyhedron. Moreover, a parameter scheduling output feedback controller was achieved on the operating condition, which satisfies robust performance and dynamic performances. Finally, the feasibility and validity of the controller analysis and synthesis method are verified by the numerical simulation.

scholarly journals LPV-Based Controller Design of a Floating Piston Pneumatic Actuator

Actuators ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 98
Author(s):  
Ádám Szabó ◽  
Tamás Bécsi ◽  
Szilárd Aradi ◽  
Péter Gáspár
Keyword(s):  
High Speed ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Pneumatic Actuator ◽  
Pd Controller ◽  
Linear Parameter ◽  
Linear Quadratic ◽  
Minimum Order ◽  
Linear Parameter Varying ◽  
Parameter Varying

The paper presents the modeling and control design of a floating piston pneumatic gearbox actuator using a grid-based Linear Parameter Varying approach. First, the nonlinear model of the pneumatic actuator is presented, then it is transformed into a 6th order Linear Parameter Varying representation with endogenous scheduling parameters. The model is simplified based on empirical considerations to solve the controller synthesis and allow fast controller tuning. The developed Linear Parameter Varying controller is tested in simulations. Moreover, using a balanced truncation-model order reduction method, the minimum order of the controller is determined, which can provide acceptable performance. The simplified controller is implemented in an embedded environment and validated against the real target. Then, the validation results are compared with a gain-scheduled PD controller and a Linear Quadratic Regulator. The results show that by taking the time-varying nature of the scheduling parameters into account, the Linear Parameter Varying controller surpasses the Linear Quadratic Regulator, which cannot handle the high-speed transients around Neutral. Furthermore, the PD controller performs slightly better in two of the four test cases, although the Linear Parameter Varying controller has a higher level of fault tolerance.

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