半舵旗舰版（功率控制有更改）

modules/algorithm/rls.c

@@ -0,0 +1,99 @@
+#include "rls.h"
+
+#include <string.h>
+
+void RLSInit(RLSInstance *rls, uint8_t order, float lambda, float init_covariance, const float *initial_theta)
+{
+    if (rls == 0) {
+        return;
+    }
+
+    memset(rls, 0, sizeof(RLSInstance));
+
+    if (order == 0u) {
+        return;
+    }
+    if (order > RLS_MAX_ORDER) {
+        order = RLS_MAX_ORDER;
+    }
+    if (lambda < 0.01f) {
+        lambda = 0.01f;
+    }
+    if (lambda > 1.0f) {
+        lambda = 1.0f;
+    }
+    if (init_covariance <= 0.0f) {
+        init_covariance = 1000.0f;
+    }
+
+    rls->order = order;
+    rls->lambda = lambda;
+    rls->initialized = 1u;
+
+    for (uint8_t i = 0u; i < order; i++) {
+        rls->theta[i] = initial_theta != 0 ? initial_theta[i] : 0.0f;
+        rls->covariance[i][i] = init_covariance;
+    }
+}
+
+float RLSPredict(const RLSInstance *rls, const float *x)
+{
+    if (rls == 0 || x == 0 || rls->initialized == 0u) {
+        return 0.0f;
+    }
+
+    float prediction = 0.0f;
+    for (uint8_t i = 0u; i < rls->order; i++) {
+        prediction += rls->theta[i] * x[i];
+    }
+    return prediction;
+}
+
+float RLSUpdate(RLSInstance *rls, const float *x, float y)
+{
+    float px[RLS_MAX_ORDER] = {0.0f};
+    float xtp[RLS_MAX_ORDER] = {0.0f};
+
+    if (rls == 0 || x == 0 || rls->initialized == 0u) {
+        return 0.0f;
+    }
+
+    const uint8_t order = rls->order;
+    const float prediction = RLSPredict(rls, x);
+    const float error = y - prediction;
+
+    for (uint8_t i = 0u; i < order; i++) {
+        for (uint8_t j = 0u; j < order; j++) {
+            px[i] += rls->covariance[i][j] * x[j];
+            xtp[i] += x[j] * rls->covariance[j][i];
+        }
+    }
+
+    float denominator = rls->lambda;
+    for (uint8_t i = 0u; i < order; i++) {
+        denominator += x[i] * px[i];
+    }
+    if (denominator <= 1.0e-6f) {
+        denominator = 1.0e-6f;
+    }
+
+    for (uint8_t i = 0u; i < order; i++) {
+        rls->gain[i] = px[i] / denominator;
+        rls->theta[i] += rls->gain[i] * error;
+    }
+
+    for (uint8_t i = 0u; i < order; i++) {
+        for (uint8_t j = 0u; j < order; j++) {
+            rls->covariance[i][j] = (rls->covariance[i][j] - rls->gain[i] * xtp[j]) / rls->lambda;
+        }
+    }
+
+    rls->last_prediction = prediction;
+    rls->last_error = error;
+    return prediction;
+}
+
+const float *RLSGetTheta(const RLSInstance *rls)
+{
+    return rls != 0 ? rls->theta : 0;
+}

modules/algorithm/rls.h

@@ -0,0 +1,25 @@
+#ifndef RLS_H
+#define RLS_H
+
+#include <stdint.h>
+
+#define RLS_MAX_ORDER 4u
+
+typedef struct
+{
+    uint8_t order;
+    uint8_t initialized;
+    float lambda;
+    float theta[RLS_MAX_ORDER];
+    float covariance[RLS_MAX_ORDER][RLS_MAX_ORDER];
+    float gain[RLS_MAX_ORDER];
+    float last_prediction;
+    float last_error;
+} RLSInstance;
+
+void RLSInit(RLSInstance *rls, uint8_t order, float lambda, float init_covariance, const float *initial_theta);
+float RLSPredict(const RLSInstance *rls, const float *x);
+float RLSUpdate(RLSInstance *rls, const float *x, float y);
+const float *RLSGetTheta(const RLSInstance *rls);
+
+#endif