In control theory, the state-transition matrix is a matrix whose product with the state vector at an initial time gives at a later time . The state-transition matrix can be used to obtain the general solution of linear dynamical systems.
Linear systems solutions
The state-transition matrix is used to find the solution to a general state-space representation of a linear system in the following form
- ,
where are the states of the system, is the input signal, and are matrix functions, and is the initial condition at . Using the state-transition matrix , the solution is given by:[1][2]
The first term is known as the zero-input response and represents how the system's state would evolve in the absence of any input. The second term is known as the zero-state response and defines how the inputs impact the system.
Peano–Baker series
The most general transition matrix is given by the Peano–Baker series
where is the identity matrix. This matrix converges uniformly and absolutely to a solution that exists and is unique.[2]
Other properties
The state transition matrix satisfies the following relationships:
1. It is continuous and has continuous derivatives.
2, It is never singular; in fact and , where is the identity matrix.
3. for all .[3]
4. for all .
5. It satisfies the differential equation with initial conditions .
6. The state-transition matrix , given by
where the matrix is the fundamental solution matrix that satisfies
- with initial condition .
7. Given the state at any time , the state at any other time is given by the mapping
Estimation of the state-transition matrix
In the time-invariant case, we can define , using the matrix exponential, as . [4]
In the time-variant case, the state-transition matrix can be estimated from the solutions of the differential equation with initial conditions given by , , ..., . The corresponding solutions provide the columns of matrix . Now, from property 4, for all . The state-transition matrix must be determined before analysis on the time-varying solution can continue.
See also
References
- ↑ Baake, Michael; Schlaegel, Ulrike (2011). "The Peano Baker Series". Proceedings of the Steklov Institute of Mathematics. 275: 155–159. doi:10.1134/S0081543811080098. S2CID 119133539.
- 1 2 Rugh, Wilson (1996). Linear System Theory. Upper Saddle River, NJ: Prentice Hall. ISBN 0-13-441205-2.
- ↑ Brockett, Roger W. (1970). Finite Dimensional Linear Systems. John Wiley & Sons. ISBN 978-0-471-10585-5.
- ↑ Reyneke, Pieter V. (2012). "Polynomial Filtering: To any degree on irregularly sampled data". Automatika. 53 (4): 382–397. doi:10.7305/automatika.53-4.248. hdl:2263/21017. S2CID 40282943.
Further reading
- Baake, M.; Schlaegel, U. (2011). "The Peano Baker Series". Proceedings of the Steklov Institute of Mathematics. 275: 155–159. doi:10.1134/S0081543811080098. S2CID 119133539.
- Brogan, W.L. (1991). Modern Control Theory. Prentice Hall. ISBN 0-13-589763-7.