Search results
Results from the WOW.Com Content Network
The state space or phase space is the geometric space in which the axes are the state variables. The system state can be represented as a vector , the state vector . If the dynamical system is linear, time-invariant, and finite-dimensional, then the differential and algebraic equations may be written in matrix form.
If the size of the state space is finite, calculating the size of the state space is a combinatorial problem. [4] For example, in the Eight queens puzzle, the state space can be calculated by counting all possible ways to place 8 pieces on an 8x8 chessboard. This is the same as choosing 8 positions without replacement from a set of 64, or
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 .
The set of possible combinations of state variable values is called the state space of the system. The equations relating the current state of a system to its most recent input and past states are called the state equations, and the equations expressing the values of the output variables in terms of the state variables and inputs are called the ...
The continuous-time case is similar to the discrete-time case but now one considers differential equations instead of difference equations: ˙ = + (), = + ().An added complication now however is that to include interesting physical examples such as partial differential equations and delay differential equations into this abstract framework, one is forced to consider unbounded operators.
The state of an isolated physical system is represented, at a fixed time , by a state vector | belonging to a Hilbert space called the state space. Separability is a mathematically convenient hypothesis, with the physical interpretation that the state is uniquely determined by countably many observations.
Example of a simple MDP with three states (green circles) and two actions (orange circles), with two rewards (orange arrows) A Markov decision process is a 4-tuple (,,,), where: is a set of states called the state space. The state space may be discrete or continuous, like the set of real numbers.
System in open-loop. If the closed-loop dynamics can be represented by the state space equation (see State space (controls)) _ ˙ = _ + _, with output equation _ = _ + _, then the poles of the system transfer function are the roots of the characteristic equation given by