313 lines
11 KiB
C++
313 lines
11 KiB
C++
#ifndef DEF_FlyByWire
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#define DEF_FlyByWire
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#include <cmath>
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#include <complex>
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#define HUGE_VALUE_REAL Real(1e20)
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// =============================================================================
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// General fly-by-wire helper functions
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// =============================================================================
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namespace FlyByWire
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{
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typedef double Real;
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typedef std::complex<Real> Complex;
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/// Computes the heading error using the shortest route from hdg to tgt, both expressed in radians.
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Real Hdg_err(Real tgt, Real hdg);
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/// Computes the heading error using the shortest route from hdg to tgt, both expressed in degrees.
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Real Hdg_err_deg(Real tgt, Real hdg);
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/// Computes the median of the triplet (a, b, c). Useful to reject an invalid measurement from a triplet of sensors, or to mix 3 control laws in a continuous fashion (C0 continuity).
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/// Internally, it is implemented as a sorting network. The middle value is the median of the triplet.
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Real Vote(Real a, Real b, Real c);
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/// Copies the input as long as it's not within +/- a from the origin. The output is then 0.
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Real Deadzone(Real x, Real a);
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/// Saturation function. Ensures that a <= x <= b.
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Real Sat1(Real x, Real a, Real b);
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/// Limits the rate of the signal x(t) : [dx/dt](t) to the interval [dy_dt_min, dy_dt_max].
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/// Use like a recursive filter.
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///
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/// \variable x_n : Input value at step n
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/// \variable y_n_1 : Output value at step n-1
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/// \variable dy_dt_min : Min derivative
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/// \variable dy_dt_max : Max derivative
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/// \variable dt : Time step
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/// \return y[n] rate-limited.
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Real Ratelim(Real x_n, Real y_n_1, Real dy_dt_min, Real dy_dt_max, Real dt);
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/// Rate limiter implemented as a self-contained recursive filter.
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class RateLimiter
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{
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public:
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/// Creates the RateLimiter object with the specified limits, and initial value. By default, y0 = 0.
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RateLimiter(Real dy_dt_min, Real dy_dt_max, Real dt, Real y_ = Real(0.));
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/// Applies the rate limiter filter to the input x[n] (parameter x_n) and returns the result y[n].
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Real Filter(Real x_n);
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public:
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Real dy_dt_min; //!< Min rate.
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Real dy_dt_max; //!< Max rate.
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Real dt; //!< Time step.
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Real y_n_1; //!< Previous filter value.
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};
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/// Heaviside function. 1 when x >= 0, 0 otherwise.
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Real Heaviside(Real x);
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// =============================================================================
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// IRR Filters from the continuous Laplace transfer function.
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// =============================================================================
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/// 1st order integrator implemented using the trapezoïdal method.
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/// G(s) = 1/s
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/// The integrator can also be limited using the lower_bound and upper_bound parameters.
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/// By default, the integrator is not bounded.
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///
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/// The class is to be used like so :
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///
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/// flt = Integrator1(Ts)
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///
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/// while control/filtering loop:
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///
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/// y_n = flt.Filter(x_n)
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///
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class Integrator1
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{
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public:
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/// Creates an integrator object. By default, y0 = 0, and the limits are +/- HUGE_VALUE_REAL.
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Integrator1(Real Ts_, Real y_ = Real(0.), Real lower_bound_ = -HUGE_VALUE_REAL, Real upper_bound_ = HUGE_VALUE_REAL);
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/// Sets the state of the filter so that it can be initialized at any value.
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/// By default, the states are initialized to 0.
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void SetState(Real y_ = Real(0.), Real x_ = Real(0.));
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/// Computes the next output value of the filter y[n] from the next input value x[n].
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Real Filter(Real x_n);
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public:
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Real Ts;//!< Time step.
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Real lower_bound;//!< Lower bound.
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Real upper_bound;//!< Upper bound.
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Real x_n_1;//!< x[n-1].
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Real y_n_1;//!< y[n-1].
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};
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/// First order discretetized filter. The coefficients are automatically computed from the continuous-time transfer function :
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///
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/// Y b1 s + b0
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/// G(s) = --- = ---------
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/// X a1 s + a0
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///
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/// The Laplace transfer function is first discretized using the Tustin method (sampling period Ts).
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///
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/// Y -2 b1 + b0 Ts + (2 b1 + b0 Ts) z
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/// G(z) = --- = --------------------------------
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/// X -2 a1 + a0 Ts + (2 a1 + a0 Ts) z
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///
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/// The coefficients of the recurrence equation are then computed :
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///
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/// 2 b1 + b0 Ts
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/// C(x[n]) = ------------
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/// 2 a1 + a0 Ts
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///
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///
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/// -2 b1 + b0 Ts
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/// C(x[n-1]) = ------------
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/// 2 a1 + a0 Ts
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///
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///
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/// 2 a1 - a0 Ts
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/// C(y[n-1]) = ------------
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/// 2 a1 + a0 Ts
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///
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/// The class is to be used like so :
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///
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/// flt = filter1(b1, b0, a1, a0, Ts)
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///
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///
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/// while control/filtering loop:
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///
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/// y_n = flt.Filter(x_n)
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///
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///
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/// The necessary previous values y[n-1] and x[n-1] are automatically stored within the object.
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class Filter1
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{
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public:
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/// Creates a Filter1 object from the continuous TF's coefficients.
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Filter1(Real b1, Real b0, Real a1, Real a0, Real Ts, Real y0 = Real(0.));
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/// Computes the filter coefficients from the continuous TF's coefficients.
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void ComputeCoeffsFromContinuousTF(Real b1, Real b0, Real a1, Real a0, Real Ts);
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/// Sets the state of the filter so that it can be initialized at any value.
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/// By default, the states are initialized to 0.
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void SetState(Real y_ = Real(0.), Real x_ = Real(0.));
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/// Computes the next output value of the filter y[n] from the next input value x[n].
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Real Filter(Real x_n);
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/// First order discretized filter that computes the derivative of the input signal.
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/// tau controls how fast the filter approximates the derivative of the input.
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/// A good default value is 0.01.
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///
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/// s
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/// G(s) = ---------
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/// tau*s + 1
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///
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static Filter1 FilteredDerivative(Real Ts, Real tau = 0.01);
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public:
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Real cx_n; //!< C(x[n])
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Real cx_n_1; //!< C(x[n-1])
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Real cy_n_1; //!< C(y[n-1])
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Real x_n_1; //!< x[n-1]
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Real y_n_1; //!< y[n-1]
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};
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/// Second order discretetized filter. The coefficients are automatically computed from the continuous-time transfer function :
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///
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/// Y b2 s^2 + b1 s + b0
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/// G(s) = --- = ------------------
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/// X a2 s^2 + a1 s + a0
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///
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/// The Laplace transfer function is first discretized using the Tustin method (sampling period Ts).
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///
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/// Y 4 b2 - 2 b1 Ts + b0 Ts^2 + (-8 b2 + 2 b0 Ts^2) z + (4 b2 + 2 b1 Ts + b0 Ts^2) z^2
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/// G(z) = --- = ---------------------------------------------------------------------------------
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/// X 4 a2 - 2 a1 Ts + a0 Ts^2 + (-8 a2 + 2 a0 Ts^2) z + (4 a2 + 2 a1 Ts + a0 Ts^2) z^2
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///
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/// The coefficients of the recurrence equation are then computed :
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///
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/// 4 b2 + 2 b1 Ts + b0 Ts^2
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/// C(x[n]) = ------------------------
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/// 4 a2 + 2 a1 Ts + a0 Ts^2
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///
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///
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/// -8 b2 + 2 b0 Ts^2
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/// C(x[n-1]) = ------------------------
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/// 4 a2 + 2 a1 Ts + a0 Ts^2
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///
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///
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/// 4 b2 - 2 b1 Ts + b0 Ts^2
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/// C(x[n-2]) = ------------------------
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/// 4 a2 + 2 a1 Ts + a0 Ts^2
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///
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///
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/// -8 a2 + 2 a0 Ts^2
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/// C(y[n-1]) = ------------------------
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/// 4 a2 + 2 a1 Ts + a0 Ts^2
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///
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///
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/// 4 a2 - 2 a1 Ts + a0 Ts^2
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/// C(y[n-2]) = ------------------------
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/// 4 a2 + 2 a1 Ts + a0 Ts^2
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///
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/// The class is to be used like so :
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///
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/// flt = filter2(b2, b1, b0, a2, a1, a0, Ts)
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///
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/// while control/filtering loop:
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///
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/// y_n = flt.Filter(x_n)
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///
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/// The necessary previous values y[n-1], y[n-2], x[n-1], and x[n-2] are automatically stored within the object.
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class Filter2
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{
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public:
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/// Creates a Filter2 object from the continuous TF's coefficients.
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Filter2(Real b2, Real b1, Real b0, Real a2, Real a1, Real a0, Real Ts, Real y0 = Real(0.));
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/// Computes the filter coefficients from the continuous TF's coefficients.
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void ComputeCoeffsFromContinuousTF(Real b2, Real b1, Real b0, Real a2, Real a1, Real a0, Real Ts);
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/// Sets the state of the filter so that it can be initialized at any value.
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/// By default, the states are initialized to 0.
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void SetState(Real y_ = Real(0.), Real x_ = Real(0.));
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/// Computes the next output value of the filter y[n] from the next input value x[n].
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Real Filter(Real x_n);
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/// Creates the transfer function from its poles, zeros, and a gain.
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///
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/// a (s - z1) (s - z2)
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/// G(s) = -------------------
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/// (s - p1) (s - p2)
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///
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static Filter2 FromPolesAndZeros(Real a, Complex p1, Complex p2, Complex z1, Complex z2, Real Ts);
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/// Creates the transfer function from its poles, and the static gain a.
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/// The poles can be real, or complex conjugate.
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///
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/// a p1 p2
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/// G(s) = -----------------
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/// (s - p1) (s - p2)
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///
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static Filter2 FromPoles(Real a, Complex p1, Complex p2, Real Ts);
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/// Second order discretetized low-pass biquadratic filter.
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///
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/// The filter is parametrized using the cutoff frequency omega in rad/s, and the quality factor Q.
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/// For no resonnance peak, use Q < 1/2
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///
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/// w^2
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/// G(s) = -----------------
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/// s^2 + w/Q*s + w^2
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///
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static Filter2 Lowpass(Real omega, Real Q, Real Ts);
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/// Second order discretetized high-pass biquadratic filter.
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/// The filter is parametrized using the cutoff frequency omega in rad/s, and the quality factor Q.
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/// For no resonnance peak, use Q < 1/2
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///
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/// s^2
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/// G(s) = -----------------
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/// s^2 + w/Q*s + w^2
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///
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static Filter2 Highpass(Real omega, Real Q, Real Ts);
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/// Second order discretetized band-pass biquadratic filter.
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/// The filter is parametrized using the cutoff frequency omega in rad/s, and the quality factor Q.
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/// For no resonnance peak, use Q < 1/2
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///
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/// w/Q*s
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/// G(s) = -----------------
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/// s^2 + w/Q*s + w^2
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///
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static Filter2 Bandpass(Real omega, Real Q, Real Ts);
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/// Second order discretetized band-stop biquadratic filter.
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/// The filter is parametrized using the cutoff frequency omega in rad/s, and the quality factor Q.
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/// For no resonnance peak, use Q < 1/2
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///
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/// s^2 + w^2
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/// G(s) = -----------------
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/// s^2 + w/Q*s + w^2
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///
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static Filter2 Bandstop(Real omega, Real Q, Real Ts);
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public:
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Real cx_n; //!< C(x[n])
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Real cx_n_1; //!< C(x[n-1])
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Real cx_n_2; //!< C(x[n-2])
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Real cy_n_1; //!< C(y[n-1])
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Real cy_n_2; //!< C(y[n-2])
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Real x_n_1; //!< x[n-1]
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Real x_n_2; //!< y[n-2]
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Real y_n_1; //!< x[n-1]
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Real y_n_2; //!< y[n-2]
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};
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}
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#endif
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