ss — Create continuous-time state-space model objects from A, B, C, and D matrices.

ss(A, B, C, D) creates a state-space model object from numeric system matrices. It follows MATLAB-compatible matrix-shape validation for state, input, output, and direct-feedthrough terms.

Syntax

sys = ss(A, B, C, D)
sys = ss(A, B, C, D, Ts)
sys = ss(A, B, C, D, "Ts", Ts)
sys = ss(A, B, C, D, name, value, ...)

Inputs

Returns

Errors

How ss works

• Returns an object whose class name is ss.
• Stores A, B, C, D, Ts, InputDelay, OutputDelay, StateName, InputName, and OutputName properties.
• Preserves the input matrix orientations on the returned object.
• Uses continuous-time defaults with Ts equal to 0.
• ss(A, B, C, D, Ts) stores a finite non-negative sample time.
• ss(A, B, C, D, 'Ts', Ts) and ss(A, B, C, D, 'SampleTime', Ts) store a finite non-negative sample time.
• Numeric scalar inputs are treated as 1-by-1 matrices and are accepted only when the resulting dimensions are consistent.
• Typed integer matrices and sample times are RunMat-only extensions because the compatibility target does not enumerate their storage classes. Each value must be exactly representable as double before the state-space object stores binary64 matrix or sample-time metadata.
• Automatically resident inputs may gather transparently for host object construction; an explicit gpuArray input is a separately gated RunMat extension.
• Complex, sparse, descriptor-form, uncertain, identified, and generalized models are not supported in this initial implementation.

GPU memory and residency

ss is a host-side object constructor. gpuArray matrix inputs are gathered before object construction, and the returned state-space object does not live on the GPU.

Examples

Creating a continuous-time state-space model

A = [0 1; -2 -3];
B = [0; 1];
C = [1 0];
D = 0;
G = ss(A, B, C, D);
class(G)

Expected output:

ans = "ss"

Reading stored state-space matrices

G = ss([0 1; -2 -3], [0; 1], [1 0], 0);
fprintf("%.0f %.0f %.0f %.0f %.0f %.0f\n", G.A(1), G.A(2), G.A(3), G.A(4), G.B(1), G.B(2));

Expected output:

0 -2 1 -3 0 1

Creating a discrete-time model

G = ss(0.5, 1, 1, 0, 0.1);
fprintf("%.1f\n", G.Ts);

Expected output:

0.1

Specifying sample time with a name-value pair

G = ss(0.5, 1, 1, 0, 'SampleTime', 0.2);
fprintf("%.1f\n", G.Ts);

Expected output:

0.2

How RunMat validates ss

ss validates finite real matrix inputs, state-space dimension consistency, supported name-value options, and sample-time constraints before constructing the host-side object. Unit and integration tests cover continuous and discrete constructors, property access, invalid dimensions, invalid sample times, descriptor signatures, and gpuArray gathering.

• Implementation: `crates/runmat-runtime/src/builtins/control/ss.rs`

See Correctness & Trust for the full methodology and coverage table.

Using ss with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how ss changes the result.

FAQ

Related Control functions

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how ss is executed, line by line, in Rust.

• View the source for ss in Rust on GitHub
• Learn how the RunMat runtime works
• Found a bug? Open an issue with a minimal reproduction.

About RunMat

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