diff --git a/ct_optcon/examples/LQR.cpp b/ct_optcon/examples/LQR.cpp
new file mode 100644
index 0000000..dcd2ae0
--- /dev/null
+++ b/ct_optcon/examples/LQR.cpp
@@ -0,0 +1,59 @@
+/*!
+ * Simple example how to linearize a system and design an LQR controller.
+ *
+ * \example LQR.cpp
+ */
+
+
+#include <ct/optcon/optcon.h>  // also includes ct_core
+#include "exampleDir.h"
+
+int main(int argc, char** argv)
+{
+    // get the state and control input dimension of the oscillator
+    const size_t state_dim = ct::core::SecondOrderSystem::STATE_DIM;
+    const size_t control_dim = ct::core::SecondOrderSystem::CONTROL_DIM;
+
+    // create an auto-differentiable instance of the oscillator dynamics
+    ct::core::ADCGScalar w_n(50.0);
+    std::shared_ptr<ct::core::ControlledSystem<state_dim, control_dim, ct::core::ADCGScalar>> oscillatorDynamics(
+        new ct::core::tpl::SecondOrderSystem<ct::core::ADCGScalar>(w_n));
+
+    // create an Auto-Differentiation Linearizer with code generation on the quadrotor model
+    ct::core::ADCodegenLinearizer<state_dim, control_dim> adLinearizer(oscillatorDynamics);
+
+    // compile the linearized model just-in-time
+    adLinearizer.compileJIT();
+
+    // define the linearization point around steady state
+    ct::core::StateVector<state_dim> x;
+    x.setZero();
+    ct::core::ControlVector<control_dim> u;
+    u.setZero();
+    double t = 0.0;
+
+    // compute the linearization around the nominal state using the Auto-Diff Linearizer
+    auto A = adLinearizer.getDerivativeState(x, u, t);
+    auto B = adLinearizer.getDerivativeControl(x, u, t);
+
+    // load the weighting matrices
+    ct::optcon::TermQuadratic<state_dim, control_dim> quadraticCost;
+    quadraticCost.loadConfigFile(ct::optcon::exampleDir + "/lqrCost.info", "termLQR");
+    auto Q = quadraticCost.stateSecondDerivative(x, u, t);    // x, u and t can be arbitrary here
+    auto R = quadraticCost.controlSecondDerivative(x, u, t);  // x, u and t can be arbitrary here
+
+    // design the LQR controller
+    ct::optcon::LQR<state_dim, control_dim> lqrSolver;
+    ct::core::FeedbackMatrix<state_dim, control_dim> K;
+
+    std::cout << "A: " << std::endl << A << std::endl << std::endl;
+    std::cout << "B: " << std::endl << B << std::endl << std::endl;
+    std::cout << "Q: " << std::endl << Q << std::endl << std::endl;
+    std::cout << "R: " << std::endl << R << std::endl << std::endl;
+
+    lqrSolver.compute(Q, R, A, B, K);
+
+    std::cout << "LQR gain matrix:" << std::endl << K << std::endl;
+
+    return 1;
+}