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attainable set for discrete system

Understanding the Attainable Set: A Key Concept for Controllability in Discrete Systems

In the realm of control theory, understanding how a system behaves under various inputs is crucial for achieving desired outcomes. For discrete-time systems, a fundamental concept in this endeavor is the attainable set. This article delves into the concept of the attainable set, highlighting its significance in analyzing the controllability of discrete systems.

Definition and Interpretation

The attainable set, denoted by K(t₀, t₁), represents the collection of all possible states a discrete system can reach at time t₁ starting from zero initial conditions at time t₀. In other words, it encapsulates the "reachable space" of the system within the specified time interval.

Mathematically, the attainable set is defined as:

K(t₀, t₁) = {x ∈ ℝⁿ | x = Σ_(j=t₀)^(t₁-1) F(t₁, j+1)B(j)u(j)}

where:

  • x is the state vector at time t₁
  • F(t₁, j+1) is the state transition matrix from time j+1 to time t₁
  • B(j) is the input matrix at time j
  • u(j) is the input vector at time j
  • ℝⁿ represents the n-dimensional real space

This definition emphasizes that the attainable set is constructed by applying all possible input sequences u(j) over the interval [t₀, t₁] and observing the resulting state vectors x.

Controllability and the Attainable Set

The concept of the attainable set is closely intertwined with the notion of controllability. A discrete system is said to be controllable in the interval [t₀, t₁] if any state x in the state space can be reached from the initial state x(t₀) using an appropriate input sequence.

Importantly, the controllability of a discrete system within a given time interval is directly related to its attainable set. The system is controllable in [t₀, t₁] if and only if its attainable set K(t₀, t₁) spans the entire state space ℝⁿ.

Example: Consider a system with a 2-dimensional state space. If the attainable set K(t₀, t₁) is a line in this space, the system is not controllable because it cannot reach states outside this line. However, if K(t₀, t₁) encompasses the entire 2-dimensional space, the system is controllable.

Applications of the Attainable Set

The concept of the attainable set proves valuable in various applications related to controllability:

  • Determining controllability: By analyzing the structure and properties of the attainable set, one can determine whether a system is controllable within a given time interval.
  • Optimal control: The attainable set can provide valuable insights for designing optimal control strategies that achieve desired states in the shortest possible time or with minimal energy consumption.
  • Robust control: Understanding the attainable set allows for designing controllers that are robust to uncertainties and disturbances in the system dynamics.
  • Reachability analysis: The attainable set forms the basis for reachability analysis, which involves determining the set of states that can be reached from a given initial state under certain constraints.

Conclusion

The attainable set is a fundamental concept in the analysis of discrete-time systems. It provides a powerful tool for understanding controllability, designing optimal controllers, and performing reachability analysis. By leveraging the insights gained from the attainable set, researchers and engineers can gain deeper understanding of system behavior and develop effective control strategies for a wide range of applications.


Test Your Knowledge

Quiz: Understanding the Attainable Set

Instructions: Choose the best answer for each question.

1. What does the attainable set, K(t₀, t₁), represent?

a) The collection of all possible states a system can reach at time t₁ starting from zero initial conditions at time t₀. b) The set of all possible input sequences that can be applied to the system. c) The set of all possible initial states the system can start from. d) The set of all possible output signals the system can produce.

Answer

a) The collection of all possible states a system can reach at time t₁ starting from zero initial conditions at time t₀.

2. Which of the following is NOT a factor in determining the attainable set?

a) The initial state of the system. b) The input matrix at each time step. c) The state transition matrix at each time step. d) The output matrix at each time step.

Answer

d) The output matrix at each time step.

3. A discrete system is considered controllable in the interval [t₀, t₁] if:

a) Its attainable set is empty. b) Its attainable set spans the entire state space. c) Its attainable set is a single point. d) Its attainable set is a line in the state space.

Answer

b) Its attainable set spans the entire state space.

4. What is the practical significance of the attainable set concept?

a) It helps determine the stability of a system. b) It helps design controllers that achieve desired states. c) It helps understand the system's response to different inputs. d) All of the above.

Answer

d) All of the above.

5. Which of the following is NOT a potential application of the attainable set concept?

a) Analyzing the controllability of a system. b) Designing optimal control strategies. c) Predicting the future behavior of a system. d) Determining the stability of a system.

Answer

d) Determining the stability of a system.

Exercise: Attainable Set Analysis

Problem: Consider a discrete-time system with the following state-space representation:

  • State vector: x = [x₁(t) x₂(t)]ᵀ
  • Input vector: u(t)
  • State transition matrix: F = [[1 1], [0 1]]
  • Input matrix: B = [[1], [0]]

Task: Determine the attainable set K(0, 2) for this system.

Exercice Correction

The attainable set K(0, 2) is the set of all possible states the system can reach at time t = 2, starting from zero initial conditions at time t = 0.
We can calculate the attainable set using the formula:
K(0, 2) = {x ∈ ℝ² | x = Σ_(j=0)^(1) F(2, j+1)B(j)u(j)}
For t = 2, j = 0 and j = 1.
So, we have:
x = F(2, 1)B(0)u(0) + F(2, 2)B(1)u(1)
F(2, 1) = F * F = [[1 1], [0 1]] * [[1 1], [0 1]] = [[1 2], [0 1]]
F(2, 2) = F = [[1 1], [0 1]]
Therefore,
x = [[1 2], [0 1]] * [[1], [0]] * u(0) + [[1 1], [0 1]] * [[1], [0]] * u(1)
x = [[1], [0]] * u(0) + [[1], [0]] * u(1)
x = [[u(0) + u(1)], [0]]
Thus, the attainable set K(0, 2) is the set of all states of the form [u(0) + u(1), 0], where u(0) and u(1) are arbitrary inputs.
This means that the system can reach any state on the x-axis, but cannot reach any state with a non-zero y-coordinate. Therefore, the system is not controllable in the interval [0, 2].


Books

  • "Discrete-Time Control Systems" by Genaro S. C. Bueno: A comprehensive resource on discrete-time systems, covering topics like controllability, observability, and attainable sets.
  • "Linear Systems" by Thomas Kailath: A classic text providing in-depth treatment of linear systems theory, including controllability analysis and the concept of attainable sets.
  • "Nonlinear Control Systems" by Hassan Khalil: Discusses the concepts of controllability and attainability in the context of nonlinear systems.
  • "Modern Control Engineering" by Katsuhiko Ogata: A widely used textbook for undergraduate control engineering courses that provides an introduction to controllability and related topics.
  • "Optimal Control Theory" by Donald Kirk: Covers the concept of attainability in the context of optimal control problems, offering a deeper theoretical understanding.

Articles

  • "Attainable Sets of Discrete-Time Systems: A Geometric Approach" by J. D. L. Morais: This paper proposes a geometric approach to compute the attainable set, making it more practical for analyzing specific systems.
  • "Controllability and Observability of Discrete-Time Systems" by E. Sontag: Provides a rigorous mathematical treatment of controllability and observability in discrete-time systems, outlining the significance of the attainable set.
  • "The Attainable Set and Controllability of Discrete-Time Systems with Bounded Inputs" by M. J. G. van den Bergh: Discusses the limitations of attainability when dealing with bounded inputs, highlighting real-world constraints in control systems.
  • "On the Controllability of Linear Discrete-Time Systems with Bounded Inputs" by D. L. Lukens: Explores the relationship between the attainable set and controllability in discrete-time systems with bounded inputs, offering insights into practical limitations.

Online Resources

  • Control Systems Toolbox Documentation: Provides a comprehensive overview of the Control Systems Toolbox in MATLAB, including tools and functions for analyzing controllability and computing the attainable set.
  • Wikipedia Article on "Controllability": Offers a basic explanation of controllability in systems theory, outlining the concept of attainable sets and its importance.
  • MIT OpenCourseware: Control Systems: This online course from MIT offers a detailed introduction to control systems, covering concepts like controllability, observability, and attainability.
  • Stanford University - EE363: Linear Dynamical Systems: This course provides a comprehensive treatment of linear systems, including controllability and related concepts like attainability and reachability analysis.

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