Observer design for apex height and vertical velocity of a single-leg hopping robot during stance phase

Robotica ◽  
2021 ◽  
pp. 1-12
Author(s):  
Ashish Prakash ◽  
Gagan Deep Meena
Keyword(s):  
Vertical Velocity ◽  
Stance Phase ◽  
Estimation Error ◽  
Vertical Direction ◽  
The State ◽  
Observer Design ◽  
Space Representation ◽  
State Space Representation ◽  
Hopping Robot ◽  
Apex Height

Abstract This article proposes an observer design for two important variables in the studies of single-leg hopping robot (SLHR), the apex height, and the vertical velocity of SLHR during its stance phase. At first, the Euler–Lagrange (EL) dynamics of SLHR are obtained and apex height is identified in the state-space representation of the EL dynamics. Apex height is the state variable that represents the robot body’s height at the top point, which keeps on changing as the robot functions. Vertical velocity is the velocity of the robot in the vertical direction. An observer design is presented in this article which will estimate these variables when required. The quality of the estimation is validated by the simulation results where the estimation error is zero which means the model output is correct and observer performance is good.

Observer design and a separation principle for linear discrete-time descriptor sysems

2020 ◽  
Author(s):  
Lázaro Ismael Hardy Llins ◽  
Daniel Coutinho
Keyword(s):  
Discrete Time ◽  
Estimation Error ◽  
Observer Design ◽  
Descriptor Systems ◽  
Descriptor System ◽  
Space Representation ◽  
Separation Principle ◽  
State Space Representation ◽  
State Observers ◽  
Error Dynamics

This paper addresses the design of state observers for linear discrete-time descriptor systems. Assuming that the original descriptor system is completely observable, an equivalent (standard) state-space representation of the system is proposed which preserves the system observability. Then, an LMI based approach is proposed for designing a Luenberger-like observer. In addition, a separation principle is demonstrated considering the estimation error dynamics and the closed-loop representation of the original descriptor system. Then, the observer design is extended to cope with model disturbances in an H1 sense. The eectiveness of the proposed methodology is illustrated by numerical examples.

Impulsive finite-time observer design for uncertain positive linear systems with L2-gain analysis

2020 ◽  
Vol 42 (10) ◽  
pp. 1871-1881 ◽  
Author(s):  
Morteza Motahhari ◽  
Mohammad Hossein Shafiei
Keyword(s):  
Linear Systems ◽  
Finite Time ◽  
Estimation Error ◽  
Sufficient Conditions ◽  
The State ◽  
Observer Design ◽  
Linear Matrix ◽  
Time Interval ◽  
State Variables ◽  
L2 Gain

This paper is concerned with the design of a finite-time positive observer (FTPO) for continuous-time positive linear systems, which is robust regarding the L2-gain performance. In positive observers, the estimation of the state variables is always nonnegative. In contrast to previous positive observers with asymptotic convergence, an FTPO estimates positive state variables in a finite time. The proposed FTPO observer, using two Identity Luenberger observers and based on the impulsive framework, estimates exactly the state variables of positive systems in a predetermined time interval. Furthermore, sufficient conditions are given in terms of linear matrix inequalities (LMIs) to guarantee the L2-gain performance of the estimation error. Finally, the performance and robustness of the proposed FTPO are validated using numerical simulations.

scholarly journals Shannon Entropy Analysis of the Genome Code

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
J. A. Tenreiro Machado
Keyword(s):  
Dynamical Systems ◽  
State Space ◽  
Shannon Entropy ◽  
Large Volume ◽  
The State ◽  
Space Representation ◽  
Entropy Analysis ◽  
Genomic Information ◽  
State Space Representation

This paper studies the chromosome information of twenty five species, namely, mammals, fishes, birds, insects, nematodes, fungus, and one plant. A quantifying scheme inspired in the state space representation of dynamical systems is formulated. Based on this algorithm, the information of each chromosome is converted into a bidimensional distribution. The plots are then analyzed and characterized by means of Shannon entropy. The large volume of information is integrated by averaging the lengths and entropy quantities of each species. The results can be easily visualized revealing quantitative global genomic information.

Furnace Modelling Using State Space Representation

2006 ◽  
Vol 3 (1) ◽  
pp. 37
Author(s):  
Razidah Ismail
Keyword(s):  
State Space ◽  
Power Plants ◽  
Controller Design ◽  
Cost Savings ◽  
Combined Cycle ◽  
The State ◽  
Space Representation ◽  
State Variables ◽  
State Space Representation ◽  
Space Modeling

The state space modeling approach was developed to cope with the demand and performance due to the increase in system complexity, which may have multiple inputs and multiple outputs (MIMO). This approach is based on time-domain analysis and synthesis using state variables. This paper describes the development of a state space representation of a furnace system of a combined cycle power plant. Power plants will need to operate optimally so as to stay competitive, as even a small improvement in energy efficiency would involve substantial cost savings. Both the quantitative and qualitative analyses of the state space representation of the furnace system are discussed. These include the responses of systems excited by certain inputs and the structural properties of the system. The analysis on the furnace system showed that the system is bounded input and bounded output stable, controllable and observable. In practice, the state space formulation is very important for numerical computation and controller design, and can be extended for time-varying systems.

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